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1

Baker, Kyri A. "Coordination of Resources Across Areas for the Integration of Renewable Generation: Operation, Sizing, and Siting of Storage Devices." Research Showcase @ CMU, 2014. http://repository.cmu.edu/dissertations/465.

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An increased penetration of renewable energy into the electric power grid is desirable from an environmental standpoint as well as an economical one. However, renewable sources such as wind and solar energy are often variable and intermittent, and additionally, are non-dispatchable. Also, the locations with the highest amount of available wind or solar may be located in areas that are far from areas with high levels of demand, and these areas may be under the control of separate, individual entities. In this dissertation, a method that coordinates these areas, accounts for the variability and intermittency, reduces the impact of renewable energy forecast errors, and increases the overall social benefit in the system is developed. The approach for the purpose of integrating intermittent energy sources into the electric power grid is considered from both the planning and operations stages. In the planning stage, two-stage stochastic optimization is employed to find the optimal size and location for a storage device in a transmission system with the goal of reducing generation costs, increasing the penetration of wind energy, alleviating line congestions, and decreasing the impact of errors in wind forecasts. The size of this problem grows dramatically with respect to the number of variables and constraints considered. Thus, a scenario reduction approach is developed which makes this stochastic problem computationally feasible. This scenario reduction technique is derived from observations about the relationship between the variance of locational marginal prices corresponding to the power balance equations and the optimal storage size. Additionally, a probabilistic, or chance, constrained model predictive control (MPC) problem is formulated to take into account wind forecast errors in the optimal storage sizing problem. A probability distribution of wind forecast errors is formed and incorporated into the original storage sizing problem. An analytical form of this constraint is derived to directly solve the optimization problem without having to use Monte-Carlo simulations or other techniques that sample the probability distribution of forecast errors. In the operations stage, a MPC AC Optimal Power Flow problem is decomposed with respect to physical control areas. Each area performs an independent optimization and variable values on the border buses between areas are exchanged at each Newton-Raphson iteration. Two modifications to the Approximate Newton Directions (AND) method are presented and used to solve the distributed MPC optimization problem, both with the intention of improving the original AND method by improving upon the convergence rate. Methods are developed to account for numerical difficulties encountered by these formula- tions, specifically with regards to Jacobian singularities introduced due to the intertemporal constraints. Simulation results show convergence of the decomposed optimization problem to the centralized result, demonstrating the benefits of coordinating control areas in the IEEE 57- bus test system. The benefit of energy storage in MPC formulations is also demonstrated in the simulations, reducing the impact of the fluctuations in the power supply introduced by intermittent sources by coordinating resources across control areas. An overall reduction of generation costs and increase in renewable penetration in the system is observed, with promising results to effectively and efficiently integrate renewable resources into the electric power grid on a large scale.
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Isaacs, Andrew C. "Siting and sizing of embedded generators : a Jamaican network analysis." Thesis, University of Bath, 2011. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.557791.

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Increasing costs associated with fossil fuel generation and a recognition and acceptance of the finite nature of this resource, have partially contributed to the growing popularity of alternative energy generation technology. International environmental treaties have also forced many states, primarily developing states, to deliberately review their fuels use. Jamaica having such a challenge requires accurate information regarding the impact of integrating generation from such technologies into its existing network. However, given a lack of resources, little work has been done to gather the relevant data that is required to evaluate the impact of embedded generation. Instead the findings from networks in other jurisdictions that have different operational and technical characteristics have been utilized. Anecdotal information regarding the availability of satisfactory renewable resources and the minimal impact that certain levels of integration will have on the existing network abounds among the engineering community on Jamaica. This research reviews the electricity and energy sectors of Jamaica. It further considers the efforts made by policy makers to fulfil the energy needs through a possible mix of fossil and renewable sources. Focus is then shifted to the analysis of available wind resource data which is then modelled to represent usable wind data for electricity generation. Actual system data is then used to produce an acceptable model of the current transmission network. The operation of the network is then considered on varying generation and loading conditions both with and without the inclusion of renewable sources. A final assessment of the impact of such sources is then made based on the magnitude and location in the network. The study concludes by highlighting the benefits to be derived from this work and reviews the challenges faced while conducting the study. It also recommends ways in which improvements to the system can be realized.
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Zabihinejad, Amin. "Optimal sizing of modular multilevel converters." Doctoral thesis, Université Laval, 2017. http://hdl.handle.net/20.500.11794/27918.

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L’électronique de puissance a pénétré depuis quelques décennies les applications à forte puissance dans de nombreux domaines de l’industrie électrique. Au-delà de l’apparition des technologies d’interrupteur à forte puissance commutable en moyenne tension, ces applications imposaient également des avancées dans le domaine des topologies de convertisseurs statiques : les principaux défis à affronter concernaient l’atteinte de niveaux de tension compatibles avec le domaine de puissance des applications, l’augmentation de la fréquence de commutation apparente en sortie afin d’augmenter la bande passante de la commande, de réduire la taille des éléments de filtrage et de limiter les harmoniques de courant injectés dans le réseau d’alimentation. Les topologies de convertisseurs modulaires multiniveaux (MMC) sont issues de cette problématique de recherche : elles permettent grâce à l’association de cellules de commutation d’atteindre des niveaux de tension exploitables en grande puissance avec les technologies d’interrupteurs existantes, de limiter les fréquences et les pertes de commutation des interrupteurs élémentaires tout en maîtrisant la distorsion harmonique totale (THD). La modularité, la redondance, les degrés de liberté et les fonctionnalités des MMC leur permettent aussi d’augmenter la tolérance aux défauts. Ils pénètrent à présent une large gamme d'applications comme le transport à courant continu en haute tension (HVDC), les systèmes d'énergie renouvelable, les entraînements à vitesse variables de grande puissance, la traction ferroviaire et maritime ainsi que des applications spécifiques très contraignantes en matière de performance dynamique comme les systèmes d’alimentation des électro-aimants dans les accélérateurs de particules. Les topologies MMC sont composées de cellules de commutation élémentaires utilisant des interrupteurs électroniques tels que le Thyristor à Commande Intégrée (IGCT) standard ou les dernières génération d’IGBT. Les convertisseurs MMC ont fait l’objet de nombreux travaux de recherche et de développement en ce qui concerne les topologies, la modélisation et le calcul du fonctionnement en régime permanent et transitoire, le calcul des pertes, le contenu harmonique des grandeurs électriques et les systèmes de commande et de régulation. Par contre le dimensionnement de ces structures est rarement abordé dans les travaux publiés. Comme la grande majorité des topologies de convertisseurs statiques, les convertisseurs MMC sont composés non seulement d’interrupteurs mais aussi d’organes de stockage d’énergie de type composants diélectriques (condensateurs) et magnétiques (inductances, coupleurs) qui sont essentiels pour assurer la conversion des grandeurs électriques en entrée et en sortie. Ces composants ont une forte influence sur la taille, le volume et le rendement des convertisseurs et le dimensionnement optimal de ces derniers résulte souvent de compromis entre la taille des composants passifs, la fréquence et la puissance commutable par les interrupteurs élémentaires. Le travail de recherche présenté dans ce mémoire concerne le développement d’une méthodologie de dimensionnement optimal et global des MMC intégrant les composants actifs et passifs, respectant les contraintes des spécifications de l’application et maximisant certains objectifs de performance. Cette méthodologie est utilisée pour analyser divers compromis entre le rendement global du convertisseur et sa masse, voire son volume. Ces divers scénarios peuvent être également traduits en termes de coût si l’utilisateur dispose du prix des composants disponibles. Diverses solutions concurrentes mettant en œuvre un nombre de cellules spécifique adaptées à des interrupteurs de caractéristiques différentes en termes de calibre de tension, de courant et de pertes associés peuvent ainsi être comparées sur la base de spécifications d’entrée-sortie identiques. La méthodologie est appliquée au dimensionnement d’un convertisseur MMC utilisé comme étage d’entrée (« Active Front-end » : AFE) d’une alimentation d’électro-aimant pulsée de grande puissance. Dans une première partie, une méthode de calcul rapide, précise et générique du régime permanent du convertisseur MMC est développée. Elle présente la particularité de prendre en compte la fréquence de commutation contrairement aux approches conventionnelles utilisant la modélisation en valeurs moyennes. Cet outil se révèle très utile dans l’évaluation du contenu harmonique qui est contraint par les spécifications, il constitue le cœur de l’environnement de conception du convertisseur. Contrairement aux convertisseurs conventionnels, il existe des courants de circulation dans les convertisseurs MMC qui les rendent complexe à analyser. Les inductances de limitation incorporées dans les bras de la topologie sont généralement volumineux et pénalisants en termes de volume et de masse. Il est courant d’utiliser des inductances couplées afin de réduire l'ondulation , la THD et la masse. Dans le travail présenté, un circuit équivalent des inductances couplée tenant compte de l'effet de saturation est développé et intégré à l’environnement. L’utilisation d’inductances couplée augmente la complexité de l'analyse du fonctionnement et la précision de leur méthode de dimensionnement est critique pour l’optimisation globale du convertisseur. Un modèle analytique de dimensionnement de ces composants a été développé et intégré dans l’environnement ainsi qu’un modèle de complexité supérieure qui utilise le calcul des champs par éléments finis. La méthodologie de conception optimale et globale proposée utilise une procédure d’optimisation non linéaire avec contraintes qui pilote l’outil de calcul de régime permanent, le modèles de dimensionnements à plusieurs niveaux de complexité des composants passifs ainsi que d’autres modules permettant de quantifier les régimes de défaut. Pour pallier à la précision réduite des modèles analytiques, une approche d'optimisation hybride est également implantée dans l’environnement. Dans la boucle d'optimisation hybride, le modèle de dimensionnement des inductances peut être corrigé par le modèle de complexité supérieure qui utilise le calcul des champs. On obtient ainsi un meilleure compromis entre la précision de la solution optimale et le temps de convergence de la méthode itérative d’optimisation globale.<br>In the last decades, power electronics has penetrated high power applications in many areas of the electrical industry. After the emergence of high-voltage semiconductor switch technologies these applications also required advances in the field of static converter topologies: The main challenges were to achieve voltage levels compatible with the application power domain, to increase the apparent switching frequency at the output, to increase the control bandwidth, to reduce the size of the elements of filtering and of limiting the current harmonics injected into the supply network. The topologies of multi-level modular converters (MMC) are based on this research problem: they enable the use of switching cells to achieve high power levels that can be used with existing switch technologies, frequencies and switching losses of the elementary switches while controlling the total harmonic distortion (THD). Modularity, redundancy, degrees of freedom and MMC functionality also allow them to increase fault tolerance. They now penetrated a wide range of applications, such as high-voltage DC (HVDC), renewable energy systems, high-speed variable speed drives, rail and marine traction, and very specific applications in terms of dynamic performance such as electromagnet power systems in particle accelerators. MMC topologies are composed of elementary switching cells using electronic switches such as the standard Integrated Control Thyristor (IGCT) or the latest generation of IGBTs. MMC converters have been the subject of extensive research and development work on topologies, modeling, and calculation of steady-state and transient operation, loss calculation, the harmonic content of electrical quantities and systems control and regulation functions. On the other hand, the dimensioning methodology of these structures is rarely addressed in the published works. Like most static converter topologies, MMC converters are composed not only of switches but also passive components of energy storage devices (capacitors) and magnetic (inductors, couplers) that are essential to ensure the conversion of the input and output electrical quantities. These components have a strong influence on the size, the volume and the efficiency of the converters and the optimal dimensioning of the latter often result from a compromise between the size of the passive components, the frequency and the power switchable by the elementary switches. The research presented in this thesis concerns the development of an optimal and comprehensive design methodology for MMCs integrating active and passive components, respecting the constraints of the application specifications and maximizing certain performance objectives. This methodology is used to analyze the various trade-off between the overall efficiency of the converter and its mass, or even its volume. These various scenarios can also be translated into cost if the user has the price of the available components. Various competing solutions using a specific number of cells adapted to switches with different characteristics in terms of voltage, current, and associated losses can thus be compared on the basis of identical input-output specifications. The methodology is applied to the dimensioning of an MMC converter used as an active front-end (AFE) input of a high-power pulsed solenoid power supply. In the first part, a fast, precise and generic method for calculating the steady-state model of MMC converter is developed. It has the particularity of taking into account the switching frequency as opposed to conventional approaches using modeling in mean values. This tool is very useful in evaluating the harmonic content that is constrained by the specifications, it is the heart of the design environment of the converter. Unlike conventional converters, there are circulation currents in MMC converter structure that make it complex to analyze. The inductors which are used in the arms of the topology are generally bulky and expensive in terms of volume and mass. It is common to use coupled inductors to reduce ripple, THD, and mass. In the presented work, an equivalent circuit of coupled inductances considering the saturation effect is developed and integrated. The use of coupled inductors increases the complexity of the analysis and the precision of its sizing method is critical for the overall optimization of the converter. An analytical model for the dimensioning of these components has been developed and integrated as well as a higher complexity model which uses the finite element method calculation. The proposed optimal and global design methodology uses a nonlinear optimization procedure with constraints that drive the steady-state computing tool, multi-level design models of passive component complexity, and other modules to quantify the fault state. To compensate the low precision of the analytical models, a hybrid optimization approach is also implemented. In the hybrid optimization loop, the inductance-sizing model can be corrected by the higher complexity model that uses finite element computation. A better compromise is thus obtained between the precision of the optimal results and convergence time of the iterative global optimization method.
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Zaker, Sassan. "Optimal transistor sizing in VLSI : algorithms & implementation /." [S.l.] : [s.n.], 1994. http://library.epfl.ch/theses/?nr=1223.

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Diyad, Elmi Mohamed, and Lavaraj Manoharan. "Optimal Grid Connected Inverter Sizing for Different Climatic Zones." Thesis, Högskolan Dalarna, Energiteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:du-30986.

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Grid connected inverter requires accurate and appropriate sizing which depends on the temperature, inverter operating efficiency, performance ratio, annual system yield and solar radiation characteristics. The aim of this study was to design and size for optimum sizing factor for grid connected inverter. The main component to be considered in any photovoltaic grid connected system is the inverter since the output depends on the inverter sizing ratio, therefore optimal sizing factor was designed by considering factors that affects inverter sizing such as temperature, irradiance and the location. Large and small systems of 50 kW and 5 kW respectively were considered to determine grid connected inverter sizing factors for different climates in Kenya, Sweden, and India using PVsyst simulation. Two different inverter brands of SMA and ABB with 20 kW and 25 kW rating for large system and 4.6 kW, 4 kW inverters for small system. PVsyst simulation result showed that different locations with different orientation angles, the optimum sizing varies hence affects the annual performance of the system. Photovoltaic system inverters are sized based on the rated power of the installed system and this can be achieved when the inverter size is either almost matching or not. In this case the study presents the optimal sizing factor for grid connected inverter for Mandera in Kenya, Norrköping in Sweden and Kerala in India. The determination was done through the use of designing, assessing and analyzing of the relationship between the sizing factor with performance ratio, operational efficiency and annual hourly energy yield. The unique weather profile in Kerala and in Mandera favors the adoption of solar energy technology in the location. Solar radiation for one year was used as a baseline input and the result reveals that Mandera receives yearly radiation of 2.1 MWh/m² while Kerala and Norrköping receives 2 MWh/m² and 1.1 MWh/m² respectively. Design simulation using PVsyst tool made it possible for the determination of the optimal sizing factor for the grid connected system. Considerations such as the losses and the variations within the specific location was done and a graph showing the relationship between the sizing factor in relation to the operational inverter efficiency as well as energy yield and performance ratio was later on compared to see the behavior of the sizing factor. The study concludes that operational efficiency, performance ratio and energy yield affects the array optimum sizing ratio. For the three locations, inverters (SMA and ABB) shows different variations because optimal sizing ratio depends on the location and irradiation. The results reveal that Mandera has an optimal grid connected inverter sizing of the range from 1.1 to 1.4 while in Kerala it has from 1.2 to 1.4 and Norrköping has the range from 1.1 to 1.3. Optimal sizing of grid connected inverters depends on the energy yield and the location therefore the inverter mismatch voltage and its rating values have to be considered while determining the optimal sizing factor. The 25 kW inverters in all the locations had better efficiency and sizing factor and this proves that sizing the photovoltaic inverter will give better performance and efficiency.
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Kahler, Jens. "Optimal sizing and operational scheduling of water distribution network components." Thesis, De Montfort University, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433258.

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Coppez, Gabrielle. "Optimal sizing of hybrid renewable energy systems for rural electrification." Master's thesis, University of Cape Town, 2011. http://hdl.handle.net/11427/10274.

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Includes bibliograhical references.<br>This project has the objective of creating a tool for feasibility assessment and recommendations of sizing of hybrid renewable energy systems in rural areas in South Africa. This involves the development of a tool which would analyse information input about the climate of the area and the load demand.
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Nassery, Fatehullah. "Optimal Sizing and Placing of Distributed Generation in Distribution Networks." Kansas State University, 2017. http://hdl.handle.net/2097/35325.

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Master of Science<br>Department of Electrical and Computer Engineering<br>Anil Pahwa<br>Due to the ongoing changes in the structure of the electricity markets, distribution networks have developed an appealing potential for housing distributed generation (DG). In order to make the most out of the present distribution network, this project report verifies the results and method developed in a paper (Optimal Allocation of Embedded Generation on Distribution Networks) by A. Kean and M. O’Malley, which discusses an efficient way of incorporating DG in the current power system. The methodology under consideration elaborates on how certain constraints should be adopted that will lead toward optimally sizing and placing DG in the network under examination. Along with that, the effect of voltage rise and short circuit current are observed which shows that a certain allocation to some buses will cause a sudden rise in voltage and short circuit levels throughout the network. Furthermore, the adopted methodology with its relative constraints is solved using linear programming. Linear programming provides a more accurate allocation than its heuristic counterparts when it comes to embedding DG in smaller networks. The adopted methodology is then applied to a section of the Irish rural distribution network and the results pinpoint that appropriate placement of the DG will pave the way toward higher levels of penetration. The results obtained showed the same pattern as those recorded in the aforementioned source paper, there were only minor differences that are the result of using different software’s than those that were used by the authors of the paper.
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Lamy, Julian V. "Optimal Locations for Siting Wind Energy Projects: Technical Challenges, Economics, and Public Preferences." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/703.

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Increasing the percentage of wind power in the United States electricity generation mix would facilitate the transition towards a more sustainable, low-pollution, and environmentally-conscious electricity grid. However, this effort is not without cost. Wind power generation is time-variable and typically not synchronized with electricity demand (i.e., load). In addition, the highest-output wind resources are often located in remote locations, necessitating transmission investment between generation sites and load. Furthermore, negative public perceptions of wind projects could prevent widespread wind development, especially for projects close to densely-populated communities. The work presented in my dissertation seeks to understand where it’s best to locate wind energy projects while considering these various factors. First, in Chapter 2, I examine whether energy storage technologies, such as grid-scale batteries, could help reduce the transmission upgrade costs incurred when siting wind projects in distant locations. For a case study of a hypothetical 200 MW wind project in North Dakota that delivers power to Illinois, I present an optimization model that estimates the optimal size of transmission and energy storage capacity that yields the lowest average cost of generation and transmission ($/MWh). I find that for this application of storage to be economical, energy storage costs would have to be $100/kWh or lower, which is well below current costs for available technologies. I conclude that there are likely better ways to use energy storage than for accessing distant wind projects. Following from this work, in Chapter 3, I present an optimization model to estimate the economics of accessing high quality wind resources in remote areas to comply with renewable energy policy targets. I include temporal aspects of wind power (variability costs and correlation to market prices) as well as total wind power produced from different farms. I assess the goal of providing 40 TWh of new wind generation in the Midwestern transmission system (MISO) while minimizing system costs. Results show that building wind farms in North/South Dakota (windiest states) compared to Illinois (less windy, but close to population centers) would only be economical if the incremental transmission costs to access them were below $360/kW of wind capacity (break-even value). Historically, the incremental transmission costs for wind development in North/South Dakota compared to in Illinois are about twice this value. However, the break-even incremental transmission cost for wind farms in Minnesota/Iowa (also windy states) is $250/kW, which is consistent with historical costs. I conclude that for the case in MISO, building wind projects in more distant locations (i.e., Minnesota/Iowa) is most economical. My two final chapters use semi-structured interviews (Chapter 4) and conjoint-based surveys (Chapter 5) to understand public perceptions and preferences for different wind project siting characteristics such as the distance between the project and a person’s home (i.e., “not-in-my-backyard” or NIMBY) and offshore vs. onshore locations. The semi-structured interviews, conducted with members of a community in Massachusetts, revealed that economic benefit to the community is the most important factor driving perceptions about projects, along with aesthetics, noise impacts, environmental benefits, hazard to wildlife, and safety concerns. In Chapter 5, I show the results from the conjoint survey. The study’s sample included participants from a coastal community in Massachusetts and a U.S.-wide sample from Amazon’s Mechanical Turk. Results show that participants in the U.S.-wide sample perceived a small reduction in utility, equivalent to $1 per month, for living within 1 mile of a project. Surprisingly, I find no evidence of this effect for participants in the coastal community. The most important characteristic to both samples was the economic benefits from the project – both to their community through increased tax revenue, and to individuals through reduced monthly energy bills. Further, participants in both samples preferred onshore to offshore projects, but that preference was much stronger in the coastal community. I also find that participants from the coastal community preferred expanding an existing wind projects rather than building an entirely new one, whereas those in the U.S.-wide sample were indifferent, and equally supportive of the two options. These differences are likely driven by the prior positive experience the coastal community has had with an existing onshore wind project as well as their strong cultural identity that favors ocean views. I conclude that preference for increased distance from a wind project (NIMBY) is likely small or non-existent and that offshore wind projects within 5 miles from shore could cause large welfare losses to coastal communities. Finally, in Chapter 6, I provide a discussion and policy recommendations from my work. Importantly, I recommend that future research should combine the various topics throughout my chapters (i.e., transmission requirements, hourly power production, variability impacts to the grid, and public preferences) into a comprehensive model that identifies optimal locations for wind projects across the United States.
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陳立梅 and Lap-mui Ann Chan. "Near optimal lot-sizing policies for multi-stage production/inventory systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1990. http://hub.hku.hk/bib/B31209129.

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Chan, Lap-mui Ann. "Near optimal lot-sizing policies for multi-stage production/inventory systems /." [Hong Kong : University of Hong Kong], 1990. http://sunzi.lib.hku.hk/hkuto/record.jsp?B12626533.

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Ali, Syed Muhammad Hassan. "Optimal sizing of low-carbon integrated power networks through shifting electricity demand." Thesis, The University of Sydney, 2019. https://hdl.handle.net/2123/22126.

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The objective of this thesis is to develop a GIS-based simulation tool for optimising the size of 100% renewable electricity grid by utilising flexible electricity demand and generation. Different technology options are presented for load-shifting; electric water-heaters and air-conditioners from the residential sector, and wastewater treatment and desalination plants from the industrial sector. The impact on renewable electricity grid due to the shifting of electricity demand from these loads is described, and several options are highlighted that might be feasible from a policy point of view. The load-shifting potential is estimated for each hour of the yearly simulation for entire Australia, based on the modelled electricity demand of the flexible loads on a 90×110 GIS raster grid. The electricity demands are shifted from periods of low renewable resources and high demands to periods of high renewable resources and low demands, enabling us to reduce the installed capacity requirements of a 100%‐renewable electricity grid in Australia. In case electric water-heaters and air-conditioners with load-shifting durations of 1-hour, the electricity demand in Australia can be met by 100% renewable electricity grid with an installed capacity of 145 GW and 130 GW, respectively. For load-shifting durations of 6-hour in wastewater treatment plant’s electricity demand and its electricity generation limited to five times the current capacity, a 100% renewable electricity grid need an installed capacity of around 149 GW to meet the demand. The installed capacity requirement in the case study of desalination plants with load-shifting periods of 10 days is 135 GW operating. This research indicates that a significant reduction in installed capacity and improvement in capacity factor are possible if flexible demand and generation are properly utilised in a 100% renewable electricity grid.
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Al-Sabounchi, Ammar M. Munir. "Optimal sizing and location of photovoltaic generators on three phase radial distribution feeder." Thesis, De Montfort University, 2011. http://hdl.handle.net/2086/5225.

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The aim of this work is to research the issue of optimal sizing and location of photovoltaic distributed generation (PVDG) units on radial distribution feeders, and develop new procedures by which the optimal location may be determined. The procedures consider the concept that the PVDG production varies independently from changes in feeder load demand. Based on that, the developed procedures deal with two performance curves; the feeder daily load curve driven by the consumer load demand, and the PVDG daily production curve driven by the solar irradiance. Due to the mismatch in the profile of these two curves the PVDG unit might end up producing only part of its capacity at the time the feeder meets its peak load demand. An actual example of that is the summer peak load demand in Abu Dhabi city that occurs at 5:30 pm, which is 5 hours after the time the PV array yields its peak. Consequently, solving the optimization problem for maximum line power loss reduction (∆PPL) is deemed inappropriate for the connection of PVDG units. Accordingly, the procedures have been designed to solve for maximum line energy loss reduction (∆EL). A suitable concept has been developed to rate the ∆EL at one time interval over the day, namely feasible optimization interval (FOI). The concept has been put into effect by rating the ∆EL in terms of line power loss reduction at the FOI (ΔPLFOI). This application is deemed very helpful in running the calculations with no need to repeat the energy-based calculations on hourly basis intervals or even shorter. The procedures developed as part of this work have been applied on actual feeders at the 11kV level of Abu Dhabi distribution network. Two main scenarios have been considered relating to the avoidance and allowance of reverse power flow (RPF). In this course, several applications employing both single and multiple PVDG units have been solved and validated. The optimization procedures are solved iteratively. Hence, effective sub-procedures to help determine the appropriate number of feasible iterative steps have been developed and incorporated successfully. Additionally, the optimization procedures have been designed to deal with a 3-phase feeder under an unbalanced load condition. The line impedances along the feeder are modeled in terms of a phase impedance matrix. At the same time, the modeling of feeder load curves along with the power flow calculations and the resulting losses in the lines are carried out by phase. The resulting benefits from each application have been evaluated and compared in terms of line power loss reduction at the FOI (∆PLFOI) along with voltage and current flow profile.
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Alsayed, Mohammed. "Optimal Sizing of Power Generation Systems Based on Multi Criteria Decision Making (MCDM)." Doctoral thesis, Università di Catania, 2013. http://hdl.handle.net/10761/1338.

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Power Generation Systems (PGSs) based on Hybrid Renewable Energy (HRE) are one of the promising solutions for future distributed generation systems. Among different configurations, Hybrid Photovoltaic - Wind turbine (PV-WT) grid connected PGSs are the most adopted for their good performance. However, due to the complexity of the system caused by wind power variability and solar radiation intermittency, the optimal balance between these two energy sources requires particular attention to achieve a good engineering solution. This thesis deals with the optimal sharing and sizing of PV-WT by adopting different Multi Criteria Decision Making (MCDM) optimization approaches. Different approaches have been developed using Multi attribute decision Making (MADM) and Multi Objective Decision Making (MODM). Moreover, sensitivity and uncertainty of MCDM algorithms have been analyzed, by considering different weighting criteria techniques with different fluctuation scenarios of wind speed and solar radiation profiles, and by considering stochastic analysis to solar radiation, wind speed, and load demand input data , thus highlighting advantages and drawbacks of the proposed optimal sizing approaches. The developed approaches could be assumed as a powerful roadmap for decision makers, analysts, and policy makers.
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Kintner-Meyer, Michael Carl Willi. "An investigation of optimal sizing and control of air-conditioning systems in commercial buildings /." Thesis, Connect to this title online; UW restricted, 1994. http://hdl.handle.net/1773/7073.

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16

Naziri, Moghaddam Iman. "Optimal Sizing and Operation of Energy Storage Systems to Mitigate Intermittency of Renewable Energy Resources." Thesis, The University of North Carolina at Charlotte, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10791200.

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<p> Increased share of Renewable Energy Sources (RES) in the generation mix requires higher flexibility in power system resources. The intermittent nature of the RES calls for higher reserves in power systems to smooth out the unpredictable power fluctuations. Grid-tied energy storage systems are practical solutions to facilitate the massive integration of RES. The deployment of Battery Energy Storage Systems (BESS) on the power grids is experiencing a significant growth in recent years. Thanks to intensive research and development in battery chemistry and power conversion systems, BESS costs are reducing. However, much more advancements in battery manufacturing as well as additional incentives from the market side are still needed to make BESS a more cost-effective solution. Planning and operation of the BESS significantly influence its profitability. It is quite important to find optimal sizes of batteries and inverters. Sizing of the BESS for two different applications is addressed in this work. In the first application, the BESS is co-located with Pumped Storage Hydro (PSH) to meet the Day-Ahead (DA) schedule of wind generation. In the second application, a method for BESS sizing in the presence of PV-induced ramp rate limits is proposed. In this thesis, two methods based on Receding Horizon Control (RHC) for the optimal operation of the BESS are introduced. A co-located BESS and wind farm is considered in both methods. In one method, electricity market participation is not considered, and the goal is solely meeting the DA schedule utilizing the BESS. A novel predictive control method is proposed in this part and the efficiency of the method is evaluated through long-run simulations using actual historical wind power. </p><p> In the second scenario, market participation of the BESS is taken into account. The deviation from the DA schedule can be compensated through the BESS, or by purchasing power from the real-time electricity market. The optimization problem based on physical and operational constraints is developed. The problem is solved through an RHC scheme while using updated wind power and electricity price forecasts. In this thesis, a Ridge-regression forecast model for electricity price and an ARIMA forecast model for wind power are developed. Simulation results using actual historical data for wind power and electricity price demonstrate that the proposed algorithm increases the average daily profit. In order to evaluate the impact of the BESS lifetime and price on average daily profit, different scenarios are defined and simulated. Although they increase the complexity of the problem, much more realistic result might be obtained when all details and constraints are considered. </p><p>
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17

Mehra, Varun S. M. Massachusetts Institute of Technology. "Optimal sizing of solar and battery assets in decentralized micro-grids with demand-side management." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/108959.

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Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2017.<br>Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 199-209).<br>Solar-based community micro-grids and individual home systems have been recognized as key enablers of electricity provision to the over one billion people living without energy access to-date. Despite significant cost reductions in solar panels, these options can still be cost-prohibitive mainly due over-sizing of generation assets corresponding with a lack of ability to actively manage electricity demand. The main contribution shared is the methodology and optimization approach of least-cost combinations of generation asset sizes, in solar panels and batteries, subject to meeting reliability constraints; these results are based on a techno-economic modeling approach constructed for assessing decentralized micro-grids with demand-side management capabilities. The software model constructed is implemented to represent the technical characteristics of a low-voltage, direct current network architecture and computational capabilities of a power management device. The main use-case of the model presented is based on serving representative, aggregated, household-level load profiles combined with simulated power output from solar photovoltaic modules and the kinetic operating constraints of lead-acid batteries at hourly timesteps over year-long simulations. The state-space for solutions is based on available solar module and battery capacities from distributors in Jharkhand, India. Additional work presented also extends to real-time operation of such isolated micro-grids with requisite local computation. First, for load disaggregation and forecasting purposes, clustering algorithms and statistical learning techniques are applied on quantitative results from inferred load profiles based on data logged from off-grid solar home systems. Second, results from an optimization approach to accurately parametrize a lead-acid battery model for potential usage in real-time field implementation are also shared. Economic results, sensitivity analyses around key technical and financial input assumptions, and comparisons in cost reductions due to the optimization of solar and battery assets for decentralized micro-grids with demand-side management capabilities are subsequently presented. The work concludes with insights and policy implications on establishing differentiated willingness-to-pay, tiers of service, and dynamic price-setting in advanced micro-grids.<br>by Varun Mehra.<br>S.M. in Technology and Policy<br>S.M.
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18

Zenginis, Ioannis. "Optimal sizing and operation planning of microgrids and operation analysis of charging stations for electric vehicles." Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/664711.

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Energy and transportation sectors are going through major changes as a result of technological advances, depletion of fossil fuels and climate change. With regard to the energy sector, the future smart grid is expected to be an interconnected network of small-scale and self-contained microgrids, in addition to a large-scale electric power backbone. By utilizing microsources, such as renewable energy sources, energy storage systems and vehicle-to-grid systems, microgrids target to satisfy the customers’ energy demands in a safe, reliable, economic and environmentally friendly way. With regard to the changes in the transportation sector, internal combustion engine vehicles are expected to be gradually replaced by electric vehicles, which are considered to be a promising solution for mitigating the impact of transportation sector on the environment. The presented thesis deals with two main topics; the first one refers to the optimal sizing and operation planning of microgrids comprising various urban building types, while the second one is related to the operation of fast charging stations for electric vehicles that are located in densely populated areas. The first objective of the thesis is to examine the effect of energy exchanges among interconnected buildings with diverse load profiles on the sizes of power equipment to be installed at the buildings. To this end, a mixed integer linear programming optimization framework is presented that determines the optimal capacities of photovoltaic panels, energy storage systems, and inverters, as well as the optimum management of the generated power. As a first step, the benefits of cooperation among buildings that are already interconnected through an existing point of common coupling is examined. The cooperation benefits are derived by comparing the buildings' costs when they participate in the microgrid with their costs when they operate as separate entities. As a second step, a different microgrid topology is proposed where energy exchanges take place through a common DC bus. In this way, neighboring buildings that are not already physically connected can be members of the same microgrid. Moreover, the optimization results for the new topology are obtained by using the Nash bargaining method, through which the benefits of cooperation are equally distributed among the participating members. Finally, the possible integration of new buildings in the existing microgrid at a later time point is also examined. The second objective of the thesis is to provide an accurate operation analysis of fast charging stations for electric vehicles. To this end, a novel queuing theory-based model is presented that classifies the various electric vehicles by their battery size. As a first step, it is analyzed a charging station that contains DC outlets, and the electric vehicles recharge their batteries up to the maximum possible level. The proposed model takes into account the arrival rates and state of charge of the electric vehicles' batteries when arriving at the station, in order to compute the maximum number of customers that can be served, subject to an upper bound for the waiting time in the queue. In addition, a charging strategy is proposed, which allows the charging station to serve more customers without any increase in the queue waiting time. As a second step, it is considered that the charging station can serve both DC and AC electric vehicle classes, while a more flexible way is adopted for denoting the customers' recharging patterns. Based on these additional novelties, the overall profit margin of the charging station operator, and the queue waiting times of the DC and AC classes are calculated under two different pricing policies.
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19

Sergent, Aaronn. "Optimal Sizing and Control of Battery Energy Storage Systems for Hybrid-Electric, Distributed-Propulsion Regional Aircraft." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1595519141013663.

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20

Nguyen, Duc Trung. "Optimal sizing and system management of water pumping and desalination process supplied with intermittent renewable sources." Thesis, Toulouse, INPT, 2013. http://www.theses.fr/2013INPT0030.

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Cette étude s’intéresse à la conception systémique intégrant simultanément les questions de dimensionnement et de gestion optimale de l'énergie. Le système étudié concerne un procédé de pompage intégrant un processus de dessalement d’eaux saumâtres alimenté par des sources de puissance hybrides renouvelable incluant un minimum de stockage électrochimique. Ce cas d’étude appartient à une classe typique de systèmes autonomes alimentés par des sources intermittentes dont profil de puissance a une forme "donnée" : « selon les conditions climatiques (ensoleillement, vent), avec un minimum de stockage d’électricité, la puissance offerte doit être convertie ou stockée hydrauliquement sous peine d’être gaspillée ». L'influence des conditions d'environnement et la robustesse du processus d’optimisation est enfin aussi discutée dans cette thèse. Deux types de modèles mathématiques, dynamiques et quasi-statiques, sont mis en œuvre pour décrire l'ensemble du dispositif. Le système est tout d’abord modélisé dynamiquement par Bond Graphs. Pour une simulation plus rapide, plus adaptée à l’optimisation globale du système, un modèle quasi-statique est créé pour être simulé dans l'environnement Matlab. Pour de tels dispositifs, étant donné une certaine puissance offerte au fil du vent et du soleil, trouver le point optimal de fonctionnement à chaque période consiste en un partage de puissance entre les sous systèmes de pompage et de traitement de l’eau : ce processus est plutôt complexe compte tenu des non linéarités (courbes rendement – puissance) et de la présence de nombreuses contraintes relatives aux limitations de puissance des pompes, aux conditions de niveau des réservoirs, ainsi qu’aux limitations de pression et de débit dans les processus hydrauliques (pompes osmoseur). Nous montrerons qu’il n’est pas si trivial de choisir une fonction objectif qui assure simultanément la performance et la robuste du système vis-à-vis des conditions d’environnement : une fonction objectif robuste quel que soit le profil de puissance des sources est ainsi proposée pour mettre en œuvre une gestion optimale de l’énergie. Le problème d’optimisation étant posé sous forme standard, consistant en la maximisation d’une fonction objectif sous contraintes, des approches d’optimisation efficaces par programmation non linéaire sont employées. La question du dimensionnement et son couplage à la gestion énergétique est finalement étudiée. En particulier, l’intérêt de la modularité des systèmes, considérant plusieurs pompes connectées en parallèle pour la même fonction, est investigué<br>This study focuses on systemic design, integrating simultaneously issues of sizing and optimal energy management. The system under study consists of a pumping process including a brackish water desalination system fed by hybrid renewable power sources with minimum electrochemical storage. Such a device belongs to the class of “autonomous systems” supplied by intermittent sources whose power profile has a “given” waveform: “with minimum electrical storage, power has to be converted, stored in water tanks, or wasted following climatic (sun, wind) conditions”. Influence of environment conditions and robustness of the optimization process is then also discussed in this thesis. Both dynamic and quasi static models are implemented for representing the whole system. The device is firstly modeled dynamically by Bond Graph methodology. For faster simulations, which are more suitable for system optimization, a quasi static model is created to be simulated in the Matlab environment. For such systems, given a certain source power, finding optimal operation point at each period consists of a power sharing between all pumping devices: it is a complex process with huge nonlinearities (efficiency vs power curves) and with many constraints as for the limitation of pump powers, tank level conditions, or pressure and flow limitations in hydraulic network and pumping devices. It is not so trivial to define an objective function which ensures system performance and robustness versus environment conditions: a convenient objective function, whatever the input power profile, is then proposed to implement the optimal management. The optimization problem being mathematically expressed, consisting of objective function maximization under constraints, efficient optimization methods by non linear programming are implemented. The issue of sizing and its coupling with system management efficiency is finally studied. In particular, the interest of modular operation with several pumps connected in parallel is also concerned in this research
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21

Nguyen, Duc Trung. "Optimal sizing and system management of water pumping and desalination process supplied with intermittent renewable sources." Electronic Thesis or Diss., Toulouse, INPT, 2013. http://www.theses.fr/2013INPT0030.

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Cette étude s’intéresse à la conception systémique intégrant simultanément les questions de dimensionnement et de gestion optimale de l'énergie. Le système étudié concerne un procédé de pompage intégrant un processus de dessalement d’eaux saumâtres alimenté par des sources de puissance hybrides renouvelable incluant un minimum de stockage électrochimique. Ce cas d’étude appartient à une classe typique de systèmes autonomes alimentés par des sources intermittentes dont profil de puissance a une forme "donnée" : « selon les conditions climatiques (ensoleillement, vent), avec un minimum de stockage d’électricité, la puissance offerte doit être convertie ou stockée hydrauliquement sous peine d’être gaspillée ». L'influence des conditions d'environnement et la robustesse du processus d’optimisation est enfin aussi discutée dans cette thèse. Deux types de modèles mathématiques, dynamiques et quasi-statiques, sont mis en œuvre pour décrire l'ensemble du dispositif. Le système est tout d’abord modélisé dynamiquement par Bond Graphs. Pour une simulation plus rapide, plus adaptée à l’optimisation globale du système, un modèle quasi-statique est créé pour être simulé dans l'environnement Matlab. Pour de tels dispositifs, étant donné une certaine puissance offerte au fil du vent et du soleil, trouver le point optimal de fonctionnement à chaque période consiste en un partage de puissance entre les sous systèmes de pompage et de traitement de l’eau : ce processus est plutôt complexe compte tenu des non linéarités (courbes rendement – puissance) et de la présence de nombreuses contraintes relatives aux limitations de puissance des pompes, aux conditions de niveau des réservoirs, ainsi qu’aux limitations de pression et de débit dans les processus hydrauliques (pompes osmoseur). Nous montrerons qu’il n’est pas si trivial de choisir une fonction objectif qui assure simultanément la performance et la robuste du système vis-à-vis des conditions d’environnement : une fonction objectif robuste quel que soit le profil de puissance des sources est ainsi proposée pour mettre en œuvre une gestion optimale de l’énergie. Le problème d’optimisation étant posé sous forme standard, consistant en la maximisation d’une fonction objectif sous contraintes, des approches d’optimisation efficaces par programmation non linéaire sont employées. La question du dimensionnement et son couplage à la gestion énergétique est finalement étudiée. En particulier, l’intérêt de la modularité des systèmes, considérant plusieurs pompes connectées en parallèle pour la même fonction, est investigué<br>This study focuses on systemic design, integrating simultaneously issues of sizing and optimal energy management. The system under study consists of a pumping process including a brackish water desalination system fed by hybrid renewable power sources with minimum electrochemical storage. Such a device belongs to the class of “autonomous systems” supplied by intermittent sources whose power profile has a “given” waveform: “with minimum electrical storage, power has to be converted, stored in water tanks, or wasted following climatic (sun, wind) conditions”. Influence of environment conditions and robustness of the optimization process is then also discussed in this thesis. Both dynamic and quasi static models are implemented for representing the whole system. The device is firstly modeled dynamically by Bond Graph methodology. For faster simulations, which are more suitable for system optimization, a quasi static model is created to be simulated in the Matlab environment. For such systems, given a certain source power, finding optimal operation point at each period consists of a power sharing between all pumping devices: it is a complex process with huge nonlinearities (efficiency vs power curves) and with many constraints as for the limitation of pump powers, tank level conditions, or pressure and flow limitations in hydraulic network and pumping devices. It is not so trivial to define an objective function which ensures system performance and robustness versus environment conditions: a convenient objective function, whatever the input power profile, is then proposed to implement the optimal management. The optimization problem being mathematically expressed, consisting of objective function maximization under constraints, efficient optimization methods by non linear programming are implemented. The issue of sizing and its coupling with system management efficiency is finally studied. In particular, the interest of modular operation with several pumps connected in parallel is also concerned in this research
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22

Mustafa, Mehran. "OPTIMAL SIZING OF GRID CONNECTED MICROGRID IN RURAL AREA OF PAKISTAN WITH WIND TURBINES AND ENERGY STORAGE SYSTEM USING PARTICLE SWARM OPTIMIZATION." OpenSIUC, 2017. https://opensiuc.lib.siu.edu/theses/2132.

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Pakistan has been riddled with energy shortage crisis. Long hours of load shedding have caused major economic setbacks in urban areas and rural areas do not even make the cut. Some rural parts, which are connected to the grid, suffer major load shedding and so economic growth is minimal. Most energy is directed towards industrial demand; hence the domestic demand suffers and causes long hours of load shedding. To aid this supply-demand gap, microgrids can be helpful in relieving some of the domestic load on the grid. A microgrid may be more economical only as a support for the main grid in an area, depending on its configuration. Since microgrids are generally composed of renewable energy sources like wind or solar or a combination of both, the supply from just these sources may result in high intermittency. To allow uniform supply, a backup energy source or energy storage is included with the renewable sources. Sizing a microgrid for the targeted region is critical. Some major sizing factors include the availability of renewable resource, load profile of the region, land availability, grid availability, etc. For this thesis, a region near Gharo, a town in Thatta District in Sindh, Pakistan, is selected to deploy the microgrid with a wind farm and battery energy storage system. The microgrid is connected to the main feeder, which supplies grid electricity to a small town of 30 small homes, a school and a small hospital. Hourly wind speed data and an annual load profile is used to calculate the most economic size of the microgrid, depending on the energy dispatch philosophy. To find the most economical solution, this thesis incorporates a stochastic technique, known as the Particle Swarm Optimization (PSO), which is a powerful intelligence evolution algorithm for solving optimization problems. Over the years, PSO has gained popularity due to its simple structure and high performance in solving linear or non-linear objective functions with any number of constraints. In this case, the objective function to be minimized is the net present cost of the microgrid, which comprises of annual capital cost, annual operation and maintenance cost, annual replacement cost of all equipment involved and the annual net cost of buying/selling electricity from/to the grid, respectively.
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23

Hjort, Mattias. "Bestämning av optimal fordonspark -Distribution av bitumen vid Nynäs AB." Thesis, Linköping University, Department of Mathematics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2903.

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<p>Nynas produces bitumen at two refineries in Sweden. The bitumen is shipped to seven depots along the swedish coast line, and from the depots special trucks handle the transportation to customers. Recently Nynas has transformed its supply chain and closed down a few depots. At the moment the company is considering a further reduction of the number of depots. In connection to these discussions an analyse of the companys distributionsystem and of possible changes is required. In this thesis an optimization model is developed that simulates Nynas distribution of bitumen from the depots to the customers. The model is used to investigate the required vehicle fleet size for a number of different scenarios, that is with different depots closed down. The question to be answered is, thus, what depots could be closed without any dramatic increase in the required vehicle fleet size? Scenarios where customers are allocated an increased storage capacity are also studied. </p><p>The distribution model that is developed is an inventory route planning problem. It is solved by column generation. Each column represents a route and is generated by a subproblem with restrictions on permitted working hours for the truck drivers. Integer solutions are generated heuristically. </p><p>Simulations that have been performed with the model reveals interesting differences concerning how the distribution is handled in different parts of Sweden. In western Sweden the transportation planning works well, but the distribution in the central parts of the country could be planned in a better way. Results from simulations also show that the depots in Norrköping and Västerås could be closed down without increasing the vehicle fleet. Probably, the existing vehicle fleet size will be sufficient even with the Kalmar-depot closed down. Nevertheless, Nynas transportation suppliers will have to purchase new vehicles if the Sandarne-depot is to be closed. </p><p>Another interesting conclusion that can be drawn from this thesis is that there is a potential for reducing the vehicle fleet size if the storage capacity is increased at a few chosen customers. A considerably small increase in the storage capacity at a few big customers that are located far from the depots will have a great effect.</p>
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24

Boutros, Fouad. "Nouvelles approches d'optimisation multi-objectifs pour les Microgrids DC Autonomes." Electronic Thesis or Diss., Nantes Université, 2025. http://www.theses.fr/2025NANU4002.

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Dans un monde confronté à l’urgence du changement climatique, les microgrids offrent une solution prometteuse pour concevoir des systèmes énergétiques durables. En particulier, les microgrids en courant continu (DC) isolés, fonctionnant indépendamment des réseaux électriques traditionnels, présentent des défis et des opportunités uniques. Le microgrid étudié dans ce travail est un microgrid DC isolé, composé de panneaux solaires, de batteries, d’un générateur diesel ainsi que de charges électriques résidentielles. Ce travail s’inscrit dans un effort global visant à réduire les émissions de gaz à effet de serre (GES) en optimisant la conception de ces microgrids tout en prenant en compte leur nature multi-objectif, notamment les aspects techniques, économiques et environnementaux. Face à la complexité de la transition énergétique mondiale, notre recherche se concentre sur trois dimensions majeures : l’optimisation des dimensions des composants du microgrid, la localisation stratégique des sources d’énergie et l’optimisation de la topologie des microgrids à réseau maillé. Ces objectifs sont atteints grâce à une approche novatrice combinant des techniques de modélisation avancées et des algorithmes d’optimisation<br>In a world facing the urgency of climate change, microgrids offer a promising solution for designing sustainable energy systems. In particular, isolated direct current (DC) microgrids, which operate independently of traditional power grids, present unique challenges and opportunities. The microgrid studied in this work is an isolated DC microgrid composed of solar panels, batteries, a diesel generator, and residential electrical loads. This work is part of a global effort to reduce greenhouse gas (GHG) emissions by optimizing the design of these microgrids while accounting for their multi-objective nature, including technical, economic, and environmental aspects. Amid the complexity of the global energy transition, our research focuses on three major dimensions: optimizing the sizing of microgrid components, strategically locating energy sources, and optimizing the topology of meshed microgrid networks. These objectives are achieved through an innovative approach combining advanced modelling techniques and optimization algorithms
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Louw, Rudolph Petrus. "Design optimisation and costing analysis of a renewable energy hydrogen system / Rudolph Petrus (Rudi) Louw." Thesis, North-West University, 2012. http://hdl.handle.net/10394/9518.

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The South African Department of Science and Technology is striving to develop a means of producing hydrogen gas in remote and civil areas through the use of renewable energy sources. For the purposes of creating such mobile hydrogen production facilities, a small-scale hydrogen production system based on renewable energy sources needs to be developed and modelled. This system is to serve as a pilot plant for further development of a large scale mobile hydrogen production facility. This work focuses on the characterisation of sizing algorithms for renewable energy sources which can determine component configurations that satisfy power requirements of the system. Additionally, optimal sizing techniques must be developed which can output an optimal plant configuration to a user based on cost and efficiency. To this end, a literature study was done on all the components that make up a renewable energy hydrogen system. The techniques researched were then applied to create algorithms capable of correctly sizing the required components of such a plant. These techniques were integrated into an application created in the LabVIEW environment, which is capable of outputting an optimal plant configuration based on the specific needs of a client. A case study was defined with which the results of the simulation models were verified. Using this work, a future, more comprehensive system may be developed and commercialised, building from the techniques implemented here.<br>Thesis (MIng (Computer and Electronic Engineering))--North-West University, Potchefstroom Campus, 2013
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BOVERI, ALESSANDRO. "Approaches to shipboard power generation systems design and management. Probabilistic approach to load prediction and system optimal design, sizing and management." Doctoral thesis, Università degli studi di Genova, 2018. http://hdl.handle.net/11567/929839.

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This doctoral thesis presents new ideas and formulations on shipboard power system sizing and management. The main motivation behind this work is to fill, at least in part, the current technological and mythological gap between land and marine applications, concerning the sizing and management of power systems. This gap is the result of several changes regarding both the electric and marine applications. Two of these are, for example, the recent increase of electric power installed on board modern vessels and recent development of technologies for land microgrids. In this context, it should be noted that, also the modern ships are comparable to land microgrids, where the generation and loads are close in space and the on board power system may work either islanded or connected to the land grid. Nowadays, microgrids are a hot topic in electric engineering, with a constant development of novel approaches for both their sizing and management. On the other hand, considering the increase in the power installed on board ships, the traditional methods developed in the last century to size and manage these systems have shown increasing limitations and inaccuracies. This results in oversized power generation systems, low performances and high level of air and sea pollution due to ships activities. To overcome these problems and criticalities, this work presents a probabilistic approach to load prediction, which may increase the flexibility of the power system design and allow a significant reduction in the total power installed. Moreover, the traditional method to size the diesel generators, based on satisfying the maximum load, it is revised with the formulation of an optimal problem, which can consider as input either the results of the traditional method to load prediction or those obtained applying the probabilistic one. Finally, due to the recent introduction in land microgrids of energy storage system, which may cover the power fluctuations due to renewable resources, allow a better management of energy and increase the quality of service, an optimum method is developed and described in order to select, size and manage these systems on board ships.
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Agha, Kassab Fadi. "Co-optimisation of the sizing and control of an urban microgrid." Electronic Thesis or Diss., Compiègne, 2024. http://www.theses.fr/2024COMP2822.

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La modernisation du réseau électrique (RE) par la mise en œuvre de micro-réseaux offre un potentiel significatif pour améliorer la résilience énergétique, la durabilité et l'efficacité. Cependant, cette transition implique de naviguer dans un ensemble complexe de défis techniques, économiques et environnementaux. Les micro-réseaux nécessitent une planification et une optimisation méticuleuses pour équilibrer la génération, le stockage et la consommation d'énergie tout en minimisant les coûts et les émissions de carbone. Atteindre cet équilibre nécessite des stratégies d'optimisation avancées capables de traiter les subtilités des composants du système et des dynamiques opérationnelles. L'objectif de cette recherche est d'améliorer les capacités de prise de décision des concepteurs de micro-réseaux en fournissant une approche globale pour la planification des micro-réseaux. L'étude offre une analyse approfondie du projet sur toute sa durée de vie, du point de vue technique, économique et environnemental. Implémenté en Python et résolu à l'aide de CPLEX, le processus d'optimisation vise à minimiser à la fois le « Levelized Cost of Energy » (LCOE) et le « Life Cycle Emission » (LCE). L'étude utilise des données économiques et environnementales réelles, en tenant compte de la croissance de la charge ainsi que des données réelles d'irradiation solaire, de température ambiante et de vitesse du vent. La charge pour le bâtiment universitaire est basée sur des données de l'Université de Technologie de Compiègne, France, avec la charge des véhicules électriques (VE) modélisée à l'aide d'une modélisation probabiliste. L'étude introduit une stratégie d'optimisation multi-objectifs conjointe utilisant le « Mixed Integer Linear Programming » (MILP) pour garantir des solutions globalement optimales, facilitant ainsi des choix de conception plus informés et efficaces. Ces choix impliquent l'évaluation de diverses solutions proposées pour équilibrer les coûts et les émissions de carbone tout en abordant les complexités et les contraintes techniques du problème de gestion de l'énergie. Un aspect novateur de ce travail est l'intégration de la gestion d'énergie (GE) et du dimensionnement des composants dans un problème d'optimisation unifié, visant un écart d'optimalité de 0 % avec un temps de calcul réduit par rapport à la littérature existante. La méthode proposée évalue les compromis inhérents entre diverses solutions, identifiant le front de Pareto et permettant un équilibre optimal entre les objectifs économiques et environnementaux. Les résultats indiquent une réduction significative du LCOE et du LCE dans le GCMG par rapport à l'IMG. L'étude révèle que la capacité du système de stockage d'énergie par batterie (BESS) augmente à mesure que le LCE diminue, et que le nombre de systèmes photovoltaïques est plus élevé lorsque le LCOE est plus bas pour les deux modes de fonctionnement. Cela se produit parce que le BESS a un LCE légèrement inférieur à celui du PV, et que le LCOE du PV est également inférieur à celui du BESS. De plus, à mesure que la limite du RE augmente, les fronts de Pareto deviennent plus bas et plus raides. En outre, le même algorithme MILP est appliqué pour optimiser les micro-réseaux d'un campus universitaire tertiaire dans diverses villes. L'étude intègre également des éoliennes (WT) et des charges de VE dans le micro-réseau. L'étude fournit une analyse comparative de trois scénarios (PV/BESS, WT/BESS et PV/WT/BESS) dans différentes villes, évalue les impacts des fluctuations saisonnières sur le LCOE et le LCE, et évalue comment les technologies des composants des micro-réseaux influencent les résultats du LCOE et du LCE. Les résultats indiquent que les scénarios incluant PV/WT/BESS produisent les valeurs de LCOE et de LCE les plus basses, tandis que le scénario WT/BESS aboutit aux valeurs de LCOE et de LCE les plus élevées<br>The modernization of the electricity grid (EG) through the implementation of microgrids offers significant potential for enhancing energy resilience, sustainability, and efficiency. However, this transition involves navigating a complex web of technical, economic, and environmental challenges. Microgrids require meticulous planning and optimization to balance energygeneration, storage, and consumption while minimizing costs and carbon emissions. Achievingthis balance calls for advanced optimization strategies, which are capable of addressing theintricacies of system components and operational dynamics. The objective of this research is to enhance the decision-making capabilities of microgrid designers by providing a comprehensive approach for microgrid planning. The study offers an in-depth analysis of the project’s lifetime from technical, economic, and environmental perspectives. Implemented in Python and solved using CPLEX, the optimization process aims to minimize both the levelized cost of energy (LCOE) and the levelized cost of emissions (LCE). The study utilizes real economic and environmental data considering load growth as well as actual solar irradiation, ambient temperature, and wind speed data. The load for the university building is based on data from the Université de Technologie de Compiègne, France with the electric vehicle (EV) load modeled using probabilistic modeling. The study introduces a joint multi-objective optimization strategy usingMixed-Integer Linear Programming (MILP) to ensure globally optimal solutions, thereby that facilitates obtaining more informed and effective design choices. These choices involve evaluating various proposed solutions to balance cost and carbon emissions while addressing the complexities and technical constraints of the energy management (EM) problem. A novel aspect of this work is the integration of EM and component sizing into a unified optimization problem, aiming for an optimality gap of 0% with reduced computation time compared to existing literature. The proposed method evaluates the inherent trade-offs among various solutions by identifying the Pareto front and allowing for an optimal balance between economic and environmental objectives. The results indicate a significant reduction in LCOE and LCE in the GCMG compared to the IMG. The study reveals that Battery Energy Storage System (BESS) capacity increases as the LCE decreases, and the number of Photovoltaic (PV) systems is higher when the LCOE is lower for both operation modes. This occurs because the BESS has a slightly lower LCE compared to PV, and the LCOE of PV is also lower than that of BESS. Furthermore, as the limit of the EG increases, the Pareto fronts become lower and steeper. Additionally, the same MILP algorithm is applied to optimize microgrids from a tertiary university campus across various cities. The study further integrates wind turbines (WT) and EV loads into the microgrid. The study provides a comparative analysis of three scenarios (PV/BESS, WT/BESS, and PV/WT/BESS) across different cities for evaluating the impacts of seasonal fluctuations on LCOE and LCE, and for assessing how microgrid component technologies influence LCOE and LCE outcomes. The results indicate that scenarios including PV/WT/BESS yield the lowest LCOE and LCE values, while the WT/BESS scenario results in the highest LCOE and LCE. It is also observed that the order of cities based on average solar irradiation or wind speed does not necessarily correspond to the order of LCOE and LCE. Monthly and daily fluctuations in solar irradiation and wind speed significantly impact these results. Regarding the technologies, locally produced PV panels contribute positively to the overall LCE of the microgrid, with PV panels incorporating phase changing material showing higher LCE. The research also compares two distinct algorithms
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28

Haddad, Maroua. "Sizing and management of hybrid renewable energy system for data center supply." Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCD036.

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Le secteur du numérique est récemment devenu un secteur majeur de la consommation d’électricité dans le monde, notamment avec l’avènement des data centers qui concentrent un très grand nombre de machines traitant des informations et fournissant des services. L’utilisation de sources d’énergie renouvelables sur site est un moyen prometteur de réduire l’impact écologique des data centers. Cependant, certaines énergies renouvelables comme les énergies solaire et éolienne sont intermittentes, étant liées aux conditions météorologiques. Étant donné qu’un centre de données doit maintenir une certaine qualité de service, l’utilisation efficace de ces sources nécessite l’utilisation de stockages. Cette thèse explore à la fois une méthode dimensionnement et une méthode de gestion optimale d’une infrastructure hybride d’énergie renouvelable, composée de panneaux photovoltaïques, d’éoliennes, de batteries et de système de stockage hydrogène.Une première contribution aborde le problème du dimensionnement de cette infrastructure électrique afin de répondre à la demande du data center. Un outil de dimensionnement est proposé, prenant en compte plusieurs métriques et fournissant trois configurations différentes. L’utilisateur choisit donc la configuration approprié, en fonction de son plan économique global de son écosystème H2. Une deuxième contribution étudie le problème de la gestion de l’énergie par programmation linéaire en nombres entiers. Un outil de gestion optimal est fourni pour trouver différents engagements optimaux des sources en fonction des objectifs de l’utilisateur. Les solutions obtenues sont ensuite discutées avec plusieurs métriques et avec différents horizons temporelles afin de trouver la meilleure solution pour répondre à la demande du data center. Enfin, une troisième contribution vise à prévoir évolution temporelle de l’ensoleillement et de la vitesse du vent à gros grain pour obtenir un dimensionnement plus précis à l’aide du modèle SARIMA<br>Information and communication technologies haverecently become a major sector in energy consumption,particularly with the advent of large platforms on the Internet. These platforms use data centers, which concentrate a very large number of machines processing information and providing services, causing a high energy consumption. The use of renewable energy sources (RES)on-site is then a promising way to reduce their ecological impact. However, some renewable energies such as solar and wind energy are intermittent and uncertain,being related to weather conditions. Since a data center must maintain a certain quality of service, using these sources effectively requires the usage of storage devices.This thesis explores an efficient sizing and management methods for a hybrid renewable energy infrastructure composed of wind turbines, photovoltaic panels, batteries and a hydrogen system..A first contribution addresses the problem of sizing the electrical plateform in order to meet the data center demand. A sizing tool is proposed, taking several metrics into account and providing three different system configurations as solutions. The user therefore chooses an appropriate configuration, according to his global economic plan of his H2 ecosystem. A second contribution studies the problem of energy management using amixed integer linear programming approach. An optimal management tool is therefore provided to find various source schedules according to different user’s objectives.The obtained solutions are discussed with several metrics considering different time horizon in order to find the beststorage management to meet the data center requests.Finally, a third contribution aims to forecast the weather data to obtain a preciser sizing of the sources using SARIMA model in order to reduce forecasts errors
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29

Kalir, Adar A. "Optimal and heuristic solutions for the single and multiple batch flow shop lot streaming problems with equal sublots." Diss., Virginia Tech, 1999. http://hdl.handle.net/10919/37485.

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This research is concerned with the development of efficient solutions to various problems that arise in the flow-shop environments which utilize lot-streaming. Lot streaming is a commonly used process of splitting production lots into sublots and, then, of scheduling the sublots in an overlapping fashion on the machines, so as to expedite the progress of orders in production and to improve the overall performance of the production system. The different lot-streaming problems that arise in various flow-shop environments have been divided into two categories, single-lot problems and multiple-lot problems. Further classification of the multiple-lot problems into the lot streaming sequencing problem (LSSP) and the flow-shop lot-streaming (FSLS) problem is made in this work. This classification is motivated by the occurrence of these problems in the industry. Several variants of these problems are addressed in this research. In agreement with numerous practical applications, we assume sublots of equal sizes. It turns out that this restriction paves the way to the relaxation of several typical limitations of current lot-streaming models, such as assumption of negligible transfer and setup times or consideration of only the makespan criterion. For the single-lot problem, a goal programming (GP) approach is utilized to solve the problem for a unified cost objective function comprising of the makespan, the mean flow time, the average work-in-process (WIP), and the setup and handling related costs. A very fast optimal solution algorithm is proposed for finding the optimal number of sublots (and, consequently, the sublot size) for this unified cost objective function in a general m-machine flow shop. For the more complicated multiple-lot problem, a near-optimal heuristic for the solution of the LSSP is developed. This proposed heuristic procedure, referred to as the Bottleneck Minimal Idleness (BMI) heuristic, identifies and employs certain properties of the problem that are irregular in traditional flow-shop problems, particularly the fact that the sublot sizes eminating from the same lot type and their processing times (on the same machines) are identical. The BMI heuristic attempts to maximize the time buffer prior to the bottleneck machine, thereby minimizing potential bottleneck idleness, while also looking-ahead to sequence the lots with large remaining process time earlier in the schedule. A detailed experimental study is performed to show that the BMI heuristic outperforms the Fast Insertion Heuristic (the best known heuristic for flow-shop scheduling), when modified for Lot Streaming (FIHLS) and applied to the problem on hand. For the FSLS problem, several algorithms are developed. For the two-machine FSLS problem with an identical sublot-size for all the lots, an optimal pseudo-polynomial solution algorithm is proposed. For all practical purposes (i.e., even for very large lot sizes), this algorithm is very fast. For the case in which the sublot-sizes are lot-based, optimal and heuristic procedures are developed. The heuristic procedure is developed to reduce the complexity of the optimal solution algorithm. It consists of a construction phase and an improvement phase. In the construction phase, it attempts to find a near-optimal sequence for the lots and then, in the improvement phase, given the sequence, it attempts to optimize the lot-based sublot-sizes of each of the lots. Extensions of the solution procedures are proposed for the general m-machine FSLS problem. A comprehensive simulation study of a flow shop system under lot streaming is conducted to support the validity of the results and to demonstrate the effectiveness of the heuristic procedures. This study clearly indicates that, even in dynamic practical situations, the BMI rule, which is based on the proposed BMI heuristic, outperforms existing WIP rules, commonly used in industry, in scheduling a flow-shop that utilizes lot streaming. With respect to the primary performance measure - cycle time (or MFT) - the BMI rule demonstrates a clear improvement over other WIP rules. It is further shown that it also outperforms other WIP rules with respect to the output variability measure, another important measure in flow-shop systems. The effects of several other factors, namely system randomness, system loading, and bottleneck-related (location and number), in a flow-shop under lot streaming, are also reported.<br>Ph. D.
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30

Bridier, Laurent. "Modélisation et optimisation d'un système de stockage couplé à une production électrique renouvelable intermittente." Thesis, La Réunion, 2016. http://www.theses.fr/2016LARE0038/document.

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L'objectif de cette thèse est la gestion et le dimensionnement optimaux d'un Système de Stockage d'Énergie (SSE) couplé à une production d'électricité issue d'Énergies Renouvelables Intermittentes (EnRI). Dans un premier temps, un modèle technico-économique du système SSE-EnRI est développé, associé à trois scénarios types d'injection de puissance au réseau électrique : lissage horaire basé sur la prévision J-1 (S1), puissance garantie (S2) et combiné (S3). Ce modèle est traduit sous la forme d'un programme d'optimisation non linéaire de grande taille. Dans un deuxième temps, les stratégies heuristiques élaborées conduisent à une gestion optimisée - selon les critères de fiabilité, de productivité, d'efficacité et de profitabilité du système - de la production d'énergie avec stockage, appelée “charge adaptative” (CA). Comparée à un modèle linéaire mixte en nombres entiers (MILP), cette gestion optimisée, applicable en conditions opérationnelles, conduit rapidement à des résultats proches de l'optimum. Enfin, la charge adaptative est utilisée dans le dimensionnement optimisé du SSE - pour chacune des trois sources : éolien, houle, solaire (PV). La capacité minimale permettant de respecter le scénario avec un taux de défaillance et des tarifs de revente de l'énergie viables ainsi que les énergies conformes, perdues, manquantes correspondantes sont déterminées. Une analyse de sensibilité est menée montrant l'importance des rendements, de la qualité de prévision ainsi que la forte influence de l'hybridation des sources sur le dimensionnement technico-économique du SSE<br>This thesis aims at presenting an optimal management and sizing of an Energy Storage System (ESS) paired up with Intermittent Renewable Energy Sources (IReN). Firstly, wedeveloped a technico-economic model of the system which is associated with three typical scenarios of utility grid power supply: hourly smoothing based on a one-day-ahead forecast (S1), guaranteed power supply (S2) and combined scenarios (S3). This model takes the form of a large-scale non-linear optimization program. Secondly, four heuristic strategies are assessed and lead to an optimized management of the power output with storage according to the reliability, productivity, efficiency and profitability criteria. This ESS optimized management is called “Adaptive Storage Operation” (ASO). When compared to a mixed integer linear program (MILP), this optimized operation that is practicable under operational conditions gives rapidly near-optimal results. Finally, we use the ASO in ESS optimal sizing for each renewable energy: wind, wave and solar (PV). We determine the minimal sizing that complies with each scenario, by inferring the failure rate, the viable feed-in tariff of the energy, and the corresponding compliant, lost or missing energies. We also perform sensitivity analysis which highlights the importance of the ESS efficiency and of the forecasting accuracy and the strong influence of the hybridization of renewables on ESS technico-economic sizing
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31

Ceschia, Adriano. "Méthodologie de conception optimale de chaines de conversion d’énergie embarquées." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPAST023.

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Les travaux proposés dans cette thèse s’inscrivent dans le cadre de l’électrification des systèmes embarqués au travers du développement de nouvelles chaines hybrides de conversion d’énergie ; celle-ci se fondant sur de nouvelles motorisations et combinaison de sources d’énergies complémentaires. Ces systèmes présentent de nombreux degrés de liberté, tant vis-à-vis des paramètres de ses constituants, que des réglages des lois de contrôle qui leurs sont associées. L’optimisation (technico-économique) pertinente de ces chaines de conversion complexes repose donc sur l’aptitude des méthodes de recherche d’intégrer simultanément les paramètres macroscopiques des composants ainsi que leurs contraintes technologiques, les conditions aléatoires imposées par l’environnement sur un cycle de fonctionnement et enfin les algorithmes de contrôle de bas niveau comme la gestion énergétique globale. Les performances de ces systèmes reposent sur la capacité des méthodologies de conception à considérer les contraintes multi-physiques liées à leur environnement réel, l’adéquation des technologies, des topologies et des lois de commandes permettant d’intégrer et d’associer efficacement leurs constituants. Dans ce contexte, ces travaux de thèse visent à développer des outils et des méthodes permettant l’optimisation des architectures de puissance et de leurs constituants, en intégrant dès la première phase de conception les notions de contrôle-commande et de gestion énergétique. Ils se déploieront sur l'étude d’une chaîne de conversion hybride électrifiée fondée sur une l’association pile à combustible / batterie.Pour ce faire, une approche globale de conception est proposée, utilisant une stratégie bi-niveau qui considère le problème de la gestion d’énergie directement à l'intérieur du problème de dimensionnement et intègre d’une manière progressive au même niveau plusieurs critères de performance: consommation d’énergie, fiabilité et encombrement. L’approche en question adopte alors deux boucles d'optimisation imbriquées: la boucle externe, basée sur les performances de la PSO (Particle Swarm Optimization), s’occupe du dimensionnement, tandis que la boucle interne agit sur la gestion d’énergie, utilisant la rapidité de la commande optimale. Cela offre un champ d’exploration plus vaste qu’une approche conventionnelle et permet d’atteindre les meilleures performances d’optimisation des sources d’énergie embarquées (minimiser la consommation, respecter les contraintes de fonctionnement de chaque constituant ainsi que les durées de vie cibles, satisfaire les exigences de la charge) avec une convergence rapide ainsi que de bonnes robustesse et précision. Outre ce couplage fort entre dimensionnement et gestion d’énergie, il s’agit de prendre en compte le caractère incertain de l’utilisation en proposant une optimisation robuste du dimensionnement final. Cela nécessite une stratégie de gestion énergétique en temps réel. Ainsi, une extension de l’approche de conception est proposée pour le fonctionnement temps réel utilisant une interaction entre reconnaissance du mode de conduite et contrainte énergétique basée sur l’apprentissage, permettant ainsi de garantir une meilleure intégration de l’approche développée<br>The research work proposed in this thesis falls within the context of embedded systems electrification with the development of a new hybrid power conversion chain, with new energy sources and powertrains. These systems offer many degrees of freedom regarding both the devices parameters and the tuning values of the associated control laws. The relevant (technico-economic) optimization of these complex power chains relies on the ability of the best-set algorithm to combine simultaneously the main parameters and the technological constraints of each component, the uncertain environmental conditions faced during areal use and finally the control algorithms as well as the global energy management. Their performances are based on the capacity of the design approaches to consider the real environment multiphysic constraints, the adequacy of the technologies, the topologies and the control laws, allowing to integrate and to associate effectively their constituents. In this context, this research work aims at developing tools and methods allowing the optimization of the power architectures and their components (hybrid energy conversion) by integrating in the design process the control-command and the energy management aspects. They consider a use case based on hybrid Fuel cell / Battery power system.For this purpose, a new nested methodology for complex system is been suggested. It enables to tackle large search spaces and considers different performance indexes (energy saving, reliability and volume). It simultaneously tunes and designs the energy management and component sizing by optimizing the main powertrain parameters while respecting the specifications. Technically, it uses two nested loops, combining the particle swarm optimization (PSO) technique’s performance and the rapid optimal control algorithm. This strategy addresses vast search spaces, achieves faster convergence to the global optimal integer design solution, and provides a good accuracy and robustness. In order to consider the randomness feature of real driving cycle (stochastic characteristic), a real time energy management strategy (EMS) was introduced based on an extension of the design approach, which increases its availability. By using machine-learning technique, an estimation of the current driving mode is developed and permits to guide the online energy management system
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32

Das, Choton Kanti. "Smart management strategies of utility-scale energy storage systems in power networks." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2019. https://ro.ecu.edu.au/theses/2209.

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Power systems are presently experiencing a period of rapid change driven by various interrelated issues, e.g., integration of renewables, demand management, power congestion, power quality requirements, and frequency regulation. Although the deployment of Energy Storage Systems (ESSs) has been shown to provide effective solutions to many of these issues, misplacement or non-optimal sizing of these systems can adversely affect network performance. This present research has revealed some novel working strategies for optimal allocation and sizing of utility-scale ESSs to address some important issues of power networks at both distribution and transmission levels. The optimization strategies employed for ESS placement and sizing successfully improved the following aspects of power systems: performance and power quality of the distribution networks investigated, the frequency response of the transmission networks studied, and facilitation of the integration of renewable generation (wind and solar). This present research provides effective solutions to some real power industry problems including minimizationof voltage deviation, power losses, peak demand, flickering, and frequency deviation as well as rate of change of frequency (ROCOF). Detailed simulation results suggest that ESS allocation using both uniform and non-uniform ESS sizing approaches is useful for improving distribution network performance as well as power quality. Regarding performance parameters, voltage profile improvement, real and reactive power losses, and line loading are considered, while voltage deviation and flickers are taken into account as power quality parameters. Further, the study shows that the PQ injection-based ESS placement strategy performs better than the P injection-based approach (in relation to performance improvement), providing more reactive power compensations. The simulation results also demonstrate that obtaining the power size of a battery ESS (MVA) is a sensible approach for frequency support. Hence, an appropriate sizing of grid-scale ESSs including tuning of parameters Kp and Tip (active part of the PQ controller) assist in improving the frequency response by providing necessary active power. Overall, the proposed ESS allocation and sizing approaches can underpin a transition plan from the current power grid to a future one.
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33

Barnawi, Abdulwasa. "Hybrid PV/Wind Power Systems Incorporating Battery Storage and Considering the Stochastic Nature of Renewable Resources." University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470357709.

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34

Haessig, Pierre. "Dimensionnement et gestion d’un stockage d’énergie pour l'atténuation des incertitudes de production éolienne." Thesis, Cachan, Ecole normale supérieure, 2014. http://www.theses.fr/2014DENS0030/document.

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Le contexte de nos travaux de thèse est l'intégration de l'énergie éolienne sur les réseaux insulaires. Ces travaux sont soutenus par EDF SEI, l'opérateur électrique des îles françaises. Nous étudions un système éolien-stockage où un système de stockage d'énergie doit aider un producteur éolien à tenir, vis-à-vis du réseau, un engagement de production pris un jour à l'avance. Dans ce contexte, nous proposons une démarche pour l'optimisation du dimensionnement et du contrôle du système de stockage (gestion d'énergie). Comme les erreurs de prévision J+1 de production éolienne sont fortement incertaines, la gestion d'énergie du stockage est un problème d'optimisation stochastique (contrôle optimal stochastique). Pour le résoudre, nous étudions tout d'abord la modélisation des composants du système (modélisation énergétique du stockage par batterie Li-ion ou Sodium-Soufre) ainsi que des entrées (modélisation temporelle stochastique des entrées incertaines). Nous discutons également de la modélisation du vieillissement du stockage, sous une forme adaptée à l'optimisation de la gestion. Ces modèles nous permettent d'optimiser la gestion de l'énergie par la méthode de la programmation dynamique stochastique (SDP). Nous discutons à la fois de l'algorithme et de ses résultats, en particulier de l'effet de la forme des pénalisations sur la loi de gestion. Nous présentons également l'application de la SDP sur des problèmes complémentaires de gestion d'énergie (lissage de la production d'un houlogénérateur, limitation des rampes de production éolienne). Cette étude de l'optimisation de la gestion permet d'aborder l'optimisation du dimensionnement (choix de la capacité énergétique). Des simulations temporelles stochastiques mettent en évidence le fort impact de la structure temporelle (autocorrélation) des erreurs de prévision sur le besoin en capacité de stockage pour atteindre un niveau de performance donné. La prise en compte de paramètres de coût permet ensuite l'optimisation du dimensionnement d'un point de vue économique, en considérant les coûts de l'investissement, des pertes ainsi que du vieillissement. Nous étudions également le dimensionnement du stockage lorsque la pénalisation des écarts à l'engagement comporte un seuil de tolérance. Nous terminons ce manuscrit en abordant la question structurelle de l'interaction entre l'optimisation du dimensionnement et celle du contrôle d'un système de stockage, car ces deux problèmes d'optimisation sont couplés<br>The context of this PhD thesis is the integration of wind power into the electricity grid of small islands. This work is supported by EDF SEI, the system operator for French islands. We study a wind-storage system where an energy storage is meant to help a wind farm operator fulfill a day-ahead production commitment to the grid. Within this context, we propose an approach for the optimization of the sizing and the control of the energy storage system (energy management). Because day-ahead wind power forecast errors are a major source of uncertainty, the energy management of the storage is a stochastic optimization problem (stochastic optimal control). To solve this problem, we first study the modeling of the components of the system. This include energy-based models of the storage system, with a focus on Lithium-ion and Sodium-Sulfur battery technologies. We then model the system inputs and in particular the stochastic time series like day-ahead forecast errors. We also discuss the modeling of storage aging, using a formulation which is adapted to the control optimization. Assembling all these models enables us to optimize the energy management of the storage system using the stochastic dynamic programming (SDP) method. We introduce the SDP algorithms and present our optimization results, with a special interest for the effect of the shape of the penalty function on the energy control law. We also present additional energy management applications with SDP (mitigation of wind power ramps and smoothing of ocean wave power). Having optimized the storage energy management, we address the optimization of the storage sizing (choice of the rated energy). Stochastic time series simulations show that the temporal structure (autocorrelation) of wind power forecast errors have a major impact on the need for storage capacity to reach a given performance level. Then we combine simulation results with cost parameters, including investment, losses and aging costs, to build a economic cost function for sizing. We also study storage sizing when the penalization of commitment deviations includes a tolerance threshold. We finish this manuscript with a structural study of the interaction between the optimizations of the sizing and the control of an energy storage system, because these two optimization problems are coupled
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Hassan, Aakash. "Improving the efficiency, power quality, and cost-effectiveness of solar PV systems using intelligent techniques." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2023. https://ro.ecu.edu.au/theses/2676.

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Growing energy demand, depleting fossil fuels, and increasing environmental concerns lead to adaptation to clean and sustainable energy sources. Renewable energy sources are now believed to play a critical role in diminishing the deteriorating environment, supplying power to remote areas with no access to the grid, and overcoming the energy crisis by reducing the stress on existing power networks. Therefore, an upsurge in renewablesbased energy systems development has been observed during the previous few decades. In particular, solar PV technology has demonstrated extraordinary growth due to readily available solar energy, technological advancement, and a decline in costs. However, its low power conversion efficiency, intermittency, high capital cost, and low power quality are the major challenges in further uptake. This research intends to enhance the overall performance of PV systems by providing novel solutions at all levels of a PV system hierarchy. The first level investigated is the solar energy to PV power conversion, where an efficient maximum power point tracking (MPPT) method is developed. Secondly, the dc to ac power conversion is explored, and an optimal PV system sizing approach with abidance to power quality constraints is developed. Finally, smart power management strategies are investigated to utilise the energy produced by solar PV efficiently, such that the minimum cost of energy can be achieved while considering various technical constraints. The methods involve Genetic Algorithm (GA) for finding the optimal parameters, mathematical models, MATLAB/Simulink simulations of solar PV system (including PV arrays, dc/dc converter with MPPT, batteries, dc/ac inverter, and electric load), and experimental testing of the developed MPPT method and power management strategies at the smart energy lab, Edith Cowan University. Highly dynamic weather and electricity consumption data encompassing multiple seasons are used to test the viability of the developed methods. The results exhibit that the developed hybrid MPPT technique outperforms the conventional techniques by offering a tracking efficiency of above 99%, a tracking speed of less than 1s and almost zero steady-state oscillations under rapidly varying environmental conditions. Additionally, the developed MPPT technique can also track the global maximum power point during partial shading conditions. The analyses of power quality at the inverter’s terminal voltage and current waveforms revealed that solar PV capacity, battery size, and LC filter parameters are critical for the reliable operation of a solar PV system and may result in poor power quality leading to system failure if not selected properly. On the other hand, the optimal system parameters found through the developed methodology can design a solar PV system with minimum cost and conformance to international power quality standards. The comparison between the grid-connected and stand-alone solar PV system reveals that for the studied case, the grid-connected system is more economical than the stand-alone system but outputs higher life cycle emissions. It was also found that for grid tied PV systems, minimum cost of energy can be achieved at an optimal renewable to grid ratio. Additionally, applying a time varying tariff yields a slightly lower energy cost than the anytime flat tariff. A sensitivity analysis of the reliability index, i.e., loss of power supply probability (LPSP), demonstrates that for the stand-alone PV systems, there is an inverse relationship between LPSP and cost of energy. Contrarily, for grid-connected systems, the cost of energy does not vary significantly with the change in LPSP.
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Le, guyadec Mathias. "Dimensionnement multi-physique des véhicules hybrides, de leurs composants et de la commande du système." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAT071/document.

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Le transport routier est au cœur des enjeux environnementaux actuels. Les véhicules électriques hybrides (VEH) sont une alternative intéressante, notamment en milieu urbain. Cependant, la conception de tels systèmes est complexe car la chaîne de traction (composants et architecture), la mission et la gestion énergétique du véhicule sont intimement liées.Les travaux de V. Reinbold ont permis de mettre au point une méthodologie de dimensionnement de VEH. Les composants sont optimisés conjointement avec la gestion énergétique sur un cycle de fonctionnement afin de minimiser la consommation de carburant du véhicule. Une attention particulière est portée à la conception fine de la machine électrique via un modèle électromagnétique adapté à l’optimisation.Dans la suite de ces travaux, nous approfondissons plusieurs aspects du dimensionnement des VEH. Tout d’abord, nous introduisons la possibilité de gérer des paramètres discrets de la machine, comme le nombre de paires de pôles. Dans un second temps, nous développons un modèle thermique de la machine prenant notamment en compte les échanges autour des têtes de bobine. Ce modèle analytique par réseau de résistances thermiques est intégré puis utilisé dans le processus de dimensionnement par optimisation. Il a été préalablement validé via un modèle par éléments finis. Des méthodes d’analyse d’incertitude et de sensibilité sont appliquées afin de quantifier l’influence de certains paramètres thermiques. Enfin, nous appliquons la méthodologie de dimensionnement par optimisation à une architecture série/parallèle, intégrant deux machines électriques<br>Road transportation has a huge impact on the environment. Hybrid electric vehicles (HEV) are an interesting alternative, especially for urban uses. However, HEV are complex systems to design because of the strong interaction between the component sizing, the energy management and the driving cycle.V. Reinbold previously developed a sizing methodology for HEV. The components and the energy management are simultaneously optimized to reduce the fuel consumption of the vehicle over a driving cycle. A specific electromagnetic model is used during the optimization process to describe accurately the electrical machine.As a continuation, we introduce firstly the possibility to deal with discrete variables such as the pole number of the electrical machine. Then, we develop a thermal model of the machine considering the convection exchanges around the end-windings. This analytical lumped parameter thermal network is used during the optimization process after being validated thanks to a finite element model. Uncertainty and sensitivity analysis are used to check the influence of some of the thermal parameters. Finally, the sizing methodology is applied to a series/parallel HEV including two electrical machines
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37

Cortez, Ernest. "Aportaciones al dimensionamiento y gestión de energía de un tren de potencia eléctrico híbrido para vehículos industriales con ciclos de conducción repetitivos y agresivos." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/668254.

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Currently, the interest for helping mitigate the emission of greenhouse gases caused by high fuel consumption in industrial vehicles has increased. In order to the reduction of fuel consumption in an industrial vehicle, it has been proposed to incorporate into the powertrain a system capable of storing and supplying electrical energy. Consequently, the design of a hybrid electric powertrain is required, based on the interconnection of the elements (topology), the sizing of the elements and/or the energy management strategy of the powertrain. This paper presents a methodology for the design of a hybrid electric vehicle for refuse collection, which presents a repetitive and aggressive drive cycle as a result of work activity. The proposed methodology consists in modeling the behavior of a hybrid electric powertrain, considering the electrical behavior of various energy accumulation elements (batteries and supercapacitors). An embedded system is used to perform the experimental characterization of a cell and a commercial supercapacitor, in order to approximate the behavior through an electric model. In accordance with a real drive cycle of a refuse collection vehicle, the energy demand for a hybrid electric refuse collection vehicle is determined. On the other hand, the fuel consumption is calculated from a hybrid electric powertrain that integrates an energy storage system or a hybrid energy storage system. A bio-inspired metaheuristic based on a stochastic population (particle swarm optimization and genetic algorithm) is developed, in order to determine an optimal solutions space. Subsequently, the optimal sizing of an energy storage system (batteries) and a hybrid energy storage system (batteries and supercapacitors) is performed, considering different mono-objective and multi-objective optimization problems. Based on the results of each optimization problem, a comparative analysis is carried out with an element of commercial accumulation. Considering a hybrid electric powertrain that integrates a hybrid energy storage system (batteries and supercapacitors), an energy management strategy based on fuzzy logic is developed. This includes the identification of the vehicle status from a real drive cycle. Finally, the validation of the energy management strategy is carried out through the model of a hybrid electric vehicle for refuse collection.<br>Actualmente, se ha incrementado el interés por mitigar la emisión de gases de efecto invernadero que se produce por un elevado consumo de combustible en vehículos industriales. Con la intención de contribuir en la reducción del consumo de combustible de un vehículo industrial, se ha propuesto incorporar al tren de potencia un sistema capaz de almacenar y suministrar energía eléctrica. En consecuencia, surge la necesidad de realizar el diseño de un tren de potencia eléctrico híbrido, a partir de la interconexión de los elementos (topología), el dimensionamiento de los elementos y/o la estrategia de gestión de energía del tren de potencia. En el presente trabajo se presenta una metodología para realizar el diseño de un vehículo eléctrico híbrido de recolección de basura, que presenta un ciclo de conducción repetitivo y agresivo como resultado de la actividad laboral. La metodología propuesta consiste en modelar el comportamiento de un tren de potencia eléctrico híbrido, considerando el comportamiento eléctrico de diversos elementos de acumulación de energía híbrido (baterías y supercapacitores). Se emplea un sistema embebido para realizar la caracterización experimental de una celda y un supercapacitor comercial, con el propósito de aproximar el comportamiento a través de un modelo eléctrico. En función de un ciclo de conducción real de un vehículo de recolección de basura se determina la demanda de energía para un vehículo eléctrico híbrido de recolección de basura. Por otra parte, se calcula el consumo de combustible a partir de un tren de potencia eléctrico híbrido que integra un sistema de almacenamiento de energía o un sistema de almacenamiento de energía híbrido. Se desarrolla una metaheurística bio-inspirada basada en una población estocástica) para determinar un espacio de soluciones óptimas. Posteriormente, se realiza el dimensionamiento óptimo de un sistema de almacenamiento de energía (baterías) y un sistema de almacenamiento de energía híbrido (baterías y supercapacitores), considerando diferentes problemas de optimización mono-objetivo y multi-objetivo. Con base en los resultados de cada problema de optimización, se procede a realizar un análisis comparativo con un elemento de acumulación comercial. Considerando un tren de potencia eléctrico híbrido que integra un sistema de almacenamiento de energía híbrido (baterías y supercapacitores), se desarrolla una estrategia de gestión de energía basada en lógica difusa, que incluye la identificación del estado del vehículo a partir de un ciclo de conducción real. Finalmente, se realiza la validación de la estrategia de gestión de energía a través del modelo de un vehículo eléctrico híbrido de recolección de basura.
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38

Marc, Nicolas. "Méthodologie de dimensionnement d’un véhicule hybride électrique sous contrainte de minimisation des émissions de CO2." Thesis, Orléans, 2013. http://www.theses.fr/2013ORLE2078/document.

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Ce travail de thèse propose une méthodologie systématique d’évaluation et de comparaison des gains en émissions de CO2 de véhicules hybrides électriques de différentes architectures et intégrant différentes fonctionnalités. Une méthodologie de dimensionnement a été mise en place, elle se base sur la définition d’un cahier des charges en performances dynamiques des véhicules, la mise en place d’algorithmes de mise à l’échelle afin de générer les données des composants de la chaîne de traction (batterie, machine électrique, moteur thermique), et l’utilisation de procédures de dimensionnement du véhicule sous contrainte de minimisation des émissions de CO2. L’évaluation énergétique des différentes configurations de véhicule ainsi dimensionnées s’articule autour de la définition de différents usages du véhicule et sur l’implémentation d’une loi de gestion optimale de l’énergie de type Principe du Minimum de Pontriaguine. Ces méthodologies ont été appliquées à une architecture conventionnelle, servant de référence pour les performances dynamiques et les consommations énergétiques, et d’une architecture hybride parallèle pré-transmission, pour laquelle une configuration hybride rechargeable et une configuration hybride non rechargeable ont été implémentées<br>This thesis work proposes a systematic methodology dedicated to the evaluation and comparison of CO2 emissions’ reduction for hybrid electric vehicles with different architectures and different levels of functionality. A sizing methodology has been developed, which is based on the definition of the requirements for the dynamic performances of vehicles, on the development of scaling algorithms in order to generate the dataset for the powertrain components (battery, electric motor, engine), and on the application of procedures for the sizing of a vehicle under CO2 emissions’ minimization constraint. The energy consumption evaluation of the different vehicle configurations, which were previously sized, is founded on the definition of a variety of vehicle’s type of use, as well as on the implementation of an optimal energy management strategy, the Pontryaguin’s Minimum Principle. These methodologies have been applied to a conventional vehicle architecture, which has been used as a reference for dynamic performances and energy consumption, and to a hybrid parallel pre-transmission architecture, which has been defined in two configurations, a plug-in hybrid and a non plug-in full-hybrid
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39

Attemene, N'guessan Stéphane. "Optimisation temps réel des flux énergétiques au sein d'un système multi-sources multi-charges basé sur les énergies d'origine renouvelable." Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCD044.

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Ce travail est axé sur le contrôle optimal en temps réel d’un système autonome constitué d’un générateur photovoltaïque, d’une pile à combustible de technologie PEM, d’un électrolyseur alcalin, d’une batterie et d’un pack de supercondensateurs pour une application stationnaire. Le couplage de ces différentes sources a pour but d’améliorer les performances, la disponibilité du réseau électrique résultant, la fourniture d’électricité sur des périodes beaucoup plus longues, et surtout la satisfaction de la charge en utilisant chaque source de façon raisonnée.D’abord, une étude approfondie sur la faisabilité du système du point de vue technique, énergétique, économique et environnemental est effectué. En conséquence une méthode de dimensionnement optimal est proposée. Une analyse de sensibilité permettant d’évaluer l’influence du coût et de la taille des sous-systèmes respectivement sur le coût énergétique global et l’équivalent CO2 émis par le système est également effectuée. Ensuite un modèle permettant une mise à l’échelle aisée des composants afin d’atteindre la capacité requise pour le système est développé. Le modèle global du système est obtenu en exploitant la modularité de la REM (représentation énergétique macroscopique), qui est le formalisme utilisé pour la modélisation. Finalement Une méthode de gestion énergétique basé sur l’« Energy consumption Minimization Strategy » (ECMS) est proposée. La stratégie proposée est validée par étude comparative des résultats avec ceux de la programmation dynamique<br>This work is focused on the real-time optimal control of a stand-alone system consisting of a photovoltaic generator, a PEM fuel cell, an alkaline electrolyzer, a battery and supercapacitor pack for a stationary application. The coupling of these different sources aims to improve performance, the availability of the resulting electrical grid, the supply of electricity over much longer periods, and especially the satisfaction of the load by using each source in a controlled way.First, a thorough study of the feasibility of the system from a technical, energetic, economic and environmental point of view is carried out. As a result, an optimal sizing method is proposed. A sensitivity analysis to evaluate the influence of subsystems cost and the size respectively on the overall energy cost and the equivalent CO2 emitted by the system is also discussed. Then, a model enabling easy scaling of components to achieve the capacity required for the system is developped. The global model of the system is obtained by exploiting the modularity of the formalism used for modeling (the Energetic Macroscopic Representation). Finally, an energy management method based on Energy consumption Minimization Strategy (ECMS) is proposed. A comparative study of the results obtained by the ECMS and those obtained by dynamic programming has enabled the validation of the optimal control strategy developed
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40

AGGARWAL, VARSHA. "OPTIMAL SITING AND SIZING OF DISTRIBUTED GENERATION RESOURCES IN RADIAL DISTRIBUTION SYSTEMS." Thesis, 2018. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16248.

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This thesis proposes an approach for the optimal sizing and placement of various types of Distributed Generation (DG) resources with the objective of minimizing the active power losses and improving the voltage profile improvement. Load flow studies have been carried out using BIBC and BCBV matrices. Teaching Learning Based Optimization (TLBO) and Artificial Bee Colony (ABC) algorithms have been implemented for optimal allocation of Type-1,Type-2 and Type-3 DG. To check the effectiveness, these two algorithms have been tested on the IEEE-33 bus, 69 bus and 119 bus radial distribution systems and compared with different existing techniques like Bacterial Foraging Optimization (BFO) and particle swarm optimization (PSO) algorithms. 24-hour load variation has been considered for some cases. The simulation results show that maximum reduction of losses take place when Type-3 DGs are used.
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41

Mokryani, Geev, and P. Siano. "Optimal siting and sizing of wind turbines based on genetic algorithm and optimal power flow." 2014. http://hdl.handle.net/10454/10747.

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42

Lai, Shih-Yu, and 賴世育. "Optimal Sitting and Sizing of Distributed Generation and Capacitor Using Memetic Algorithm." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/30627842384105411490.

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碩士<br>雲林科技大學<br>電機工程系碩士班<br>96<br>This thesis includes three problems. First, distribution companies consider the expansion of substation facilities is not simple, and the power demand keeps on raise. The distribution system planners are using distributed generation to expand the system capacity. They need to decide optimal sitting and sizing of distributed generation. Second, due to the reactive power demands exist in the power system, there are reactive power flows on the transmission lines. Therefore the system voltage drop and line loss problems will be appeared. The distribution system planners decide optimal sitting of capacitors that can advance bus voltage, reduce transmission line loss and improve the reliability. Finally, the above of two problems have to consider at the same time. The distribution system planners decide optimal sitting and sizing of distributed generation and capacitor. Using distributed generation to expand the system capacity and capacitor could compensate the reactive power. This thesis presents a method called memetic algorithm for the above three problems. Its feature is that combine with local search heuristics. By exchange the good information between every individual of a population then the solution can be achieved the global minima simply. It is shown in experiments that apply many kinds of local search methods to decide the best one then used to determine the optimal sitting and sizing of distributed generation and capacitor. Numerical results show that memetic algorithm is an effective and fast method than other heuristics.
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Sung, Yi-ming, and 宋翊銘. "Optimal Sitting and Sizing of Distributed Generation and Capacitor Using a Fuzzy Optimization Approach." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/91788233110839596046.

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碩士<br>雲林科技大學<br>電機工程系碩士班<br>98<br>This thesis includes three problems. First, because the electricity market price is very expensive and without considering expansion of substation facilities, the independent distribution company plans to invest distributed generations to expand the power supply capacity for increasing load demands. They need to decide optimal sitting and sizing of distributed generation. Second, due to the reactive load demands exist in the distribution system, there are reactive power flows on the feeders. Therefore the system voltage drop and line loss problems will be appeared. The distribution system planners decide optimal sitting of capacitors that can improve bus voltage, reduce transmission line loss and improve the reliability. Finally taking into account the above two problems. The distribution system planners decide optimal sitting and sizing of distributed generation and capacitor. Using distributed generation to expand the system capacity and capacitor could compensate the reactive power. In the planning problem, the real and reactive power loads must be known before solving the distribution system planning problem by implementing distributed generations and capacitors. Power loads can only be known through forecasting. Since power loads depend on the social behavior of customers. There are always errors in the forecast loads. In the proposed approach, the errors will be taken into account by using fuzzy sets to form fuzzy models and then using enhanced genetic algorithm to solve these problems.
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Mukerji, Meghana. "Optimal Siting and Sizing of Solar Photovoltaic Distributed Generation to Minimize Loss, Present Value of Future Asset Upgrades and Peak Demand Costs on a Real Distribution Feeder." Thesis, 2011. http://hdl.handle.net/10012/6213.

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The increasing penetration of distributed generation (DG) in power distribution systems presents technical and economic benefits as well as integration challenges to utility engineers. Governments are beginning to acknowledge DG as an economically viable alternative to deferring investment at generation, transmission and distribution levels, meeting demand growth and improving distribution network performance and security. DG technology is rapidly maturing in Ontario due to government economic incentives promoting connection, specifically, the Ontario’s Feed-In-Tariff (FIT) Program. Optimal sizing and siting of DG is well researched, traditionally studying the technical impact on distribution system such as real power loss reduction and voltage profile improvement. Equally common objectives studied are the economics of DG installation which are useful for the developer when deciding when and where to install. Although DG represents a “non-wires” solution to network asset reinforcement, the direct economic benefit to the host utility from promoting DG uptake is not fully understood by utility planners and asset managers. Some DG based asset reinforcement deferral work has been performed in the UK and Italy but is mainly at the transmission level and is not part of an overall strategy that could be applied by a utility. This research presents a comprehensive three stage technique: optimal siting, optimal sizing and financial evaluation of cost savings over a defined planning period to quantify the economic benefit to a Local Distribution Company (LDC) of solar photovoltaic (PV) DG connections on an actual distribution feeder. Optimal sites for PV DG are determined by applying the power loss sensitivity factor method to the test feeder. The objective functions used to determine cost savings consist of loss minimization, asset investment deferral, and peak demand reduction to identify an optimal DG penetration limit. Furthermore, a utility planner can identify an optimal DG penetration limit, encourage uptake at preferred locations that would benefit the LDC, and use the positive impact of DG at existing locations as part of an asset management strategy to prioritize and schedule future asset reinforcement upgrades.
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Lee, Yu-Cheng, and 李育政. "Optimal Constrained Wire Sizing." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/72587344413294668722.

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碩士<br>中華大學<br>資訊工程學系碩士班<br>93<br>As fabrication process improves, the interconnection delay problem becomes more and more important. In order to solve this delay problem and understand the timing phenomenon more clearly at the same time, it is necessary for the timing delay to recognize more deeply the wire sizing problem. For a normal wire sizing implementation, some improvement may further be done. For the consideration of better resource usage and power / performance progress, conventional wire sizing does not meet the proposed requirement. Recently, circuit realization also needs to add more restricted conditions to satisfy foundry process. Based on the result of non-uniform wire sizing and the wire size constraints, constrained non-uniform wire sizing must be further studied. This thesis discusses in detail how to adjust any non-uniform wire to get better result when wire size does not meet the wire constraints. The proposed methodology in this thesis has significance advance on constrained wire sizing. By applying an Elmore delay model to compute timing delay, an iterative approach is proposed to obtain a near-optimal constrained wire sizing for any wire. The experimental results show that our proposed approach obtains optimal non-uniform wire sizing. Because modern designs tend to design for manufacture (DFM), we suggest to use symmetric wire sizing and consider real physical design rules to reduce error rate when circuit layout implementation influences from environment effect and decreases other disadvantage factors.
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46

Binnington, Taylor. "Optimal Siting of Distributed Wind Farms in Ontario, Canada." Thesis, 2013. http://hdl.handle.net/1807/35110.

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Increasing wind penetration adds to the importance of enhancing the reliability of wind, to mitigate the magnitude and frequency of changes in electricity generation. This work addresses how improvements can be made to reliability through the geographic dispersal of wind farms in Ontario, Canada, using modeled North American Regional Reanalysis data. Optimal configurations of wind farm locations are determined according to two criteria. The first selects combinations of wind farms that follow temporal demand patterns, by maximizing the difference between the energy price and the cost of electricity. The second attempts to select combinations of wind farms that minimize the coefficient of variation in the aggregate output. It is found that there are no wind regimes in Ontario that match demand sufficiently for a viable development strategy, but that combinations of as few as three locations can reduce the coefficient of variation by over 30%, compared to a single region.
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47

Alizadeh, Seyed Morteza. "An analytical voltage stability model for wind power plant sizing and siting in distribution networks." Thesis, 2017. https://vuir.vu.edu.au/35053/.

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Electrical energy is the most widely used form of energy worldwide. The world is currently experiencing severe energy shortages as the fossil-fuel deposits are decreasing at an alarming rate. The increased awareness about environmental hazards, caused by the burning of fuels, is also forcing governments towards exploiting renewable-energy resources. Wind is one the important renewable resources, abundantly available, and offers the lowest cost per MWh as compared to most other renewable-energy resources. Harvesting energy from the wind as an alternative to fossil fuels has many advantages in terms of protecting the environment and promoting sustainability. However, voltage profile of distribution networks with interconnected Wind Power Plant (WPP) can be significantly affected ascribable to the limited capability of Wind Turbine Generators (WTGs) in regulating terminal voltage through reactive power control.
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48

Scalfati, Andrea. "Optimal sizing of distributed energy resources in microgrids." Tesi di dottorato, 2017. http://www.fedoa.unina.it/12106/1/Optimal_Sizing_of_Distributed_Energy_Resources_in_Microgrids__Andrea_Scalfati_PhD_Thesis.pdf.

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This work is focused on the optimal sizing of the Distributed Energy Resources included in a Microgrid. In recent years Microgrids are one of the most relevant research topics in electrical power systems. They are electricity distribution systems containing loads and distributed energy resources that can be operated in a controlled, coordinated way either while connected to the main power network or while islanded, and they are considered a key component of the smart grid scenario, aimed at obtaining better integration of distributed energy resources, increasing energy efficiency and reliability of the whole system, and providing the possibility to improve power quality and to achieve grid-independence to individual end-user sites. Despite the strong consensus existing among researchers and stakeholders on the variety and importance of the advantages deriving from the implementation of the Microgrid paradigm in modern electrical distribution systems, their widespread diffusion is hindered from cost considerations and from the difficulties in conducting a comprehensive cost-benefit analysis and in identifying qualified modalities for system design and management. Although the accurate evaluation of the economic results originating from the deployment of a µG is a demanding task, due to considerable uncertainties affecting the required input data, the complexity of system model and market dynamics, difficult representation of the economic value for some outcomes, the identification of efficient methodologies for the optimal system design is important to allow appropriate analyses and informed choices on the opportunity and feasibility of µG realizations. A fundamental aspect involved in the Microgrid design process, which constitutes the object of this work, is the choice and sizing of Distributed Energy Resources to be installed, including both Distributed Generators (DGs) and Electrical Energy Storage Systems (ESSs). The thesis includes four chapters: - Chapter 1 is an introduction to Microgrids, outlining their definition and main characteristics, the role they can play in present and future power systems, expected benefits and challenges related to their adoption and diffusion. - Chapter 2 introduces different approaches applicable to the problem of optimally sizing the distributed energy resources included in a microgrid; a categorization is made distinguishing analytical approaches, mathematical programming approaches and heuristic approaches, then various techniques used to deal with the uncertainty affecting design parameters are presented: sensitivity analyses, Stochastic Optimization, Sample Average Approximation, Robust Optimization and Decision Theory. - Chapter 3 presents a new analytical approach aimed at the optimal sizing of energy storage systems in DC microgrids, pursuing the objective to improve the efficiency of energy supply through the minimization of line losses; the DC µG under study is characterized by the presence of loads, fossil and renewables based generation units and storage devices; numerical applications show the effectiveness of the method and allow implementing sensitivity analyses to identify ratios between costs of energy and cost of storage devices which make their installation convenient. - Chapter 4 is focused on the application of mathematical programming approaches to the problem of optimally sizing, from an economic perspective, the Distributed Energy Resources included in a Microgrid; the proposed procedure is based on Mixed Integer Linear Programming and allows to determine the optimal sizes of Distributed Energy Resources, i.e. distributed generators and storage devices, which minimize the Microgrid Total Cost of Ownership, given location and load characteristics, also considering the opportunities of Load Management related to the presence of different quotes of controllable loads. Two variants of the sizing procedure are presented: the first uses a deterministic approach, not considering the uncertainties that affect design parameters, while the second uses a Robust Optimization approach to deal with them. In both cases, the performance of the sizing results against uncertainty is evaluated a-posteriori by means of Monte Carlo simulations. Numerical applications to a case study, referring to a DC µG with PV generation, storage and a certain amount of flexible load, are reported to show the effectiveness of the proposed methodology and allow different useful considerations. Three appendices accompany the above mentioned chapters: - Appendix A, linked to Chapter 3, presents an application of the superposition principle to derive a simple analytical expression of the power losses caused by the circulation of currents through the resistances of branch lines connecting the nodes of a DC network, depending on the nodal currents and the conductance matrix of the network; - Appendix B details the calculations and operations made to adapt the standard AC LV CIGRE distribution network to be used as a DC test grid in the numerical applications of Chapter 3; - Appendix C describes a well-established methodology of mathematical programming, useful to force different variables not to being simultaneously different from zero while preserving the linearity of the problem formulation, used in Chapter 4 to prevent solutions where energy is sold to the grid and bought from the grid at the same time (which is physically impossible on a single PCC).
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Tsai, Cheng-Hsiu, and 蔡政修. "Optimal Sizing Design of a Stand-AloneHybrid Energy System." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/zu9y49.

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碩士<br>健行科技大學<br>電機工程系碩士班<br>103<br>A Particle Swam Optimization – Hill Climbing algorithm is proposed in this paper to find the optimal size of a stand-alone hybrid energy system. The hybrid system is composed of solar powers, wind generators, batteries and diesel generators. According to the hourly isolations, temperatures and wind speeds measured by three weather stations of Central Weather Bureau, the power generation amounts are simulated. In the meantime, by using the standard industrial load, commercial load and residential load, the optimal sizing design is processed with the objective function of the lowest cost. Test results show that the performance of the method proposed by this paper is more accurate and faster than that of the traditional Genetic Algorithms.
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50

Chang, Chih-Yuan, and 張致源. "The Optimal Sizing Formulation For Continuous Glass Fiber Process." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/38457907664539710921.

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碩士<br>國立雲林科技大學<br>工業工程與管理研究所碩士班<br>94<br>E-Glass fibers are typically treated after forming with sizing formulation that are film former, lubricant, antistatic solution and emulsion etc… in order to reduce fuzzes of fiber glass。 The thesis relates to adjust the sizing formulation by Taguchi method to improve the quality (for example: to reduce fuzz, break filament) of fiber glass. At first, we adjust the ratio of main ingredients from sizing formulation, than mix this formulation and coat sizing on it. Also the suitable orthogonal array is used to Taguchi method. Secondly, we calculate the SN ratio by inspect the fuzz numbers of surface and rub times for each sizing formulation. By understanding how the sizing ingredients affect the quality of fiber glass, than we can find the optimal sizing formulation. Thirdly ,to ensure the best quality of sizing formulation ,we analysis of variance (ANOVA) to directed to sizing compositions for glass fibers and the results are quite stable and consistent. The method of trial and error always used to find the optimal sizing formulation in the past and therefore not only wasted cost but also time .The mode adopted in this research will provide one of the best methods for producing this fiber glass. Keywords: the fiber glass of E-type, sizing formulation, Taguchi method, ANOVA
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