Academic literature on the topic 'Hybrid Optimisation of Multiple Energy Resources'
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Journal articles on the topic "Hybrid Optimisation of Multiple Energy Resources"
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Jones, Tyson, and Simon C. Benjamin. "Robust quantum compilation and circuit optimisation via energy minimisation." Quantum 6 (January 24, 2022): 628. http://dx.doi.org/10.22331/q-2022-01-24-628.
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We explore a method for automatically recompiling a quantum circuit A into a target circuit B, with the goal that both circuits have the same action on a specific input i.e. B∣in⟩=A∣in⟩. This is of particular relevance to hybrid, NISQ-era algorithms for dynamical simulation or eigensolving. The user initially specifies B as a blank template: a layout of parameterised unitary gates configured to the identity. The compilation then proceeds using quantum hardware to perform an isomorphic energy-minimisation task, and an optional gate elimination phase to compress the circuit. If B is insufficient for perfect recompilation then the method will result in an approximate solution. We optimise using imaginary time evolution, and a recent extension of quantum natural gradient for noisy settings. We successfully recompile a 7-qubit circuit involving 186 gates of multiple types into an alternative form with a different topology, far fewer two-qubit gates, and a smaller family of gate types. Moreover we verify that the process is robust, finding that per-gate noise of up to 1% can still yield near-perfect recompilation. We test the scaling of our algorithm on up to 20 qubits, recompiling into circuits with up to 400 parameterized gates, and incorporate a custom adaptive timestep technique. We note that a classical simulation of the process can be useful to optimise circuits for today's prototypes, and more generally the method may enable `blind' compilation i.e. harnessing a device whose response to control parameters is deterministic but unknown.The code and resources used to generate our results are openly available online \cite{githubLink} \cite{mmaGithubLink}. A simple Mathematica demonstration of our algorithm can be found at questlink.qtechtheory.org.
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Newbold, Charles, Mohammad Akrami, and Mahdieh Dibaj. "Scenarios, Financial Viability and Pathways of Localized Hybrid Energy Generation Systems around the United Kingdom." Energies 14, no. 18 (September 7, 2021): 5602. http://dx.doi.org/10.3390/en14185602.
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Decarbonisation is becoming a central aim of countries around the globe, ensuring the effects of climate change do not increase exponentially in the coming years. Renewable energy generation is at the core of this decarbonisation process, enabling economies to divorce themselves from a reliance on oil and coal. Hybrid energy systems can utilise multiple generation methods to supply electrical demand best. This paper investigates the use of localised hybrid energy systems around the UK, comparing the financial viability of solar, wind and hydrokinetic generation methods both as a hybrid system and individually in different scenarios. The significance of having localised hybrid energy systems is that they address two large problems within renewable energy generation, that of storage issues and also generating the electricity far away from where it is actually used, requiring extensive infrastructure. The microgrid optimisation software HOMER was used to simulate each of the generation methods alongside the national grid, including lithium ion batteries and converters to create a comprehensive hybrid system. Net Present Cost, which is the current value of all the costs of installing and operating the system over the project lifetime, was considered as the metric. The analysis finds that for each modelled location, wind turbines in combination with lithium ion batteries and a converter is the system with the lowest Net Present Cost, with the exception of Bristol, which also uses hydrokinetic turbines within the system. The findings indicate the extensive wind resources available within the UK, along with identifying that certain locations around the country also have very high potential for tidal power generation.
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Jeyaprakash, P., C. Agees Kumar, and A. Ravi. "System cost minimisation in hybrid energy storage systems connected to microgrids: A comparative approach." Journal of Intelligent & Fuzzy Systems 42, no. 3 (February 2, 2022): 2793–808. http://dx.doi.org/10.3233/jifs-212262.
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Electricity is the most critical facility for humans. All traditional energy supplies are rapidly depleting. As a result, the energy resources are moved from traditional to non-conventional. In this research, mixture of two energy tools, namely wind and solar energy are used. Using a Hybrid Energy Storage System (HESS), continuous power can be provided. Electricity can be produced at a cost that is affordable. The integration of solar and wind in a hybrid system cause an increase in the system’s stability, which is the key benefit of this research. The system’s power transmission efficiency and reliability can be greatly enhanced by integrating these two intermittent sources. When one of the energy source is unavailable or inadequate to meet load demands, the other energy source will supply the power. The major contribution in this research is that, the proposed bidirectional single-inductor multiple-port (BSIMP) converter significantly lowers the component count, smaller circuit size and lower cost, allowing HESS to be integrated into DC microgrid. Minimum number of components are used for the same number of ESs in HESS in the proposed BSIMP converter. The hybridization of battery and supercapacitor (SC) for storage purpose is more cost effective, as compared to the battery energy storage system, thus improving the battery stress and hence used for large scale grid energy storage. SC’s are accepted as backup and found very useful in delivering high power, not possible with batteries. The use of SC in addition to batteries can be one solution for achieving the low life cycle economy. The Single Objective Adaptive Firefly Algorithm (SOAFA) is introduced for optimising the Proportional-Integral (PI) controller parameters. The system cost is reduced by about 32%, with the constraints on wind turbine swept area, PV area, total battery and SC capacity with the proposed optimisation algorithm.
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Roque, Paxis Marques João, Shyama Pada Chowdhury, and Zhongjie Huan. "Performance Enhancement of Proposed Namaacha Wind Farm by Minimising Losses Due to the Wake Effect: A Mozambican Case Study." Energies 14, no. 14 (July 16, 2021): 4291. http://dx.doi.org/10.3390/en14144291.
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District of Namaacha in Maputo Province of Mozambique presents a high wind potential, with an average wind speed of around 7.5 m/s and huge open fields that are favourable to the installation of wind farms. However, in order to make better use of the wind potential, it is necessary to evaluate the operating conditions of the turbines and guide the independent power producers (IPPs) on how to efficiently use wind power. The investigation of the wind farm operating conditions is justified by the fact that the implementation of wind power systems is quite expensive, and therefore, it is imperative to find alternatives to reduce power losses and improve energy production. Taking into account the power needs in Mozambique, this project applied hybrid optimisation of multiple energy resources (HOMER) to size the capacity of the wind farm and the number of turbines that guarantee an adequate supply of power. Moreover, considering the topographic conditions of the site and the operational parameters of the turbines, the system advisor model (SAM) was applied to evaluate the performance of the Vestas V82-1.65 horizontal axis turbines and the system’s power output as a result of the wake effect. For any wind farm, it is evident that wind turbines’ wake effects significantly reduce the performance of wind farms. The paper seeks to design and examine the proper layout for practical placements of wind generators. Firstly, a survey on the Namaacha’s electricity demand was carried out in order to obtain the district’s daily load profile required to size the wind farm’s capacity. Secondly, with the previous knowledge that the operation of wind farms is affected by wake losses, different wake effect models applied by SAM were examined and the Eddy–Viscosity model was selected to perform the analysis. Three distinct layouts result from SAM optimisation, and the best one is recommended for wind turbines installation for maximising wind to energy generation. Although it is understood that the wake effect occurs on any wind farm, it is observed that wake losses can be minimised through the proper design of the wind generators’ placement layout. Therefore, any wind farm project should, from its layout, examine the optimal wind farm arrangement, which will depend on the wind speed, wind direction, turbine hub height, and other topographical characteristics of the area. In that context, considering the topographic and climate features of Mozambique, the study brings novelty in the way wind farms should be placed in the district and wake losses minimised. The study is based on a real assumption that the project can be implemented in the district, and thus, considering the wind farm’s capacity, the district’s energy needs could be met. The optimal transversal and longitudinal distances between turbines recommended are 8Do and 10Do, respectively, arranged according to layout 1, with wake losses of about 1.7%, land utilisation of about 6.46 Km2, and power output estimated at 71.844 GWh per year.
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Dragomir, Florin, and Otilia Elena Dragomir. "Improvement of Energy Consume from Hybrid Systems Integrating Renewable Energy Sources." Advanced Materials Research 512-515 (May 2012): 1147–50. http://dx.doi.org/10.4028/www.scientific.net/amr.512-515.1147.
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This article proposes a solution for smart grid technologies using renewable energy and has as main result the optimisation of energy generation and consum in a power system with distributed power generation from renewable resources, by designing and implementation an system platform for monitoring and transmission the message (phone via SMS) by consumers. This application make available to consumers real-time information about energy, giving them the opportunity to make smart choices, allowing them to reduce their monthly bills and carbon emissions, reducing also the demand during peak periods and allows a more efficient use of renewable energy resources.
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Razali, Samirah, Kamaruddin Mamat, and Nor Shahniza Kamal Bashah. "Multiple error correction towards optimisation of energy in sensor network." Indonesian Journal of Electrical Engineering and Computer Science 13, no. 3 (March 1, 2019): 1208. http://dx.doi.org/10.11591/ijeecs.v13.i3.pp1208-1220.
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<span>Hybrid ARQ (HARQ) is among the optimum error controls implemented in Wireless Sensor Network as it reduces the overhead from retransmission and error correcting codes. The advancement in WSN includes the usage of high number of nodes and the increase in traffic with large data transmitted among the nodes had concerned the need for a new approach in error control algorithm. This paper proposed the multiple error correction based on HARQ process to aid the changes in channel with proper error correction assignment towards optimising the performances of WSN in terms of bit error rates, remaining energy, and latency for different types of congestion and channel conditions. In this study, we have developed the channel adaptation algorithm that can adapt to sudden changes and demonstrated the optimal error correcting codes as well as adjustment on the transmit power for the given channel condition and congestion presented. From the result analysed, the optimisation between the remaining energy and Bit Error rates happened on the basis of adapting to these different channel condition and congestion to minimize redundancies appended. From the result obtained, we concluded that by using multiple error correction algorithm with the aid of adjustment on the transmit power, the remaining energy can be optimised together with Bit Error rates and the excessive redundancies can be reduced</span>
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Bokharaie, Vahid S., Pieter Bauweraerts, and Johan Meyers. "Wind-farm layout optimisation using a hybrid Jensen–LES approach." Wind Energy Science 1, no. 2 (December 5, 2016): 311–25. http://dx.doi.org/10.5194/wes-1-311-2016.
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Abstract. Given a wind farm with known dimensions and number of wind turbines, we try to find the optimum positioning of wind turbines that maximises wind-farm energy production. In practice, given that optimisation has to be performed for many wind directions, and taking into account the yearly wind distribution, such an optimisation is computationally only feasible using fast engineering wake models such as the Jensen model. These models are known to have accuracy issues, in particular since their representation of wake interaction is very simple. In the present work, we propose an optimisation approach that is based on a hybrid combination of large-eddy simulation (LES) and the Jensen model; in this approach, optimisation is mainly performed using the Jensen model, and LES is used at a few points only during optimisation for online tuning of the wake-expansion coefficient in the Jensen model, as well as for validation of the results. An optimisation case study is considered, in which the placement of 30 turbines in a 4 km by 3 km rectangular domain is optimised in a neutral atmospheric boundary layer. Optimisation for both a single wind direction and multiple wind directions is discussed.
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Roslan, Sharul Baggio, Dimitrios Konovessis, and Zhi Yung Tay. "Sustainable Hybrid Marine Power Systems for Power Management Optimisation: A Review." Energies 15, no. 24 (December 19, 2022): 9622. http://dx.doi.org/10.3390/en15249622.
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The increasing environmental concerns due to emissions from the shipping industry have accelerated the interest in developing sustainable energy sources and alternatives to traditional hydrocarbon fuel sources to reduce carbon emissions. Predominantly, a hybrid power system is used via a combination of alternative energy sources with hydrocarbon fuel due to the relatively small energy efficiency of the former as compared to the latter. For such a hybrid system to operate efficiently, the power management on the multiple power sources has to be optimised and the power requirements for different vessel types with varying loading operation profiles have to be understood. This can be achieved by using energy management systems (EMS) or power management systems (PMS) and control methods for hybrid marine power systems. This review paper focuses on the different EMSs and control strategies adopted to optimise power management as well as reduce fuel consumption and thus the carbon emission for hybrid vessel systems. This paper first presents the different commonly used hybrid propulsion systems, i.e., diesel–mechanical, diesel–electric, fully electric and other hybrid systems. Then, a comprehensive review of the different EMSs and control method strategies is carried out, followed by a comparison of the alternative energy sources to diesel power. Finally, the gaps, challenges and future works for hybrid systems are discussed.
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Wang, Zhiliang, Xianan Li, Kunmin Liu, and Long Zhao. "Optimisation of regional energy demand networks based on flexible load model." Journal of Physics: Conference Series 2310, no. 1 (October 1, 2022): 012012. http://dx.doi.org/10.1088/1742-6596/2310/1/012012.
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Abstract The existing literature on integrated energy station-grid planning studies focuses on configuration planning. Therefore, a multi-objective hybrid particle swarm algorithm is used in this paper to solve a multi-objective optimisation model and combines a multi-indicator evaluation method based on evidence-based reasoning to select the solution with the highest evaluation value from multiple candidates (Pareto solution set) as the optimal solution. The optimal planning solution is selected from multiple candidates (Pareto solution set) by a multi-indicator evaluation method based on evidence-based reasoning, and the effectiveness of the proposed model is verified utilizing an example. The customer participation demand response optimises the demand curve by adjusting the flexible load, reduces the system operation cost and investment construction cost, and maximises the economic, environmental and reliability benefits of the integrated regional energy station grid.
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Hasan, Ghanim Thiab, Ali Hlal Mutlaq, and Mohammad Omar Salih. "Investigate the optimal power system by using hybrid optimization of multiple energy resources software." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 1 (April 1, 2022): 9. http://dx.doi.org/10.11591/ijeecs.v26.i1.pp9-19.
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Increasing the effects of global pollution and the availability of renewable energy sources has push many countries to use reasonable energy sources such as wind and solar energy. This paper presents a case study of evaluating a hybrid renewable energy system by using a hybrid optimization of multiple energy resources (HOMER) software program based on the entered data available from the net for the considered location. The hybrid system consisting of a wind turbine, a photovoltaic system, a battery and a diesel generator. The simulation results are presented in a graphical curves n HOMER software. The obtained results indicate that by using the HOMER simulation program, the optimal design of the hybrid electrical power system for the considered location can be achieved which can help the designer to decide the types and number of the competent required for conducting the intending hybrid electrical power system which results in optimum output power in addition to reducing the overall operating costs.
Dissertations / Theses on the topic "Hybrid Optimisation of Multiple Energy Resources"
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Xu, Chen. "Hybrid cell for harvesting multiple-type energies." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44782.
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An abundance of energy in our environment exists in the form of light, thermal, mechanical (e.g., vibration, sonic waves, wind, and hydraulic), magnetic, chemical, and biological. Harvesting these forms of energy is of critical importance for solving long-term energy needs and the sustainable development of the planet. However, conversion cells for harvesting solar energy and mechanical energy are usually independent entities that are designed and built following distinct physical principles. The effective and complementary use of such energy resources whenever and wherever one or all of them are available demands the development of innovative approaches for the conjunctional harvesting of multiple types of energy using an integrated structure/material. By combining solar and mechanical energy-harvesting modules into a single package for higher energy conversion efficiency and a more effective energy recovery process, the research has designed and demonstrated a hybrid cell for harvesting solar and mechanical energy. The results of the research show that we can fully utilize the energy available from our living environment by developing a technology that harvests multiple forms of both solar and mechanical energy 24 hours a day. As the proposed research represents a breakthrough in the innovation of energy harvesting, it should pave the way toward building a new field called "multi-type hybrid" energy harvesting.
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Fujdiak, Radek. "Analýza a optimalizace datové komunikace pro telemetrické systémy v energetice." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-358408.
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Telemetry system, Optimisation, Sensoric networks, Smart Grid, Internet of Things, Sensors, Information security, Cryptography, Cryptography algorithms, Cryptosystem, Confidentiality, Integrity, Authentication, Data freshness, Non-Repudiation.
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Saiprasad, Nithya. "Optimum sizing and triple bottom line analysis of integrating hybrid renewable energy systems into the micro-grid." Thesis, 2019. https://vuir.vu.edu.au/40010/.
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There have been growing concerns over global warming, and this has increased the awareness towards the reduction of Greenhouse gas (GHG) emissions. Many countries including Australia have signed the “Paris Agreement” to try and combat global climate change. This agreement aims to restrict global temperature rise under 2ºC above pre-industrial levels and further limit the temperature rise to 1.5ºC. In December 2018, the United Nations Climate Change conference was held in Katowice, Poland and a framework called the United Nations Framework Convention on Climate Change (COP24) was agreed upon to help in implementing regulations of 2015 Paris Agreement. The agreement also ensures boosting support to developing countries to counter this threat. In order to help the developing and the most vulnerable countries achieve these rather ambitious goals, this new framework will focus on technology, financial flows and capacity improvement.
The global reliance on fossil fuels, which contributes approximately 80% of primary energy, has resulted in the rise of global temperatures. Several countries have begun to reduce their reliance on fossil fuels and thus GHG emissions, by shifting their focus towards Renewable Energy (RE). Thus, RE has become a “go to” energy source to solve the aforementioned global issues with a pronounced focus on the guiding energy policies
Energy, economics and environment play a crucial role in ensuring the sustainability of a country. Adoption of RE would be the key to ensuring energy sustainability and also reducing the environmental impact, thus helping RE to reach the citizens. Having acknowledged these global challenges and thus relying on RE for the energy needs, sustainability can be achieved by modernising the present micro-grids by integrating RE into them. In order to integrate RE into the existing micro-grid, sizing of Distributed Energy Resources (DERs) using RE sources are investigated to improve their energy production mechanism and enhance the overall efficiency.
There are several approaches to size the RE sources into a micro-grid. Two approaches are followed for sizing HRES based on analysing the electricity consumption of the area of interest relying on: (i) Hybrid Optimisation of Multiple Energy Resources (HOMER) software and (ii) improved Hybrid Optimisation using Genetic Algorithm (iHOGA) software. This study highlights the issues related to the optimal sizing of the DERs by investigating their use of the novel application in micro-grids, using both photovoltaic (PV), wind turbine (WT) as the RES for supplying power to the grid for residences and commercial building at Aralvaimozhi, India and Warrnambool, Australia. These two chosen locations are bestowed with good sunlight and wind. The average solar radiation in Warrnambool 4.16kWh/m2/day and annual average wind velocity 5.96m/s. The wind speed and the average solar radiation at Aralvaimozhi are 7.16m/s and 5.05kWh/m2/day respectively. Aralvaimozhi has been spotted as a potential wind farm location according to the Government of Tamil Nadu.
India being a developing country and Australia, a developed country, their respective energy policies are scrutinised to understand their energy policies status. Suggestions to improve RE adoption by understanding the energy policies laid by other RE developed counties like Germany, USA, etc. have been conducted. Triple Bottom Line (TBL) analysis is conducted to understand the feasibility of adopting RE into a micro-grid. It focuses on the Techno-economic, environmental and social perspectives to understand the feasibility of RE adoption from the perspective of a developed country (Australia) versus a developing country (India). In this respect, a prototype model of the micro-grid is studied and used at Victoria University, Footscray Campus for various scenarios.
Book chapters on the topic "Hybrid Optimisation of Multiple Energy Resources"
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"Decentralised-distributed hybrid voltage control by inverter-based DERs." In Coordination of Distributed Energy Resources in Microgrids: Optimisation, control, and hardware-in-the-loop validation, 359–76. Institution of Engineering and Technology, 2021. http://dx.doi.org/10.1049/pbpo188e_ch16.
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Deogam, Nitish, and Shabbiruddin. "Optimal Site Selection for Solar Photovoltaic Power Plant in North Eastern State of India using Hybrid MCDM Tools." In Research Anthology on Clean Energy Management and Solutions, 965–89. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-9152-9.ch041.
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As society develops, the demand for energy also increases. Most of world's energy requirements are fulfilled using fossil fuels or other types of non-renewable resources, which are polluting the environment, but also depleting. For this reason, the Government of India and the Government of Sikkim (North Eastern State of India) are working on policies to promote investment in solar photovoltaic (PV) plants and has plans to use it to meet the growing energy demand without causing damage to the environment. To make the best use of solar PV cells on commercial scale, it is necessary to know how to optimize the output of the PV power plant, and the most important factor is the selection of the land or the area on which the PV power plant is to be set up. There are multiple factors one must take into consideration for better output. In this study, focus has been put on geographical and meteorological factors that affect the output of the PV cells. Multi criteria decision making (MCDM) techniques have been used for selection of best site for PV power plant.
Conference papers on the topic "Hybrid Optimisation of Multiple Energy Resources"
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Abedi, Mehdi, Raymond Chiong, Nasimul Noman, and Rui Zhang. "A hybrid particle swarm optimisation approach for energy-efficient single machine scheduling with cumulative deterioration and multiple maintenances." In 2017 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2017. http://dx.doi.org/10.1109/ssci.2017.8285316.
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Mitropoulou, D., M. Kalikatzarakis, T. van Der Klauw, AJ Blokland, RD Geertsma, AM Bucurenciu, and D. Dembinskas. "Multi-objective optimisation and Energy Management: adapt your ship to every mission." In International Ship Control Systems Symposium. IMarEST, 2020. http://dx.doi.org/10.24868/issn.2631-8741.2020.015.
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Adaptability, stealth, damage sustainability, extended range and reliability are key factors to every successful naval mission. The shipbuilding industry conceptualized and deployed a wide variety of power and propulsion architectures over the decades: from mechanical, to electrical and hybrid propulsion. The tendency towards increasingly complex propulsion and power generation systems calls for the development of intelligent control strategies, Energy Management Systems (EMSs), that can handle the complexity and exploit the increased degrees-of-freedom (DOFs) of hybrid systems, while conforming to all operational constraints. In current EMSs, the aim is to save fuel costs. However, the ability to adapt to a wide variety of missions in an ever changing world is important for naval vessels. Hence, this raises the question: Can further operational gains be achieved through the use of more sophisticated integrated control algorithm, with multiple optimization goals? The present work aims to address this issue, by developing such a control system for a naval platform. The proposed EMS can modulate shipboard energy production of a hybrid propulsion plant with hybrid power supply, considering the trade-off between multiple conflicting operating goals: fuel savings, maintenance costs of on-board assets, noise and infrared signature. A validated model of a Holland class Patrol Vessel has been utilized to test the proposed EMS. Simulation results under varying operational profiles demonstrate the applicability, validity and the advantages of the approach.
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Chou, Yu-Cheng. "A Hybrid Energy-Efficient Itinerary Planning for Mobile Agents in Wireless Sensor Networks." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12920.
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Wireless sensor networks (WSNs) are limited to resources including computing power, storage capacity, and especially energy supply. Thus, energy consumption of sensor nodes has become a dominant performance index for a WSN. In addition, data transmission between sensor nodes is a main energy consumer of WSNs. This paper presents a method called immune genetic algorithm based multiple-mobile-agent itinerary planning (IGA-M2IP) that addresses issues of energy consumption in large-scale WSNs. The IGA-M2IP preserves a GA’s advantages, and further improves a GA’s efficiency by restraining possible degenerative phenomena during the evolutionary process.
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Espinola Gonzalez, Oswaldo, Laura Paola Vazquez Macedo, Julio Cesar Villanueva Alonso, and Julieta Alvarez Martinez. "Novel Approach to Enhance Field Development Plan Process and Reservoir Management to Maximize the Recovery Factor of Gas Condensate Reservoirs Through Integrated Asset Modeling." In SPE Trinidad and Tobago Section Energy Resources Conference. SPE, 2021. http://dx.doi.org/10.2118/200895-ms.
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Abstract The proper exploitation for a gas condensate reservoir requires an integrated collaboration and management strategy capable to provide detailed insight about future behavior of the reservoir. When a development plan is generated for a field, the reservoir management is not performed integrally, this is, different domains: geology, reservoir, drilling, production, economics, etc., work separately, and therefore, an adequate understanding of the main challenges, leading to issues such as an over dimensioning of surface facilities, excessive costs, among others. Through this paper, a methodology to improve the conventional field development plan is described, which contains 4 main pillars: Collaborative approach, Integrated analysis, engineering optimization and monitoring & surveillance. The methodology involves the description of a hybrid workflow based on the integration of multiple domains, technologies and recommendations to consider all the phenomena and compositional changes over time in the whole production system, aiming to define the optimum reservoir management strategy, facilities and operational philosophy as part of the Field Development Plan (FDP). Conventionally, the used of simplistic models most of times do not allow seeing phenomena in the adequate resolution (near wellbore and porous media effects, multiphase flow in pipelines, etc.), that occur with high interdependency in the Integrated Production System. With this methodology, the goal pursued is to support oil and gas companies to increase the recovery factor of gas condensate fields through the enhancement in the development and exploitation process and therefore, reducing associated costs and seizing available time and resources.
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Contreras, Francisco J., David A. Romero, and Cristina H. Amon. "A Multilevel Optimization Method for the Design and Operation of Stand-Alone Hybrid Renewable Energy Systems for Multiple Remote Communities." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-38973.
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Recently, there has been increased interest in designing stand-alone Hybrid Renewable Energy Systems (HRES) for remote communities. Several methodologies have been proposed to tackle the design optimization problem, to develop strategies for optimal operation/dispatch, or to address both problems concurrently. So far, however, these methods have been developed only for specific communities or system configurations (e.g., wind-diesel; PV-diesel). In this study, we propose a multilevel design optimization method that considers both optimal component selection and dispatch strategy that can be applied to any community regardless of the available renewable resources, thus overcoming the limitations of previous studies. The new approach considers a wide range of renewable and non-renewable energy technologies, a database of commercially available components, and leverages state-of-the-art methods for solving each optimization subproblem. The novel algorithm was evaluated with a set of meteorological conditions that emulate different remote communities. In addition, two pricing scenarios for diesel are studied to explore how the HRES design is influenced by this parameter.
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Al-Qasim, Abdulaziz, Sharidah Alabduh, Muhannad Alabdullateef, and Mutaz Alsubhi. "Expanding the Envelope of Fiber-Optic Sensing for Reservoir Description and Dynamics." In SPE Trinidad and Tobago Section Energy Resources Conference. SPE, 2021. http://dx.doi.org/10.2118/200888-ms.
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Abstract Fiber-optic sensing (FOS) technology is gradually becoming a pervasive tool in the monitoring and surveillance toolkit for reservoir engineers. Traditionally, sensing with fiber optic technology in the form of distributed temperature sensing (DTS) or distributed acoustic sensing (DAS), and most recently distributed strain sensing (DSS), distributed flow sensing (DFS) and distributed pressure sensing (DPS) were done with the fiber being permanently clamped either behind the casing or production tubing. Distributed chemical sensing (DCS) is still in the development phase. The emergence of the composite carbon-rod (CCR) system that can be easily deployed in and out of a well, similar to wireline logging, has opened up a vista of possibilities to obtain many FOS measurements in any well without prior fiber-optic installation. Currently, combinations of distributed FOS data are being used for injection management, well integrity monitoring, well stimulation and production performance optimization, thermal recovery management, etc. Is it possible to integrate many of the distributed FOS measurements in the CCR or a hybrid combination with wireline to obtain multiple measurements with one FOS cable? Each one of FOS has its own use to get certain data, or combination of FOS can be used to make a further interpretation. This paper reviews the state of the art of the FOS technology and the gamut of current different applications of FOS data in the oil and gas (upstream) industry. We present some results of traditional FOS measurements for well integrity monitoring, assessing production and injection flow profile, cross flow behind casing, etc. We propose some nontraditional applications of the technology and suggest a few ways through. Which the technology can be deployed for obtaining some key reservoir description and dynamics data for reservoir performance optimization.
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Ruvalcaba Velarde, Salvador Alejandro. "Multi-Objective Optimisation Analysis for Off-Grid, On-Site Power Generation Comparing Hybrid Renewable Energy Systems and Gas-to-Power Systems In Upstream Applications." In SPE Middle East Oil & Gas Show and Conference. SPE, 2021. http://dx.doi.org/10.2118/204814-ms.
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Abstract As the oil and gas industry increases its focus on sustainability, including greenhouse gases emissions reductions and carbon footprint management, it is relevant to analyze optimal solutions integrating different renewable, green and hydrogen technologies into hybrid renewable energy systems and compare them with well gas-to-power approaches for off-grid, on-site power generation in upstream applications. This paper goes through a desk review of different types of upstream facilities and an overview of potential power requirements to consider for off-grid electrification. Then, different technologies used for off-grid hybrid renewable energy systems are introduced and compared in terms of potential uses and integration requirements. Furthermore, emission targets are presented along with potential economical constraints. With those aspects introduced, system sizing and assumptions are modeled, simulated and optimized. The different modeled cases, including integrated renewable energy systems and power-to-gas systems, are presented in terms of suitability in application to the facilities under consideration. For such cases, simulation results are presented in quantitative terms of equivalent optimized value for the multiple competing objectives in the study, in terms of sustainability targets and economics. Sensitivity analysis are also presented showing main parameters of influence on the optimal energy scheme approach. This paper provides a qualitative and quantitative analytical optimization approach evaluating multiple competing objectives in terms of green, renewable, hydrogen and gas-to-power technologies, economics and carbon footprint management for consideration in facilities power systems schemes.
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Srinivasan, Ashwin, Gaurav Modi, Rahul Agrawal, and Viren Kumar. "Application of Advanced Data Analytics for Gas Reservoirs and Wells Management." In SPE Trinidad and Tobago Section Energy Resources Conference. SPE, 2021. http://dx.doi.org/10.2118/200927-ms.
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Abstract Objectives/Scope The amount of time and effort required to access and integrate Subsurface data from multiple sources is significant. Using Advanced Data Analytics, mainly python, an integrated subsurface dashboard titled Hybrid Integrated Visualization Environment (HIVE) was created using Spotfire to empower the integrated Exploration, Development and Well Reservoir and Facilities Management (WRFM) subsurface teams in: Professionalizing data and knowledge management to have "one" version of the truth. Data consolidation and preparation to avoid repetitive manual work & Enhancing opportunity identification to optimize production and value Methods, procedure, process The approach of subsurface data integration can be broken down into 4 major steps, namely: Step 1: Python programming was used to pre-process, restructure and create unified data frames. Use of python significantly reduces the time required to pre-process a diverse number of subsurface data sources consisting of static, dynamic reservoir models, log data, historical production & pressure data and wells & completion data to name a few. Step 2: - Standard diagnostic industry recognized diagnostic plots were automated using advanced analytic techniques in HIVE with the help of unified data frames. Step 3: HIVE was created to link various internal corporate data stores like pressure, temperature, rate data from PI System (stores real time measured data), Energy Components (EC) and Oil Field Manager (OFM) in real time. This was done to ensure that data from various petroleum engineering disciplines could now be visualized and analyzed in a structured manner to make integrated business decisions. Step 4: One of the key objectives of pursuing this initiative was to ensure that subsurface professionals in Shell Trinidad and Tobago were trained and upskilled in the use of python as well visualization tools like Spotfire and Power BI to ensure the maintenance and improvement of HIVE going forward. Results, Observations, Conclusions The development of HIVE has made it easier and more efficient to access and visualize subsurface data, which was extremely time consuming earlier while using older conventional techniques. Standard diagnostic plots and visuals were developed and are now used to drive integrated decision making, with key focus being water and sand production management from a production management perspective. Consequently, HIVE also drives enhanced integration between disciplines (Petrophysics, Petroleum Geology, Production Technology, Reservoir Engineering and Production operations) and departments (Developments, Upstream and Exploration). Novel/Additive Information The petroleum industry has started to embrace the application of advanced data analytics in our day-to-day work. A successful application of these techniques results in transforming the ways of working by increasing efficiency, transparency and integration among teams.
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Cheng, Rui, Jian Dong, and Zuomin Dong. "Modeling and Simulation of a Multiple-Regime Plug-In Hybrid Electric Vehicle." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-13619.
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In recent years, the automotive industry has devoted considerable resources to the research and development of hybrid vehicles. Plug-in hybrid electric vehicles (PHEV) present to be the next generation hybrid vehicles that offer the advantages in reducing fossil fuel consumption and lowering emissions without sacrifice vehicle performance, and the ability to utilize renewable energy through charge from the electric grid. In this work, the powertrain model of a series-parallel, multiple-regime plug-in hybrid electric vehicle (SPMR-PHEV) was introduced. As one of the several parallel powertrain modeling, simulation and control system design approaches at University of Victoria, the presented SPMR-PHEV model was developed using rule-based load-leveling energy management strategy (EMS) under the MATLAB/Simulink and SimDriveline environment. In order to validate the model and evaluate the fuel consumption and performance of SPMR-PHEV, a Simulink based Prius model and two different PHEV powertrain models have also been built using Autonomie — a vehicle simulation tool developed by DOE’s Argonne National Laboratory, using the default control logics. Fuel consumption from the three different models were compared using a test drive case consisting of eight times of the US06-City drive cycle. Under the static modeling and simulation method and different control strategies, the SPMR-PHEV model in Simulink/SimDriveline and rule-based load-leveling EMS showed 12.02% fuel economy and powertrain efficiency improvements over the Autonomie model. The new powertrain system model developed using Simulink and SimDrivline could also be used as a generic, modular and flexible vehicle modeling platform to support the integration of powertrain design and control system optimization.
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Moulik, Bedatri, and Dirk Söffker. "Combined Voltage-Current Control of DC/DC Converters for Power Management of a Multi-Power Source Hybrid With HIL Tests." In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-5937.
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Rising fuel prices and fast depletion of energy resources have led to an increasing interest in green technology. Hybrid vehicles due to their ability to draw power from multiple energy sources are a preferred option. Although the components such as supercapacitors, batteries, internal combustion engine, or a fuel cell, generally needed to realize a hybrid topology are known, the topology of their arrangement and realization by interchanging the components and combining different power sources, needs to be studied. In this paper, various hybrid powertrain configurations in combination with different storage elements are compared and a suitable control and power management strategy for a multi-power source powertrain system is implemented using a scalable test rig. In order to validate the component design and topology, Hardware-in-the-Loop (HiL) tests are carried out with the help of an emulator set-up.