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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.
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Rahat, Alma A. M., Richard M. Everson, and Jonathan E. Fieldsend. "Hybrid Evolutionary Approaches to Maximum Lifetime Routing and Energy Efficiency in Sensor Mesh Networks." Evolutionary Computation 23, no. 3 (September 2015): 481–507. http://dx.doi.org/10.1162/evco_a_00151.
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Mesh network topologies are becoming increasingly popular in battery-powered wireless sensor networks, primarily because of the extension of network range. However, multihop mesh networks suffer from higher energy costs, and the routing strategy employed directly affects the lifetime of nodes with limited energy resources. Hence when planning routes there are trade-offs to be considered between individual and system-wide battery lifetimes. We present a multiobjective routing optimisation approach using hybrid evolutionary algorithms to approximate the optimal trade-off between the minimum lifetime and the average lifetime of nodes in the network. In order to accomplish this combinatorial optimisation rapidly, our approach prunes the search space using k-shortest path pruning and a graph reduction method that finds candidate routes promoting long minimum lifetimes. When arbitrarily many routes from a node to the base station are permitted, optimal routes may be found as the solution to a well-known linear program. We present an evolutionary algorithm that finds good routes when each node is allowed only a small number of paths to the base station. On a real network deployed in the Victoria & Albert Museum, London, these solutions, using only three paths per node, are able to achieve minimum lifetimes of over 99% of the optimum linear program solution’s time to first sensor battery failure.
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Gonsrang, S., and R. Kasper. "Optimisation-Based Power Management System for an Electric Vehicle with a Hybrid Energy Storage System." International Journal of Automotive and Mechanical Engineering 15, no. 4 (December 24, 2018): 5729–47. http://dx.doi.org/10.15282/ijame.15.4.2018.2.0439.
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Hybridisation of energy storage sources is necessary for extending mileage of electric vehicles. However, coordination of multiple devices with different characteristics is challenging. This paper presents a power management system (PMS) for an electric car equipped with a battery pack, supercapacitor bank, and range extender. The proposed PMS deals with vehicular load distribution by solving a power management problem, formulated as a constrained quadratic program (CQP). Then, the optimised variables, such as the desired speed and optimised operation points of the car’s components, are implemented by controllers at a component level. Complete knowledge about the trip is unwanted because the proposed PMS considers a power management problem only over a controlled horizon of one sampling period. Furthermore, this work varies weight factors to tackle various difficulties, for instance, regenerative power management. The simulation results revealed that the proposed system optimally allocated an electric power load to the car components, without violating any physical constraints. Also, the comparative study showed that the performance of the CQP in power management was comparable to that of the benchmark, based on a nonlinear model predictive control.
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USACHEVA, IRINA V., ELENA A. GLADKAYA, and SERGEY V. LANDIN. "HYBRID ENERGY STORAGE: PROBLEMS AND PROSPECTS OF ENERGY STORAGE TECHNOLOGIES." Scientific Works of the Free Economic Society of Russia 236, no. 4 (2022): 149–67. http://dx.doi.org/10.38197/2072-2060-2022-236-4-149-167.
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The ever-increasing trend of renewable energy sources (RES) in energy systems of various levels has increased uncertainty in their operation and management. The vulnerability of RES to unforeseen changes in meteorological conditions requires additional resources to support, which are energy storage systems (ESS). However, existing ETSs have limited capacity to meet all the requirements of a modern enterprise energy system. Thus, the hybridization of multiple ETSs to form a composite ETS is a potential solution to this problem. As a flexible energy source, energy storage has many potential applications for integration into renewable energy generation, transmission and distribution networks. This paper analyzes the prospects for hybrid energy storage applications and summarizes the latest experience in terms of the maturity of these technologies, efficiency, scale, lifetime, cost and applications, taking into account their impact on the entire power system, including generation, transmission, distribution and utilization. The challenges of large-scale applications of energy storage in power systems are presented in terms of technical and economic considerations.
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Jaszczur, Marek, Qusay Hassan, Haidar N. Al-Anbagi, and Patryk Palej. "A numerical analysis of a HYBRID PV+WT power system." E3S Web of Conferences 128 (2019): 05001. http://dx.doi.org/10.1051/e3sconf/201912805001.
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The increase in global energy consumption and the expected exhaustion of traditional energy sources, especially in the last century, led to an increased search for alternative sources of energy.The use of renewable energy sources has become extremely important to reduce dependence on fossil fuels. Due to the stochastic nature of the renewable energy sources such as the wind speed fluctuation and the intensity of solar radiation the stable operation of the systems base single renewable source can be problematic. But the using two or more of these sources results in higher stability than relying on a single source. For this reason, hybrid renewable energy systems have become an attractive solution in thefield of renewable energy. A hybrid energy system is a combination of two or more renewable energy sources that can enhance each another to increase the reliability of the supplied energy. The objective of this paper is investigation about the energy supplying improvement and the energy efficiency utilisation by hybridisation using two renewable energy resources: wind energy and solar energy with respect two different optimisation objectives: economical to reduce the net present cost and ecological to reduce CO2 emissions. Presented system has been implemented to supply a single household with an electric load.
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Bin, Yang, Yaoyu Li, and Zhong Ren Peng. "Multiple trip information based spatial domain optimisation for power management of plug-in hybrid electric vehicles." International Journal of Electric and Hybrid Vehicles 2, no. 4 (2010): 259. http://dx.doi.org/10.1504/ijehv.2010.034980.
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Kaur, Jaspreet, and Amit Kumar Bindal. "Resource Aware Hybrid Energy Harvesting for Wireless Sensor Networks." Journal of Computational and Theoretical Nanoscience 16, no. 10 (October 1, 2019): 4117–24. http://dx.doi.org/10.1166/jctn.2019.8490.
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Sensors consume the resources to perform different operations, and energy of the nodes may be depleted due to excessive computational load; thus, may reduce the overall network lifespan as well as coverage area. Traditional energy harvesting schemes provides energy to the nodes in linear way but these schemes depend over a single source as well as these do not interact with the routing protocol. In this paper, a Hybrid Energy Harvester scheme for wireless sensor network is introduced which can utilize multiple energy sources for harvesting and also interact with the routing protocols to fulfill their energy requirements. Simulation based analysis using various protocols are performed under the QoS constraints.
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Akrami, Mohammad, Samuel J. Gilbert, Mahdieh Dibaj, Akbar A. Javadi, Raziyeh Farmani, Alaa H. Salah, Hassan E. S. Fath, and Abdelazim Negm. "Decarbonisation Using Hybrid Energy Solution: Case Study of Zagazig, Egypt." Energies 13, no. 18 (September 8, 2020): 4680. http://dx.doi.org/10.3390/en13184680.
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In this study, an analysis is carried out to determine the optimal application of multiple renewable energy resources, namely wind and solar, to provide electricity requirements for green smart cities and environments. This was done to determine the potential of renewable energy to provide clean, economically viable energy for the case study of Zagazig, located at 30°34′ N 31°30′ E in the North East of Egypt. The relevant data surrounding the production of energy were collected, including the meteorological data from NASA, and specifications regarding renewable resources including solar panels, wind turbines, and storage batteries. Then a hybrid model was constructed consisting of Photovoltaics (PV) panels, wind turbines, a converter, and storage batteries. Once the model was constructed, meteorological data were added alongside average daily demand and cost of electricity per kWh. The optimal solution for Zagazig consisted of 181,000 kW of solar panels feeding directly into the grid. This system had the lowest Net Present Cost (NPC) of the simulations run of US$1,361,029,000 and a net reduction of 156,355 tonnes of CO2 per year.
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Obukhov, M. Yu, and N. P. Kalinin. "Reducing the cost of fuel and energy resources through the use of hybrid multi-unit rolling stock." PROCEEDINGS OF PETERSBURG TRANSPORT UNIVERSITY 18, no. 1 (March 31, 2021): 25–33. http://dx.doi.org/10.20295/1815-588x-2021-1-25-33.
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Objective: Analysis of the economic feasibility of replacing diesel multiple units with hybrid ones exemplified by the Saint Petersburg–Vyborg route (through Primorsk). Methods: To solve the problem of energy efficiency of multiple units, an integrated approach is applied which is focused on the practical significance and economic feasibility of the results. Results: The data obtained can serve as a basis for the rational selection of rolling stock to use in the sections with alternating arrangement of autonomous and non-autonomous traction. Practical importance: The concept developed will allow for effective selection of multiple units for operation in the sections with alternating arrangement of autonomous and non-autonomous traction.
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Tazvinga, Henerica, Oliver Dzobo, and Maxwell Mapako. "Towards sustainable energy system options for improving energy access in Southern Africa." Journal of Energy in Southern Africa 31, no. 2 (June 14, 2020): 59–72. http://dx.doi.org/10.17159/2413-3051/2020/v31i1a6504.
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Access to modern energy services is one of the pre-requisites to improved livelihood, yet the poor, particularly in developing countries, remain tied to unhealthy and inefficient traditional fuels. Renewable energy technologies are increasingly popular energy supply alternatives to fossil-based fuels in many countries. This study presents sustainable energy system implementation options for increasing energy access in developing countries, with special emphasis on Sub-Saharan Africa. A feasibility case study and various implementation options are presented for possible deployment of these systems. Hybrid optimization of multiple energy resources software was used to simulate and validate the proposed hybrid system design and performance. The simulation results indicate that hybrid systems would be feasible options for distributed generation of electric power for remote locations and areas not connected to the electricity grid. Such a hybrid energy system, through providing modern energy services, gives promise to free-up rural communities to engage in productive activities. The opportunity to power or facilitate productive activities such as agro-processing, fabrication and services can potentially reduce poverty.
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Elgammal, Adel, and Mohamed El-Naggar. "Energy management in smart grids for the integration of hybrid wind–PV–FC–battery renewable energy resources using multi-objective particle swarm optimisation (MOPSO)." Journal of Engineering 2018, no. 11 (November 1, 2018): 1806–16. http://dx.doi.org/10.1049/joe.2018.5036.
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Mhashilkar, Parag, Mine Altunay, Eileen Berman, David Dagenhart, Stuart Fuess, Burt Holzman, James Kowalkowski, et al. "HEPCloud, an Elastic Hybrid HEP Facility using an Intelligent Decision Support System." EPJ Web of Conferences 214 (2019): 03060. http://dx.doi.org/10.1051/epjconf/201921403060.
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HEPCloud is rapidly becoming the primary system for provisioning compute resources for all Fermilab-affiliated experiments. In order to reliably meet the peak demands of the next generation of High Energy Physics experiments, Fermilab must plan to elastically expand its computational capabilities to cover the forecasted need. Commercial cloud and allocation-based High Performance Computing (HPC) resources both have explicit and implicit costs that must be considered when deciding when to provision these resources, and at which scale. In order to support such provisioning in a manner consistent with organizational business rules and budget constraints, we have developed a modular intelligent decision support system (IDSS) to aid in the automatic provisioning of resources spanning multiple cloud providers, multiple HPC centers, and grid computing federations. In this paper, we discuss the goals and architecture of the HEPCloud Facility, the architecture of the IDSS, and our early experience in using the IDSS for automated facility expansion both at Fermi and Brookhaven National Laboratory.
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Munsamy, Megashnee, Arnesh Telukdarie, and Johannes Fresner. "Business process centric energy modelling." Business Process Management Journal 25, no. 7 (October 14, 2019): 1867–90. http://dx.doi.org/10.1108/bpmj-08-2018-0217.
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Purpose Sustainability is an accepted measure of business performance, with reductions in energy demand a commonly practised sustainability initiative by multinational corporations (MNCs). Traditional energy models have limited scope when applied to the entire MNC as the models exhibit high data and time intensity, high technical proficiency, specificity of application and omission of non-manufacturing activities. The purpose of this paper is to propose a process centric energy model (PCEM), which adopts a novel approach of applying business processes for business energy assessment and optimisation. Business processes are a fundamental requirement of MNCs across all sectors. The defining features of the proposed model are genericity, reproducibility, minimum user input data, reduced modelling time and energy evaluation of non-manufacturing activities. The approach forwards the adoption of Industry 4.0, a subset of which focuses on business process automation or part thereof. Design/methodology/approach A quantitative approach is applied in development of the PCEM. The methodology is demonstrated by application to the procure to pay and electroplating business processes. Findings The PCEM quantifies and optimises the business energy demand and associated carbon dioxide emissions of the procure to pay and electroplating business processes, validating the application of business processes. The application demonstrates minimum user inputs as only equipment operational parameters are required and minimum modelling time as business process models and optimisation options are pre-defined requiring only user modification. As MNCs have common business processes across multiple sites, once a business process energy demand is quantified, its inputs are applied as the default in the proceeding sites, only requiring updating. The model has no specialist skills requirement enabling business wide use and eliminating costs associated with training and expert’s services. The business processes applied in the evaluation are developed by the researchers and are not as comprehensive as those in actual MNCs, but is sufficiently detailed to accurately calculate an MNC energy demand. The model databases are not exhaustive of all resources found in MNCs. Originality/value This paper provides a new approach to MNC business energy assessment and optimisation. The model can be applied to MNEs across all sectors. The model allows the integration of manufacturing and non-manufacturing activities, as it occurs in practice, providing holistic business energy assessment and optimisation. The model analyses the impacts of the adoption of Industry 4.0 technologies on business energy demand, CO2 emission and personnel hours.
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Paul, Aditi, and Indu Pandey. "Multi-Source Hybrid Energy Harvesting Wireless Sensor Network Framework for Addressing Energy Unpredictability Issues." International Journal of Engineering Research in Africa 57 (November 9, 2021): 225–41. http://dx.doi.org/10.4028/www.scientific.net/jera.57.225.
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Energy harvesting wireless sensor network (EH-WSN) harvests energy from the environment to supply power to the sensor nodes which apparently enhances their lifetime. However, the unpredictable nature of the resources throws challenges to the sustainability of energy supply for the continuous network operation. This creates a gap between unstable energy harvesting rates & energy requirements of the nodes of the network. The state-of-the-art algorithms proposed so far to address this problem domain are not able to bridge the gap fully to standardize the framework. Hence there is considerable scope of research to create a trade-off between EH techniques and specially designed protocols for in EH-WSN. Current study evaluates the performance and efficiency of some futuristic techniques which incorporate advanced tools and algorithms. The study aims to identify the strength and weaknesses of the proposed techniques which can emerge specific research requirement in this field. Finally, we propose a research direction towards Multi-source Hybrid EH-WSN (MHEHWSN) which is able to maximize energy availability and functional efficiency. The scope of this study is to develop a notion of a framework which eliminates the limitations of very recent techniques of EH-WSN by including multiple energy resources to extract required energy even in presence of unpredictability. However, keeping in mind the ease of use and less complex structure Multi-source hybrid EH technique requires a careful design paradigm.
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Ji, Jie, Zujun Ding, Xin Xia, Yeqin Wang, Hui Huang, Chu Zhang, Tian Peng, et al. "System Design and Optimisation Study on a Novel CCHP System Integrated with a Hybrid Energy Storage System and an ORC." Complexity 2020 (September 26, 2020): 1–14. http://dx.doi.org/10.1155/2020/1278751.
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For achieving higher energy transferring efficiency from the resources to the load, the Combined Cooling, Heating, and Power (CCHP) systems have been widely researched and applied as an efficient approach. The key idea of this study is designing a novel structure of a hybrid CCHP system and evaluating its performance. In this research, there is a hybrid energy storage unit enhancing the whole system’s operation flexibility while supplying cooling, heating, and power. An ORC system is integrated into the CCHP system which takes responsibility of absorbing the low-temperature heat source for electricity generation. There are a few research studies focusing on the CCHP systems’ performance with this structure. In order to evaluate the integrated system’s performance, investigation and optimisation work has been conducted with the approaches of experimental studies and modelling simulation. The integrated system’s configuration, the model building process of several key components, the optimisation method, and the case studies are discussed and analysed in this study. The design of the integrated system and the control strategy are displayed in detail. Several sets of dynamic energy demand profiles are selected to evaluate the performance of the integrated system. The simulation study of the system supplying selected scenarios of loads is conducted. A comprehensive evaluation report indicates that the system’s efficiency during each study process differs while supplying different loads. The results include the power supplied by each component, the energy consumed by each type of load, and the efficiency improvements. It is found that the integrated system fully satisfies the selected domestic loads and various selected scenarios of loads with high efficiency. Compared to conventional power plants or CHP systems, the system efficiency enhancement comes from higher amount of recovery waste heat. Especially, the ORC system can absorb the low-temperature heat source for electricity generation. Compared to the original following electrical load (FEL) control strategy, the optimisation process brings overall efficiency improvements. The system’s overall efficiency was increased by from 3%, 3.18%, 2.85%, 17.11%, 8.89%, and 21.7% in the second case studies. Through the whole study, the main challenge lies within the design and the energy management of the integrated system.
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Yang, Yuqing, Stephen Bremner, Chris Menictas, and Merlinde Kay. "A Mixed Receding Horizon Control Strategy for Battery Energy Storage System Scheduling in a Hybrid PV and Wind Power Plant with Different Forecast Techniques." Energies 12, no. 12 (June 18, 2019): 2326. http://dx.doi.org/10.3390/en12122326.
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This paper presents a mixed receding horizon control (RHC) strategy for the optimal scheduling of a battery energy storage system (BESS) in a hybrid PV and wind power plant while satisfying multiple operational constraints. The overall optimisation problem was reformulated as a mixed-integer linear programming (MILP) problem, aimed at minimising the total operating cost of the entire system. The cost function of this MILP is composed of the profits of selling electricity, the cost of purchasing ancillary services for undersupply and oversupply, and the operation and maintenance cost of each component. To investigate the impacts of day-ahead and hour-ahead forecasting for battery optimisation, four forecasting methods, including persistence, Elman neural network, wavelet neural network and autoregressive integrated moving average (ARIMA), were applied for both day-ahead and hour-ahead forecasting. Numerical simulations demonstrated the significant increased efficiency of the proposed mixed RHC strategy, which improved the total operation profit by almost 29% in one year, in contrast to the day-ahead RHC strategy. Moreover, the simulation results also verified the significance of using more accurate forecasting techniques, where ARIMA can reduce the total operation cost by almost 5% during the whole year operation when compared to the persistence method as the benchmark.
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Yang, Myeong-Gyu, Ngoc-Son Pham, Seong-Wook Choi, Keun-Yong Chung, Kwang-Hyun Baek, and Yong Shim. "SIMO DC-DC Converter with Low-Complexity Hybrid Comparator-Charge Control." Energies 15, no. 3 (January 21, 2022): 783. http://dx.doi.org/10.3390/en15030783.
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A hybrid control method using a comparator and a charge control method is proposed for a single-inductor multiple-output (SIMO) DC-DC converter. SIMO DC-DC converters have the weaknesses relating to cross-regulation, as all the output channels share the energy stored in a single inductor. Although multiple control methods such as Time-Multiplexing Control (TMC) and Ordered Power Distributing Control (OPDC) have been proposed to prevent cross-regulation or to improve load capability, effective use of limited resources appears to have not yet been achieved. This paper introduces a hybrid control topology that (1) utilizes comparator-based regulations for most outputs and (2) uses a new charge control loop method for the last output to reduce cross-regulation with low hardware complexity. In addition, the proposed scheme efficiently reuses the system’s redundant energy by adaptively controlling the freewheeling switch that opens the path to the input battery to store the surplus energy resources again. The proposed SIMO DC-DC converter was designed and validated with a 0.18 μm 3.3 V CMOS process. The converter has four regulated outputs of 0.9, 1.2, 1.5, and 2.2 V, and as a result of the simulation, it was found that the cross-regulation was estimated to be 0.4 mV/mA when the output current changes by ~200 mA. In addition, estimated peak power conversion efficiency of 88.5% was achieved at a total output power of 405 mW.
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Mohseni, Soheil, Alan C. Brent, and Daniel Burmester. "Off-Grid Multi-Carrier Microgrid Design Optimisation: The Case of Rakiura–Stewart Island, Aotearoa–New Zealand." Energies 14, no. 20 (October 11, 2021): 6522. http://dx.doi.org/10.3390/en14206522.
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The establishment of the concept of sustainable, decentralised, multi-carrier energy systems, together with the declining costs of renewable energy technologies, has proposed changes in off-grid electrification interventions towards the development of integrated energy systems. Notwithstanding the potential benefits, the optimal capacity planning of such systems with multiple energy carriers—electricity, heating, cooling, hydrogen, biogas—is exceedingly complex due to the concurrent goals and interrelated constraints that must be relaxed. To this end, this paper puts forward an innovative new optimal capacity planning method for a first-of-its-kind stand-alone multiple energy carrier microgrid (MECM) serving the electricity, hot water, and transportation fuel demands of remote communities. The proposed off-grid MECM system is equipped with solar photovoltaic panels, wind turbines, a hydrogen-based energy storage system—including an electrolyser, a hydrogen reservoir, and a fuel cell—a hybrid super-capacitor/battery energy storage system, a hot water storage tank, a heat exchanger, an inline electric heater, a hydrogen refuelling station, and some power converters. The main objective of calculating the optimal size of the conceptualised isolated MECM’s components through minimising the associated lifetime costs is fulfilled by a specifically developed meta-heuristic-based solution algorithm subject to a set of operational and planning constraints. To evaluate the utility and effectiveness of the proposed method, as well as the technical feasibility and economic viability of the suggested grid-independent MECM layout, a numerical case study was carried out for Rakiura–Stewart Island, Aotearoa–New Zealand. Notably, the numeric simulation results highlight that the optimal solution presents a low-risk, high-yield investment opportunity, which is able to save the diesel-dependent community a significant 54% in electricity costs (including electrified space heating)—if financed as a community renewable energy project—apart from providing a cost-effective and resilient platform to serve the hot water and transportation fuel needs.
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Sun, Wei, Sam Harrison, and Gareth P. Harrison. "Value of Local Offshore Renewable Resource Diversity for Network Hosting Capacity." Energies 13, no. 22 (November 12, 2020): 5913. http://dx.doi.org/10.3390/en13225913.
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It is imperative to increase the connectable capacity (i.e., hosting capacity) of distributed generation in order to decarbonise electricity distribution networks. Hybrid generation that exploits complementarity in resource characteristics among different renewable types potentially provides value for minimising technical constraints and increasing the effective use of the network. Tidal, wave and wind energy are prominent offshore renewable energy sources. It is of importance to explore their potential complementarity for increasing network integration. In this work, the novel introduction of these distinct offshore renewable resources into hosting capacity evaluation enables the quantification of the benefits of various resource combinations. A scenario reduction technique is adapted to effectively consider variation of these renewables in an AC optimal power flow-based nonlinear optimisation model. Moreover, the beneficial impact of active network management (ANM) on enhancing the renewable complementarity is also investigated. The combination of complementary hybrid generation and ANM, specifically where the maxima of the generation profiles rarely co-occur with each other and with the demand minimum, is found to make the best use of the network components.
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Phan and Lai. "Control Strategy of a Hybrid Renewable Energy System Based on Reinforcement Learning Approach for an Isolated Microgrid." Applied Sciences 9, no. 19 (September 24, 2019): 4001. http://dx.doi.org/10.3390/app9194001.
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Due to the rising cost of fossil fuels and environmental pollution, renewable energy (RE) resources are currently being used as alternatives. To reduce the high dependence of RE resources on the change of weather conditions, a hybrid renewable energy system (HRES) is introduced in this research, especially for an isolated microgrid. In HRES, solar and wind energies are the primary energy resources while the battery and fuel cells (FCs) are considered as the storage systems that supply energy in case of insufficiency. Moreover, a diesel generator is adopted as a back-up system to fulfill the load demand in the event of a power shortage. This study focuses on the development of HRES with the combination of battery and hydrogen FCs. Three major parts were considered including optimal sizing, maximum power point tracking (MPPT) control, and the energy management system (EMS). Recent developments and achievements in the fields of machine learning (ML) and reinforcement learning (RL) have led to new challenges and opportunities for HRES development. Firstly, the optimal sizing of the hybrid renewable hydrogen energy system was defined based on the Hybrid Optimization Model for Multiple Energy Resources (HOMER) software for the case study in an island in the Philippines. According to the assessment of EMS and MPPT control of HRES, it can be concluded that RL is one of the most emerging optimal control solutions. Finally, a hybrid perturbation and observation (P&O) and Q-learning (h-POQL) MPPT was proposed for a photovoltaic (PV) system. It was conducted and validated through the simulation in MATLAB/Simulink. The results show that it showed better performance in comparison to the P&O method.
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Kaldate, Avinash, Amarsingh Kanase-Patil, and Shashikant Lokhande. "Optimization and Techno-Economic Analysis of PV-Wind Power Systems for Rural Location in India." E3S Web of Conferences 170 (2020): 01015. http://dx.doi.org/10.1051/e3sconf/202017001015.
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One downside to Green Energy is that it cannot be estimated. Therefore, determining the optimum planning and perfect working strategies for the resources to be included in the hybrid system is very important. HOMER software has been used in this research paper to solve the case study of the hybrid renewable energy system. Due to its extensive analytical capabilities and advanced prediction capabilities based on the sensitivity of variables, HOMER is one of the most used software for optimal planning purposes. A case study for the sizing of a renewable energy-based hybrid system is solved in this article, using the Hybrid Optimization of Multiple Energy Resources (HOMER) software. Photovoltaic panels (PV panels), wind turbines (WT), batteries, converters, electric charge and grid are used in case study. The results of the simulation are presented in graphical form and tabulated for better system visualization. The design of a system to supply 6.8 KWh/d whereas the peak is 1.04 KW electric loads has been performed using HOMER software. In order to allow the user to choose the most suitable option, a comparative analysis has made, showing the pros and cons of cases. Optimum construction conditions help to lower operating costs.
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Babatunde, Olubayo Moses, Damilola Elizabeth Babatunde, Iheanacho Henry Denwigwe, Toyosi Beatrice Adedoja, Oluwaseye Samson Adedoja, and Taiwo Emmanuel Okharedia. "Analysis of an optimal hybrid power system for an off-grid community in Nigeria." International Journal of Energy Sector Management 14, no. 2 (November 4, 2019): 335–57. http://dx.doi.org/10.1108/ijesm-01-2019-0009.
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Purpose This study aims to analyze the effects of variations in annual real interest rates in the assessment of the techno-economic feasibility of a hybrid renewable energy system (HRES) for an off-grid community. Design/methodology/approach Hybrid Optimization of Multiple Energy Resources (HOMER) software is used to propose an HRES for Abadam community in northern Nigeria. The HRES was designed to meet the basic needs of the community over a 25-year project lifespan. Based on the available energy resources in the community, photovoltaic (PV), wind turbine, diesel generator and battery were suggested for integration to serve the load requirements. Findings When the annual real interest rates were taken as 10 and 8 per cent, the total amount of total energy fraction from PV, wind turbine and the diesel generator is 28, 57 and 15 per cent, respectively. At these interest rates, wind turbines contributed more energy across all months than other energy resources. The energy resource distribution for 0, 2,4 and 6 per cent annual real interest rates have a similar pattern, but PV contributed a majority of the energy. Practical implications This study has used annual real interest and inflation rates dynamic behavior to determine optimal HRES for remote communities. Hence, its analysis will equip decision-makers with the necessary information for accurate planning. Originality/value The results of this study can be used to plan and design HRES infrastructure for off-grid communities around the world.
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Okhaifoh, Joseph E., Godwin Uzedhe, and Ishioma A. Odigwe. "Hybrid Energy Systems: Optimal Resource Determination and Cost Evaluation Using Homer Grid Software." Equity Journal of Science and Technology 8, no. 1 (April 18, 2022): 33–39. http://dx.doi.org/10.4314/equijost.v8i1.5.
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This paper proposes a resource evaluation and validation study of a grid-connected hybrid power system whichtends to maximize the use of renewable energy generation with energy storage systems while minimizing thetotal system cost. The HOMER (Hybrid Optimization of Multiple Energy Resources) Grid software is adoptedin this study to find the optimal configuration of solar energy sources with battery storage systems to delivercomplementary electricity supply to satisfy AC primary load of 68.55 kWh/day with a 10.2 kW peak loaddemand to a building on a University campus premises located in the Niger Delta region of Nigeria. The resultsobtained from simulations showed a list of feasible resource configurations for the hybrid system. However,the most optimal/economical configuration is a grid-connected Solar PV-Gasoline system with a least cost ofenergy (COE) at ₦93.83/kWh and 6.7% renewable energy fraction.
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Enang, Wisdom, and Chris Bannister. "Robust proportional ECMS control of a parallel hybrid electric vehicle." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 231, no. 1 (October 1, 2016): 99–119. http://dx.doi.org/10.1177/0954407016659198.
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Improved fuel efficiency in hybrid electric vehicles requires a delicate balance between the internal combustion engine usage and battery energy, using a carefully designed energy management control algorithm. Numerous energy management strategies for hybrid electric vehicles have been proposed in literature, with many of these centered on the equivalent consumption minimisation strategy (ECMS) owing to its potential for online implementation. The key challenge with the equivalent consumption minimisation strategy lies in estimating or adapting the equivalence factor in real-time so that reasonable fuel savings are achieved without over-depleting the battery state of charge at the end of the defined driving cycle. To address the challenge, this paper proposes a novel state of charge feedback ECMS controller which simultaneously optimises and selects the adaption factors (proportional controller gain and initial equivalence factor) as single parameters which can be applied in real time, over any driving cycle. Unlike other existing state of charge feedback methods, this approach solves a conflicting multiple-objective optimisation control problem, thus ensuring that the obtained adaptation factors are optimised for robustness, charge sustenance and fuel reduction. The potential of the proposed approach was thoroughly explored over a number of legislative and real-world driving cycles with varying vehicle power requirements. The results showed that, whilst achieving fuel savings in the range of 8.40 −19.68% depending on the cycle, final battery state of charge can be optimally controlled to within ±5% of the target battery state of charge.
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Jonnagadla, Manasa. "Minimizing the Cost for Resource Allocation from Multiple Cloud Providers." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (November 30, 2021): 1611–18. http://dx.doi.org/10.22214/ijraset.2021.39058.
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Abstract: Cloud computing provides streamlined tools for exceptional business efficiency. Cloud service providers typically offer two types of plans: reserved and on-demand. Restricted policies provide low-cost long-term contracting, while order contracts are expensive and ready for short periods. Cloud resources must be delivered wisely to meet current customer demands. Many current works rely on low-cost resource-reserved strategies, which may be under- or over-provisioning. Resource allocation has become a difficult issue due to unfairness causing high availability costs and cloud demand variability. That article suggests a hybrid approach to allocating cloud services to complex customer orders. The strategy was built in two stages: accommodation stages and a flexible structure. By treating each step as an optimization problem, we can reduce the overall implementation cost while maintaining service quality. Due to the uncertain nature of cloud requests, we set up a stochastic Optimization-based approach. Our technique is used to assign individual cloud resources and the results show its effectiveness. Keywords: Cloud computing, Resource allocation, Demand
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Satapathy, Anshuman, Niranjan Nayak, and Tanmoy Parida. "Real-Time Power Quality Enhancement in a Hybrid Micro-Grid Using Nonlinear Autoregressive Neural Network." Energies 15, no. 23 (November 30, 2022): 9081. http://dx.doi.org/10.3390/en15239081.
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The extensive use of renewable energy sources (RESs) in energy sectors plays a vital role in meeting the present energy demand. The widespread utilization of allocated resources leads to multiple usages of converters for synchronization with the power grid, introducing poor power quality. The integration of distributed energy resources produces uncertainties which are reflected in the distribution system. The major power quality problems such as voltage sag/swell, voltage unbalancing, poor power factor, harmonics distortion (THD), and power transients appear during the transition of micro-grids (MGs). In this research, a single micro-grid is designed with PVs, wind generators, and fuel cells as distributed energy resources (DERs). A nonlinear auto regressive exogenous input neural network (NARX-NN) controller has been investigated in this micro-grid in order to maintain the above power quality issues within the specific standard range (IEEE/IEC standards). The performance of the NARX-NN controller is compared with PID and fuzzy-PID controllers. The single micro-grid is extended to design a three-phase large-scale realistic micro-grid structure to test the feasibility of the proposed controller. The realistic micro-grid is verified through addition of line-impedance, communication delay, demand response, and off-nominal situations. The proposed controller is also validated by simulating different test scenarios using MATLAB/Simulink and TMS320-based processor-in-loop (PIL) for real-time implementation.
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Srivastava, Sudiksha. "Generation of Hybrid Energy System (Solar-Wind) Supported with Battery Energy Storage." International Journal for Research in Applied Science and Engineering Technology 10, no. 9 (September 30, 2022): 1439–46. http://dx.doi.org/10.22214/ijraset.2022.46864.
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Abstract: The utilization of renewable energy is significantly important for the world because global energy consumption is increasing, while conventional energy sources are no longer sufficient to meet the energy demand, triggering energy crises. In recent years, the increasing prices of fossil fuels and concerns about the environmental consequences of greenhouse gas emissions have renewed the interest in the development of alternative energy resources. Renewable energy is now considered a more desirable source of fuel than nuclear power due to the absence of risk and disasters [1]. Considering that the major component of greenhouse gases is carbon dioxide, there is a global concern about reducing carbon emissions. In this regard, different policies could be applied to reducing carbon emissions, such as enhancing renewable energy deployment and encouraging technological innovations. There are various of renewable energy sources such as Solar, biomass, wind, hydrogen, fuel cell, nanocomposite, and supercapacitor. Each of the energy sources are suitable for specific geographical locations and can suits from region to region. However, variation in solar radiation and wind speed caused by climate and weather conditions restricts the stable operation of renewable energy systems, therefore, causing the output to fluctuate. A hybrid renewable energy generation system can be highly efficient by combining multiple renewable energy sources and is regarded as a promising solution to overcome from this issue. Hybrid solar systems are the systems combining two renewable sources of energy, like solar and wind. Then, energy is generated through solar on sunny days and when there is limited sunshine but there is wind, energy can be generated through it. The study aims to focus on generation of hybrid solar-wind power plant with the optimal contribution of renewable energy resources supported by battery energy storage technology. The motivating factor behind the hybrid solar–wind power system design is the fact that both solar and wind power exhibit complementary power profiles. Advantageous combination of solar and wind with optimal ratio will lead to clear benefits for hybrid solar-wind power plants such as smoothing of intermittent power, higher reliability, and availability. However, the potential challenges for its integration into power grids cannot be neglected. A potential solution is to utilise one of the energy storage technologies, though all of them are still very expensive for such applications, especially at large scale. Therefore, optimal capacity calculations for energy storage system are also vital to realise full benefits. Currently, battery energy storage technology is considered as one of the most promising choices for renewable power applications. However, solar-wind power technology are most suitable for off-grid services, serving the remote are without having to build or extend expensive and complicated grid infrastructure. Therefor standalone system using renewable energy sources have become a preferred option. Hence hybrid energy systems are an ideal solution since they can offer substantial improvements in performance and cost reduction and can be tailored to varying end user requirements
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Al Abri, Abdullah, Abdullah Al Kaaf, Musaab Allouyahi, Ali Al Wahaibi, Razzaqul Ahshan, Rashid S. Al Abri, and Ahmed Al Abri. "Techno-Economic and Environmental Analysis of Renewable Mix Hybrid Energy System for Sustainable Electrification of Al-Dhafrat Rural Area in Oman." Energies 16, no. 1 (December 27, 2022): 288. http://dx.doi.org/10.3390/en16010288.
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Affordable and clean energy for any rural community is crucial for the sustainable development of the community and the nation at large. The utilization of diesel-based power generation is one of the barriers to the sustainable development of these communities. Such generations require fuel that has a volatile market price and emits massive greenhouse gas emissions. This paper presents the design, modeling, and simulation of a hybrid power system for a rural area in the Sultanate of Oman that aims to reduce daily consumption of diesel fuel and greenhouse gas emissions. Hybrid Optimization of Multiple Energy Resources (HOMER) is utilized to model multiple energy mix hybrid systems and to propose the best optimal energy mix system for a selected community. In addition, Electrical Transient Analyzer Program (ETAP) software is employed to assess hybrid system operational performances, such as bus voltage profiles and active and reactive power losses. This study revealed that the PV–wind–diesel system is the optimal energy mix hybrid microgrid for the Al-Dhafrat rural area in Oman, with a net present cost of USD 14.09 million. Compared to the currently operating diesel-based system, the deployment of this microgrid can reduce the levelized cost of energy, diesel fuel consumption, and greenhouse gas emissions per year by 54.56%, 70.44%, and 70.40%, respectively. This study confirms that the Sultanate of Oman has a substantial opportunity to install a hybrid microgrid system for rural diesel-based communities to achieve sustainable development in the country.
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Karmaker, Ashish Kumar, Md Alamgir Hossain, Nallapaneni Manoj Kumar, Vishnupriyan Jagadeesan, Arunkumar Jayakumar, and Biplob Ray. "Analysis of Using Biogas Resources for Electric Vehicle Charging in Bangladesh: A Techno-Economic-Environmental Perspective." Sustainability 12, no. 7 (March 25, 2020): 2579. http://dx.doi.org/10.3390/su12072579.
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The growing popularity of electric vehicles (EV) is creating an increasing burden on the power grid in Bangladesh due to massive energy consumption. Due to this uptake of variable energy consumption, environmental concerns, and scarcity of energy lead to investigate alternative energy resources that are readily available and environment friendly. Bangladesh has enormous potential in the field of renewable resources, such as biogas and biomass. Therefore, this paper proposes a design of a 20 kW electric vehicle charging station (EVCS) using biogas resources. A comprehensive viability analysis is also presented for the proposed EVCS from technological, economic, and environmental viewpoints using the HOMER (Hybrid Optimization of Multiple Energy Resources) model. The viability result shows that with the capacity of 15–20 EVs per day, the proposed EVCS will save monthly $16.31 and $29.46, respectively, for easy bike and auto-rickshaw type electric vehicles in Bangladesh compare to grid electricity charging. Furthermore, the proposed charging station can reduce 65.61% of CO2 emissions than a grid-based charging station.
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Dodo, Usman Alhaji, Evans Chinemezu Ashigwuike, Najashi Barau Gafai, Emmanuel Majiyebo Eronu, Abdullahi Yusuf Sada, and Mustapha Alhaji Dodo. "Optimization of an Autonomous Hybrid Power System for an Academic Institution." European Journal of Engineering Research and Science 5, no. 10 (October 8, 2020): 1160–67. http://dx.doi.org/10.24018/ejers.2020.5.10.2157.
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The epileptic power supply in Nigeria is enormously impeding universities’ administrative, academic, and research activities. The diesel generators on which most of these institutions rely as alternative power sources during grid failures are not viable solutions as the grid outage is incessant and the duration usually lasts for hours, at times for days. The effects of these are high running costs and increased environmental pollution. If normal activities in the universities are to continue unhindered and to reduce the health risks associated with the fossil-based generators, there is the need to explore other alternatives such as utilizing the environmentally-friendly, free and abundant renewable resources to meet their electricity demands. The present study uses Hybrid Optimization of Multiple Energy Resources (HOMER) to evaluate two different configurations of a stand-alone diesel generator (DG) system and a hybrid solar photovoltaic(PV)-diesel generator(DG)-battery energy storage (BES) system for sustainable power supply to the Baze University Abuja, Nigeria. The net present cost and levelized cost of energy, operating cost, and carbon dioxide emission of the hybrid PV-DG-BES system are lower by 50%, 30.93%, and 90% respectively when compared to the stand-alone DG system. Therefore, a hybrid solar PV-DG-BES system is a suitable technology to sustainably power the University.
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Dodo, Usman Alhaji, Evans Chinemezu Ashigwuike, Najashi Barau Gafai, Emmanuel Majiyebo Eronu, Abdullahi Yusuf Sada, and Mustapha Alhaji Dodo. "Optimization of an Autonomous Hybrid Power System for an Academic Institution." European Journal of Engineering and Technology Research 5, no. 10 (October 8, 2020): 1160–67. http://dx.doi.org/10.24018/ejeng.2020.5.10.2157.
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The epileptic power supply in Nigeria is enormously impeding universities’ administrative, academic, and research activities. The diesel generators on which most of these institutions rely as alternative power sources during grid failures are not viable solutions as the grid outage is incessant and the duration usually lasts for hours, at times for days. The effects of these are high running costs and increased environmental pollution. If normal activities in the universities are to continue unhindered and to reduce the health risks associated with the fossil-based generators, there is the need to explore other alternatives such as utilizing the environmentally-friendly, free and abundant renewable resources to meet their electricity demands. The present study uses Hybrid Optimization of Multiple Energy Resources (HOMER) to evaluate two different configurations of a stand-alone diesel generator (DG) system and a hybrid solar photovoltaic(PV)-diesel generator(DG)-battery energy storage (BES) system for sustainable power supply to the Baze University Abuja, Nigeria. The net present cost and levelized cost of energy, operating cost, and carbon dioxide emission of the hybrid PV-DG-BES system are lower by 50%, 30.93%, and 90% respectively when compared to the stand-alone DG system. Therefore, a hybrid solar PV-DG-BES system is a suitable technology to sustainably power the University.
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Subramaniam, Umashankar, Swaminathan Ganesan, Mahajan Sagar Bhaskar, Sanjeevikumar Padmanaban, Frede Blaabjerg, and Dhafer J. Almakhles. "Investigations of AC Microgrid Energy Management Systems Using Distributed Energy Resources and Plug-in Electric Vehicles." Energies 12, no. 14 (July 23, 2019): 2834. http://dx.doi.org/10.3390/en12142834.
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The world has witnessed a rapid transformation in the field of electrical generation, transmission and distribution. We have been constantly developing and upgrading our technology to make the system more economically efficient. Currently, the industry faces an acute shortage of energy resources due to overconsumption by industries worldwide. This has compelled experts to look for alternatives to fossil fuels and other conventional sources of energy to produce energy in a more sustainable manner. The microgrid concept has gained popularity over the years and has become a common sight all over the world because of the ability of a microgrid to provide power to a localized section without being dependent on conventional resources. This paper focuses on development of such an AC hybrid microgrid, which receives power from distributed energy resources (DERs) such as a PV array alongside a battery storage system, and also uses an emergency diesel generator system and an online uninterruptible power supply (UPS) system to provide power to predefined loads under different conditions. This paper also addresses on the power flow to the loads under two main modes of operation—on grid and off grid—and investigates the microgrid in different states and sub-states. The final objective is to design an efficient microgrid model such that it can sustain the multiple loads simultaneously under all operating conditions.
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Tan, Shengmin, Xu Wang, and Chuanwen Jiang. "Optimal Scheduling of Hydro–PV–Wind Hybrid System Considering CHP and BESS Coordination." Applied Sciences 9, no. 5 (March 2, 2019): 892. http://dx.doi.org/10.3390/app9050892.
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Coordination of a hydropower, combined heat and power (CHP), and battery energy storage system (BESS) with multiple renewable energy sources (RES) can effectively reduce the adverse effects of large-scale renewable energy integration in power systems. This paper proposes a concept of a renewable-based hybrid energy system and puts forward an optimal scheduling model of this system, taking into account the cost of operation and risk. An optimization method is proposed based on Latin hypercube sampling, scene reduction, and piecewise linearization. Firstly, a large number of samples were generated with the Latin hypercube sampling method according to the uncertainties, including the renewable resources availability, the load demand, and the risk aversion coefficients, and the generated samples were reduced with a scene reduction method. Secondly, the piecewise linearization method was applied to convert nonlinear constraints into linear to obtain the best results of each scene. Finally, the performance of the proposed model and method was evaluated based on case studies with real-life data. Results showed that the renewable-based hybrid system can not only reduce the intermittent and volatility of renewable resources but also ensure the smooth of tie-line power as much as possible. The proposed model and method are universal, feasible, and effective.
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Liu, Xiaokai, Fangmin Xu, Ye Xiao, Xiaoming Zhou, Zhao Li, Chenglin Zhao, and Min Zhang. "Multiple Local-Edge-Cloud Collaboration Strategies in Industrial Internet of Things: A Hybrid Genetic-Based Approach." Mathematical Problems in Engineering 2022 (September 24, 2022): 1–12. http://dx.doi.org/10.1155/2022/1486580.
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To cope with the challenge of successful edge offloading brought by the mobility of mobile devices in intelligent factories, this paper studies the optimization problem of the edge offloading strategy of mobile devices based on mobility. Considering the decision task flow executed by priority, the unique offloading mode of a single task, the communication range of the edge server, and the delay constraint of the offloading of a single task, appropriate computing resources are selected according to the real-time location of the mobile device to offload the computing task. Based on the edge computing architecture of an intelligent factory, this paper puts forward five different computation offloading methods. From a global perspective, the energy consumption and delay of tasks offloading in local, edge, cloud center, local-edge collaboration, and local-edge-cloud collaboration are considered. In this paper, the algorithm based on the genetic algorithm and particle swarm optimization is used to design and obtain the decision task flow offloading strategy with the lowest energy consumption and delay. Simulation results show that the proposed algorithm can reduce the computation offloading energy consumption and delay of mobile devices.
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Ali, Muhammad Sharjeel, Syed Umaid Ali, Saeed Mian Qaisar, Asad Waqar, Faheem Haroon, and Ahmad Alzahrani. "Techno-Economic Analysis of Hybrid Renewable Energy-Based Electricity Supply to Gwadar, Pakistan." Sustainability 14, no. 23 (December 6, 2022): 16281. http://dx.doi.org/10.3390/su142316281.
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Gwadar is essential to Pakistan’s financial stability. Being the third deep-water port in Pakistan, it plays a significant role in trade between the Gulf States, Africa, UAE, and CARs. The load shedding of 12–16 h in Gwadar is the most concerning issue due to the non-availability of a utility grid, which is why the Pakistan imports 70 MW of electricity from Iran to fulfill Gwadar’s electricity needs. Gwadar has renewable energy resources that can be utilized for electricity generation. However, wind and solar systems were only installed for limited residential areas. Considering this scenario, a technological and economic analysis was performed using the Hybrid Optimization Model for Multiple Energy Resources (HOMER) software. Three models were considered in this study. Model 1 consisted of photovoltaic (PV) cells, wind turbines, converters, and batteries. Model 2 consisted of PV cells, wind turbines, converters, and a grid. Model 3 consisted of PV cells, wind turbines, converters, and diesel generators. The annual energy generated by Model 1, Model 2, and Model 3 was respectively 57.37 GWh, 81.5 GWh, and 30.4 GWh. The Levelized Cost of Electricity (LCOE) for Model 1, Model 2, and Model 3 was respectively USD 0.401/kWh, USD 0.0347/kWh, and USD 0.184/kWh. The simple payback period of Model 1 was 6.70 years, the simple payback period of Model 2 was 7.77 years and the simple payback period of Model 3 was 4.98 years. Because Model 3 had the lowest Net Present Cost NPC, its payback period was also less than those of the other two. However, Model 2 had the lowest LCOE and its renewable fraction was 73.3%. These facts indicate that Model 2 is the optimal solution.
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Bourmada, Amal, and Azeddine Bilami. "Hybrid Energy Efficient Protocol with Service Differentiation for QoS Provisions in Multi-Hop WSNs." International Journal of Embedded and Real-Time Communication Systems 6, no. 2 (April 2015): 27–47. http://dx.doi.org/10.4018/ijertcs.2015040102.
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The growing demand of usage of wireless sensors networks (WSNs) in multiple types of applications such as environment monitoring or asset tracking makes the quality-of-service (QoS) a paramount topic in wireless sensors applications. In these applications, each sensor node may collect different types of data with different levels of importance involving a different treatment to meet QoS purpose. Consequently, a sensor network should be ready to spend more resources in transmitting packets that hold more important information. In this paper, the authors propose an enhanced protocol with differentiated services for WSNs called QoS-HEEP. The proposed protocol is an improvement of HEEP protocol while providing requested quality of service for high priority real time traffic, which is distinguished from the low priority and non-real time traffic. Thus, input traffic streams are served based on their priorities. Through simulations using NS Simulator; it is observed that the authors' proposal outperforms more than other protocols developed in the literature for QoS provisions in WSNs.
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Maroufmashat, Taqvi, Miragha, Fowler, and Elkamel. "Modeling and Optimization of Energy Hubs: A Comprehensive Review." Inventions 4, no. 3 (August 23, 2019): 50. http://dx.doi.org/10.3390/inventions4030050.
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: The concept of energy hubs has grown in prominence as a part of future energy systems, driven by the spread of Distributed Energy Resources (DERs) and the inception of the smart grid. This paper systematically reviews 200 articles about energy hubs, published from 2007 to 2017, and summarizes them based on their modeling approach, planning and operation, economic and environmental considerations, and energy hub applications. The common applications of energy hubs are considered, such as distributed energy resources, the consideration of Plug-in Hybrid Electric Vehicles (PHEVs), and the hydrogen economy. This paper examines modeling approaches towards energy hubs, including storage and its network models; it mentions some of the optimization strategies used to tackle the efficient operation and control of energy hubs. The novelty of this work lies in the classification of research papers related to energy hubs, the development of a generic framework for modeling these multiple energy flow carriers with storage and network considerations, and the provision of solution techniques in line with energy hub optimization.
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Akinyele, D. O., A. O. Amole, O. E. Oyadoyin, O. E. Olabode, I. K. Okakwu, and K. S. Abimbola. "Analysis of multi-distributed generation systems based on solar/biomass/natural gas/diesel energy resources for off-grid application." Nigerian Journal of Technology 41, no. 4 (November 3, 2022): 805–16. http://dx.doi.org/10.4314/njt.v41i4.18.
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This study presents the analysis of multi-distributed generation systems for 20 off-grid homes in Ogun State based on the techno-environmental analysis planning (TEAP) approach. The technical aspect includes the load, DG capacities, energy generation/year, and the unmet energy demand (UED. The paper considers and compares different energy configurations such as the PV-based DG, the hybrid DGs: PV/biogas, PV/biogas/natural gas, PV/biogas/diesel, PV/diesel, and the diesel-based DGs. The environmental aspect examines the emissions produced by the DGs compared to a diesel-based DG system. The paper also examines the effect of temperature on the performance of the PV system. The simulation is based on a total daily demand of 99.04 kWh/d, and the solar, ambient temperature and the biomass data in Hybrid Optimization of Multiple Energy Resources (HOMER) environment. The size of the PV-based DG obtained is 36.9 kW, which generates 54,565 kWh/yr without temperature effect. Result shows that this value reduced to 48,268 kWh/yr with temperature effect and the value of UED is 7.84 %. The biogas, natural gas and diesel generators have the same size of 13.2 kW. The hybrid DGs achieve a UED of 0% implying 100 % system availability. Results further demonstrate that the mentioned hybrid DGs have CO2 emissions that range between 2.21 and 15, 448 kg/yr, compared to a value of 40, 273 kg/yr obtained when the homes are entirely run on a diesel-based DG. The study can help to understand energy systems analysis.
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Dursun, Bahtiyar, and Ercan Aykut. "An investigation on wind/PV/fuel cell/battery hybrid renewable energy system for nursing home in Istanbul." Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 233, no. 5 (April 2019): 616–25. http://dx.doi.org/10.1177/0957650919840519.
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This paper presents a techno-economic analysis of hybrid renewable energy systems to supply the electrical load requirements of the nursing home located in Istanbul, Turkey. The standalone hybrid renewable energy systems (Photovoltaic (PV)/wind/fuel cell/electrolyzer, PV/fuel cell/electrolyzer, and wind/fuel cell/electrolyzer, etc.) considered in the analysis were comprised of different combinations of PV panels, fuel cells, and wind turbines supplemented with hydrogen storage. In this study, the Hybrid Optimization of Multiple Energy Resources (HOMER) software is used as the assessment tool to determine the optimal configuration of hybrid renewable energy systems taking total net present cost and cost of energy into consideration. As a result, it is determined that the optimal system configuration of standalone wind/PV/fuel cell/electrolyzer hybrid renewable energy systems with the lowest total net present cost consists of 30 kW PV panel, 20 kW wind turbine, 20 kW fuel cell, 20 kW power converter, 50 kW electrolyzer, 20 kW rectifier, and 100 kg hydrogen tank. Besides, the net present cost and cost of energy of the optimum configuration are calculated to be $607,298 and $1.306/kWh, respectively. The system is considered as completely renewable. When wind speed and solar radiation values increase, then the cost of energy decrease about $0.979/kWh.
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Antonio Barrozo Budes, Farid, Guillermo Valencia Ochoa, Luis Guillermo Obregon, Adriana Arango-Manrique, and José Ricardo Núñez Álvarez. "Energy, Economic, and Environmental Evaluation of a Proposed Solar-Wind Power On-grid System Using HOMER Pro®: A Case Study in Colombia." Energies 13, no. 7 (April 2, 2020): 1662. http://dx.doi.org/10.3390/en13071662.
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The electrical sector in the Caribbean region of Colombia is currently facing problems that affect its reliability. Many thermo-electric plants are required to fill the gap and ensure energy supply. This paper thus proposes a hybrid renewable energy generation plant that could supply a percentage of the total energy demand and reduce the environmental impact of conventional energy generation. The hybrid plant works with a photovoltaic (PV) system and wind turbine systems, connected in parallel with the grid to supply a renewable fraction of the total energy demand. The investigation was conducted in three steps: the first stage determined locations where the energy system was able to take advantage of renewable sources, the second identified a location that could work more efficiently from an economic perspective, and finally, the third step estimated the number of PV solar panels and wind turbines required to guarantee optimal functioning for this location using, as a main method of calculation, the software HOMER pro® for hybrid optimization with multiple energy resources. The proposed system is expected to not only limit environmental impacts but also decrease total costs of electric grid consumption from thermoelectric plants. The simulations helped identify Puerto Bolivar, Colombia, as the location where the hybrid plant made the best use of non-conventional resources of energy. However, Rancho Grande was found to offer the system more efficiency, while generating a considerable amount of energy at the lowest possible cost. An optimal combination was also obtained—441 PV arrays and 3 wind turbines, resulting in a net present cost (NPC) of $11.8 million and low CO2 production of 244.1 tons per year.
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Uwineza, Laetitia, Hyun-Goo Kim, Jan Kleissl, and Chang Ki Kim. "Technical Control and Optimal Dispatch Strategy for a Hybrid Energy System." Energies 15, no. 8 (April 8, 2022): 2744. http://dx.doi.org/10.3390/en15082744.
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Optimal dispatch is a major concern in the optimization of hybrid energy systems (HESs). Efficient and effective dispatch models that satisfy the load demand at the minimum net present cost (NPC) are crucial because of the high capital costs of renewable energy technologies. The dispatch algorithms native to hybrid optimization of multiple energy resources (HOMER) software, cycle-charging (CC) and load-following (LF), are powerful for modeling and optimizing HESs. In these control strategies, the decision to use fuel cell systems (FCs) or battery energy storage systems (BESs) at each time step is made based on the lowest cost choice. In addition, the simultaneous operation of a FC with a BES reduces the operating efficiency of the FC. These deficiencies can affect the optimal design of HESs. This study introduces a dispatch algorithm specifically designed to minimize the NPC by maximizing the usage of FCs over other components of HESs. The framework resolves the dispatch deficiencies of native HOMER dispatch algorithms. The MATLAB Version 2021a, Mathworks Inc., Natick, MA, USA Link feature in HOMER software was used to implement the proposed dispatch (PD) algorithm. The results show that the PD achieved cost savings of 4% compared to the CC and LF control dispatch strategies. Furthermore, FCs contributed approximately 23.7% of the total electricity production in the HES, which is more than that of CC (18.2%) and LF (18.6%). The developed model can be beneficial to engineers and stakeholders when optimizing HESs to achieve the minimum NPC and efficient energy management.