Optimal design of a hybrid solar–wind-battery system using the minimization of the annualized cost system and the minimization of the loss of power supply probability (LPSP)

Bilal, Boudy; Sabourin, Vincent; Ndiaye, P. D.; Kébé, Cheikh Mouhamed Fadel; Ndongo, Mamoudou

doi:10.1016/j.renene.2010.03.004

Cited by 193 publications

(27 citation statements)

References 6 publications

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“…In last decade, GA had been widely applied to optimize and evaluate energy system for different practical objectives. Bilal utilized GA to design hybrid solar-wind-battery systems that can achieve the customers' required Loss of Power Supply Probability (LPSP) with a minimum annual economic cost [18]. Mohamed introduced a three-phase multi-objective optimization approach (PR_GA_RF) to minimize the environmental impacts (CO 2 emission) and economic cost in dwelling building.…”

Section: Optimization Algorithm: Genetic Algorithm (Ga)mentioning

confidence: 99%

Energy Quality Management for a Micro Energy Network Integrated with Renewables in a Tourist Area: A Chinese Case Study

2018

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For a tourist area (TA), energy utilization is mostly concentrated in certain period of time. Therefore, the peak load is several times more than the average load. A Micro Energy Network Integrated with Renewables (MENR) system is considered as a potential solution to mitigate this problem. To design an appropriate MENR system, a multi-objective energy quality management (EQM) method based on the Genetic Algorithm is proposed. Here, EQM aims at reducing the primary energy consumption and optimizing the energy shares of various renewables in a MENR system. In addition to minimizing life-cycle costs and maximizing the exergy efficiency of a MENR system, the issue of system reliability is addressed. Then, a case study is presented, where the EQM method is applied to a TA located in Dali, China. Three possible reference MENR scenarios are analyzed. After confirming the reference scenarios, advanced MENR scenarios with improved system reliability are discussed. The rest of the work is dedicated to investigating the effects of various energy storage systems (ESSs) parameters and the number of electric vehicles (EVs) on MENR scenarios. The results suggest that there are significant differences between various MENR scenarios depending on the number of EVs and the investment reduction of ESSs.

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Section: Optimization Algorithm: Genetic Algorithm (Ga)mentioning

confidence: 99%

Energy Quality Management for a Micro Energy Network Integrated with Renewables in a Tourist Area: A Chinese Case Study

2018

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“…7,11 As aforementioned, variations in the output of solar and wind RESs can be reduced through their hybridization which can in turn significantly decrease required ESS capacities. 3,12,13 Moreover, hybridization and the integration of ESSs can enable RES-based microgrids that can alternately connect (on-grid) and disconnect (islanded) from the grid based on the changing states of the micro-grid and main grid. 14 The economic feasibility of the a RES is strongly affected by the sizing of the system's components 3,12,15 including the sizing of the ESS.…”

Section: Introductionmentioning

confidence: 99%

“…3,12,13 Moreover, hybridization and the integration of ESSs can enable RES-based microgrids that can alternately connect (on-grid) and disconnect (islanded) from the grid based on the changing states of the micro-grid and main grid. 14 The economic feasibility of the a RES is strongly affected by the sizing of the system's components 3,12,15 including the sizing of the ESS. 9 Therefore, optimal component sizing of RESs with ESSs is critical to ensure the system's technical and economic feasibility.…”

Section: Introductionmentioning

confidence: 99%

An investigation of optimum PV and wind energy system capacities for alternate short and long‐term energy storage sizing methodologies

2018

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Summary The goal of this study is to find the optimal sizes of renewable energy systems (RES) based on photovoltaic (PV) and/or wind systems for three energy storage system (ESS) scenarios in a micro‐grid; (1) with pumped hydro storage (PHS) as a long‐term ESS, (2) with batteries as a short‐term ESS, and (3) without ESS. The PV and wind sizes are optimally determined to accomplish the maximum annual RES fraction (FRES) with electricity cost lower than or equal to the utility tariff. Furthermore, the effect of the use of battery and PHS on the electricity cost and FRES are studied. A university campus on a Mediterranean island is selected as a case study. The results show that PV‐wind hybrid system of 8 MW wind and 4.2 MW PV with 89.5 MWh PHS has the highest FRES of 88.0%, and the highest demand supply fraction as 42.6%. Moreover, the results indicate that the economic and technical parameters of RESs are affected significantly by the use of ESSs depending on the type and the capacity of both the RES and the ESS.

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“…In another research, Ould Bilal et al . carried out an optimal sizing of an HRES including a solar–wind–battery system for the Potou site in the north coast of Senegal. They used a MOGA with two objectives: the minimization of the ACS and the minimization of the loss of power supply probability.…”

Section: Introductionmentioning

confidence: 99%

“…For this task, differential evolution algorithm or fuzzy techniques have been used to find the best combination of the components and control strategies for the HRES. In another research, Ould Bilal et al [25] carried out an optimal sizing of an HRES including a solar-wind-battery system for the Potou site in the north coast of Senegal. They used a MOGA with two objectives: the minimization of the ACS and the minimization of the loss of power supply probability.…”

Section: Introductionmentioning

confidence: 99%

A dynamic MOPSO algorithm for multiobjective optimal design of hybrid renewable energy systems

Sharafi

ElMekkawy

2014

Int. J. Energy Res.

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SUMMARY In this paper, a dynamic multiobjective particle swarm optimization (DMOPSO) method is presented for the optimal design of hybrid renewable energy systems (HRESs). The main goal of the design is to minimize simultaneously the total net present cost (NPC) of the system, unmet load, and fuel emission. A DMOPSO‐simulation based approach has been used to approximate a worthy Pareto front (PF) to help decision makers in selecting an optimal configuration for an HRES. The proposed method is examined for a case study including wind turbines, photovoltaic (PV) panels, diesel generators, batteries, fuel cells, electrolyzer, and hydrogen tanks. Well‐known metrics are used to evaluate the generated PF. The average spacing and diversification metrics obtained by the proposed approach are 1386 and 4656, respectively. Additionally, the set coverage metric value shows that at least 67% of Pareto solutions obtained by DMOPSO dominate the solutions resulted by other reported algorithms. By using a sensitivity analysis for the case study, it is found that if the PV panel and wind turbine capital cost are decreased by 50%, the total NPC of the system would be decreased by 18.8 and 3.7%, respectively. Copyright © 2014 John Wiley & Sons, Ltd.

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Optimal design of a hybrid solar–wind-battery system using the minimization of the annualized cost system and the minimization of the loss of power supply probability (LPSP)

Cited by 193 publications

References 6 publications

Energy Quality Management for a Micro Energy Network Integrated with Renewables in a Tourist Area: A Chinese Case Study

Energy Quality Management for a Micro Energy Network Integrated with Renewables in a Tourist Area: A Chinese Case Study

An investigation of optimum PV and wind energy system capacities for alternate short and long‐term energy storage sizing methodologies

A dynamic MOPSO algorithm for multiobjective optimal design of hybrid renewable energy systems

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