Multiobjective Optimization of a Hybrid PV/Wind/Battery/Diesel Generator System Integrated in Microgrid: A Case Study in Djelfa, Algeria

Zakaria Belboul, Belgacem Toual, Abdellah Kouzou, Lakhdar Mokrani, Abderrahman Bensalem, Ralph Kennel and Mohamed Abdelrahem
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Zakaria Belboul: Laboratory of Applied Automation and Industrial Diagnostics (LAADI), Faculty of Science and Technology, Ziane Achour University, Djelfa 17000, Algeria
Belgacem Toual: Laboratory of Applied Automation and Industrial Diagnostics (LAADI), Faculty of Science and Technology, Ziane Achour University, Djelfa 17000, Algeria
Abdellah Kouzou: Laboratory of Applied Automation and Industrial Diagnostics (LAADI), Faculty of Science and Technology, Ziane Achour University, Djelfa 17000, Algeria
Lakhdar Mokrani: LACoSERE Laboratory, Department of Electrical Engineering, Faculty of Technology, University Amar Telidji of Laghouat, Laghouat 03000, Algeria
Abderrahman Bensalem: Laboratory of Applied Automation and Industrial Diagnostics (LAADI), Faculty of Science and Technology, Ziane Achour University, Djelfa 17000, Algeria
Ralph Kennel: Institute for High-Power Converter Systems (HLU), Technical University of Munich (TUM), 80333 Munich, Germany
Mohamed Abdelrahem: Institute for High-Power Converter Systems (HLU), Technical University of Munich (TUM), 80333 Munich, Germany

Energies, 2022, vol. 15, issue 10, 1-30

Abstract: Hybrid Renewable Energy Sources (HRES) integrated into a microgrid (MG) are a cost-effective and convenient solution to supply energy to off-grid and rural areas in developing countries. This research paper focuses on the optimization of an HRES connected to a stand-alone microgrid system consisting of photovoltaics (PV), wind turbines (WT), batteries (BT), diesel generators (DG), and inverters to meet the energy demand of fifteen residential housing units in the city of Djelfa, Algeria. In this context, the multiobjective salp swarm algorithm (MOSSA), which is among the latest nature-inspired metaheuristic algorithms recently introduced for hybrid microgrid system (HMS) optimization, has been proposed in this paper for solving the optimization of an isolated HRES. The proposed multiobjective optimization problem takes into account the cost of energy (COE) and loss of power supply probability (LPSP) as objective functions. The proposed approach is applied to determine three design variables, which are the nominal power of photovoltaic, the number of wind turbines, and the number of battery autonomy days considering higher reliability and minimum COE. In order to perform the optimum size of HMG, MOSSA is combined with a rule-based energy management strategy (EMS). The role of EMS is the coordination of the energy flow between different system components. The effectiveness of using MOSSA in addressing the optimization issue is investigated by comparing its performance with that of the multiobjective dragonfly algorithm (MODA), multiobjective grasshopper optimization algorithm (MOGOA), and multiobjective ant lion optimizer (MOALO). The MATLAB environment is used to simulate HMS. Simulation results confirm that MOSSA achieves the optimum system size as it contributed 0.255 USD/kW h of COE and LPSP of 27.079% compared to MODA, MOGOA, and MOALO. In addition, the optimization results obtained using the proposed method provided a set of design solutions for the HMS, which will help designers select the optimal solution for the HMS.

Keywords: multiobjective salp swarm algorithm; solar energy; microgrid; energy management strategy; batteries; wind; Djelfa (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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