Optimal control and implementation of energy management strategy for a DC microgrid

• Published in: Energy (Oxford) Vol. 238; p. 121777
• Main Authors: Ferahtia, Seydali, Djeroui, Ali, Rezk, Hegazy, Houari, Azeddine, Zeghlache, Samir, Machmoum, Mohamed
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.01.2022; Elsevier BV; Elsevier
• Subjects: Algorithms; batteries; Battery; Commercial buildings; Converters; DC microgrid; Distributed generation; Efficiency; Electric power systems; energy; Energy management; Energy management system (EMS); Energy storage; energy use and consumption; Engineering Sciences; Fuel cell; Fuel cells; Fuel consumption; Optimal control; Particle swarm optimization (PSO); Photovoltaic cells; Photovoltaics; Power consumption; Power management; Power sources; Salp swarm algorithm (SSA); State machines; swarms; Energy management system (EMS); DC microgrid; Particle swarm optimization (PSO); Fuel cell; Salp swarm algorithm (SSA); Battery
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2021.121777

This paper proposes an optimal energy management strategy (EMS) for DC microgrid. The studied system presents a commercial building power system that combines a photovoltaic array (PV), fuel cell (FC), a battery storage system and a bidirectional DC/AC grid converter. The integration of multiple power sources like renewables leads to techno-economical challenges including power quality, stability, fuel consumption, and efficiency. The proposed EMS is based on the salp swarm algorithm (SSA). This algorithm has been implemented because of considerable advantages such as its convergence properties and its reduced computing complexity. The step-by-step design of the proposed method is detailed. Then HIL tests are performed to validate the proposed EMS performances. The performance of the proposed EMS is compared with the state machine control strategy (SMC) in terms of system efficiency and fuel consumption where the obtained results prove the superiority of the proposed EMS (5.2 % fuel saving). Regarding the power quality, the proposed EMS is compared with EMS based PSO to investigate the optimizer influence, the obtained results confirm the ability of the proposed EMS to provide a superior power quality. Hence, the proposed EMS responds to the power systems challenges including power quality, fuel-saving and efficiency. •A DC microgrid based commercial building power system.•An optimized management strategy based salp swarm algorithm.•A comparative study with a state machine strategy.•The proposed EMS′ performance has been confirmed using processing in the loop (PIL).•The performance has been improved on both efficiency (72.18 %) and fuel saving (5.2 %).