TY - JOUR
T1 - Optimal control and implementation of energy management strategy for a DC microgrid
AU - Ferahtia, Seydali
AU - Djeroui, Ali
AU - Rezk, Hegazy
AU - Houari, Azeddine
AU - Zeghlache, Samir
AU - Machmoum, Mohamed
N1 - Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2022/1/1
Y1 - 2022/1/1
N2 - 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.
AB - 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.
KW - Battery
KW - DC microgrid
KW - Energy management system (EMS)
KW - Fuel cell
KW - Particle swarm optimization (PSO)
KW - Salp swarm algorithm (SSA)
UR - http://www.scopus.com/inward/record.url?scp=85114183114&partnerID=8YFLogxK
U2 - 10.1016/j.energy.2021.121777
DO - 10.1016/j.energy.2021.121777
M3 - Article
AN - SCOPUS:85114183114
SN - 0360-5442
VL - 238
JO - Energy
JF - Energy
M1 - 121777
ER -