An optimal energy management strategy with subsection bi-objective optimization dynamic programming for photovoltaic/battery/hydrogen hybrid energy system

• Published in: International journal of hydrogen energy 2023-01, Vol.48 (8), p.3154-3170
• Main Authors: Huangfu, Yigeng, Tian, Chongyang, Zhuo, Shengrong, Xu, Liangcai, Li, Peng, Quan, Sheng, Zhang, Yonghui, Ma, Rui
• Format: Article
• Language: English
• Subjects: Dynamic programming; Energy management; Fuel economy; Stand-alone microgrid; Subsection bi-objective optimization
• ISSN: 0360-3199; 1879-3487
• DOI: 10.1016/j.ijhydene.2022.10.133

Nowadays, the scheme of a stand-alone microgrid utilizing renewable energy is regarded as an effective approach to guarantee the power supply of an off-grid system. However, the intermittent nature of renewables brings new challenges to the determination of the optimal operation point for a hybrid energy system (HES). To address this issue, this paper proposes a subsection bi-objective optimization dynamic programming strategy for the HES consisting of photovoltaic, fuel cell, electrolyzer, hydrogen storage system, and battery bank. Within the proposed strategy, reasonable rule-based judgment is introduced to reduce the complexity of system control. Moreover, dynamic programming is selected to obtain the global optimal power distribution scheme. Meanwhile, a multi-objective genetic algorithm strategy is designed for comparative analysis. The results in two typical cases indicate the proposed strategy can improve photovoltaic utilization by 0.95% and 0.0003%, and fuel economy by nearly 50%. [Display omitted] •The hybrid energy system is modeled to clarify the operation mechanism.•Subsection bi-objective optimization dynamic programming is proposed.•Rule-based judgment is introduced to reduce the complexity of the optimization.•Two-staged optimization is implemented to improve fuel economy and utilization.