A coordinated optimal scheduling model with Nash bargaining for shared energy storage and Multi-microgrids based on Two-layer ADMM. (March 2023) - Xu, Yangbing; Ye, Shengxuan; Qin, Zhiqi; Lin, Xin; Huangfu, Jiangtao; Zhou, Weihua
Abstract: The environment has been gradually broken due to the extensive use of fossil energy. Advocating for renewable energy and improving energy utilization have become essential cornerstones for the energy revolution. However, renewable energy generation's intense volatility and instability bring challenges to management control's energy scheduling. To this end, we propose a coordinated optimal scheduling model for a shared energy storage system (SESS) and multi-microgrids (MGs), where SESS stores excess energy and releases it when needed. However, the benefit of SESS or MGs may be lost to minimize total cost. Therefore, Nash bargaining redistributes the benefits between SESS and MGs to maintain long-term cooperation. In addition, SESS and MGs belong to different operators. It is vital to protect data privacy in the model. To this end, a two-layer alternating direction multipliers algorithm (ADMM) is designed to solve the proposed model due to its inherent data privacy mechanism. Finally, we compare the proposed model with the other two models through simulation experiments. The results prove that a) the proposed model is both valid and efficient; b) the designed two-layer ADMM is an effective algorithm to solve the energy scheduling problem; c) this study provides a solid basis for building a sustainable city.