Aggregating and Scheduling Flexibility of Multiple Flexible Resources for Distribution Network: A Feasible Region-Embedded EMPC Method
Li Na, Song Gao, ZENG Xiaoyu, Xuri Chen · 2024
In order to achieve the ambitious goal of carbon neutrality by mid-century, the penetration of renewable energy increased rapidly in recent years, which has led to an increased need for flexibility in power system. Diverse flexible resources dispersed throughout the grid have the potential to complement power system flexibility. Therefore, we propose a feasible region-embedded MPC method. Firstly, we develop the virtual battery models of various flexible resources, and generate the scheduling feasible region of flexible resource individuals. Secondly, the scheduling feasible regions of resources are deflated to the form of zonotopes with simple M-Sum form by the principle of maximum similarity, and the scheduling feasible regions of aggregations are obtained by M-Sum. Thirdly, a model predictive control algorithm for grid peaking requirements is proposed to reasonably utilize the scheduling flexibility of aggregations to participate in grid peaking service while meeting the basic needs of users. Finally, we design a case study to verify the performance of the proposed method. The results show that the proposed method can effectively mobilize the regulation potential of distributed flexible resources and provide peak-shaving services for the grid with maximum proceed.