- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
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| Citation: | JIANG Xiaofeng, PAN Pengyu, ZHOU Bo, JIA Shicheng, TANG Chun, XU Yunyang, WEI Wei, YANG Jianwei. Two-Stage Optimization Dispatching Strategy for Distribution Network Considering Dispatchable Potential of Charging Station[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20240420
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To address the challenges posed to the safe and economic operation of distribution networks by the large-scale integration of electric vehicles (EVs) and wind and solar power, as well as the issue of low accuracy in traditional single timescale optimization dispatching methods, a multi-timescale coordinated distribution network optimization dispatching strategy that considered the dispatchable potential of charging stations was proposed. Firstly, an assessment method for the dispatchable capacity of charging stations based on the Minkowski sum was proposed. By aggregating EV clusters within the stations and treating them as generalized energy storage systems, the real-time dispatchable potential of each station was accurately calculated. Subsequently, a day-ahead and intra-day two-stage optimization dispatching strategy for the distribution network based on model predictive control was introduced. In the day-ahead dispatching stage, with the objective of minimizing the daily operating cost of the distribution network, the electricity purchase and sales plans, along with the output schedules of controllable distributed generators and energy storage systems, were coordinately optimized to achieve optimal allocation of global resources. In the intra-day dispatching stage, by leveraging rolling optimization and feedback correction mechanisms based on the day-ahead plan and real-time states, the day-ahead output schedules of controllable devices were dynamically corrected to cope with intra-day fluctuations in wind power, photovoltaic power, and load, ensuring the stable operation of system state variables under disturbances. Finally, the performance of the proposed strategy in fulfilling day-ahead dispatching instructions under uncertain disturbances was analyzed. Simulation results demonstrate that by exploiting the dispatchable potential of charging stations, the proposed strategy reduces the daily operating cost of the distribution network by 10.86% compared to scenarios without V2G capability. Furthermore, it achieves an additional 13.66% cost reduction compared to day-ahead optimization strategies, while limiting the deviation from the day-ahead tie-line power to merely 1.77%. This approach realizes distributed optimization dispatching for the distribution network, significantly enhancing its economic efficiency and robustness amidst uncertainties.
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