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Abstract
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Due to the random time-space distribution of electric vehicles (EVs), disordered charging management can easily lead to “peak plus peak” during peak load periods, which aggravates the risk of local voltage exceeding limit. A two-level active and reactive joint optimization model of active distribution network (ADN) with charging-swapping-storage integrated station (CSSIS) participation is established. The outer layer optimization, focusing on ADN level, emphasizes the overall active/reactive power output plan of CSSIS to improve the safety and economics of ADN operation; The inner layer optimization, focusing on the specific output plan within CSSIS, achieves energy complementary for each station of CSSIS, suppresses EV load fluctuations, reduces the cost of electricity for EVs and realizes cascade utilization of used batteries. In order to reduce the regulation pressure of dynamic power sources in real-time optimization, a robust optimization method is adopted in day-ahead optimization to improve the system ability dealing with uncertain factors and realize the "friendliness" of CSSIS access to ADN
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