计及电动汽车参与多元需求响应的微电网多时间尺度优化调度模型

Multi-Time-Scale Optimization Scheduling Model of Microgrid with Electric Vehicles Participating in Multiple Demand Response

为深入挖掘电动汽车的可调度潜力,缓解含高比例新能源微电网的供能压力,结合多元需求响应技术,提出一种考虑电动汽车资源参与的微电网多时间尺度优化调度模型。在日前调度阶段,一部分电动汽车资源与价格型需求响应技术相结合,以用户的综合满意度为目标进行优化。微电网基于价格型电动汽车资源的调度计划,以经济低碳成本最低与灵活性满足度最大为目标进行优化,确定各侧可调资源的调度安排。在日内调度阶段,另一部分电动汽车资源与激励型需求响应技术相结合。微电网能量管理中心作为领导者,以运营成本最小为目标,激励型电动汽车群作为跟随者,以用电成本最小为目标,构建微电网日内主从博弈模型进行滚动优化,双方基于补贴价格与用能策略进行博弈。最后,基于某微电网场景进行仿真验证,结果表明所提模型能够降低用户用电成本,减少负荷曲线的峰谷差,实现新能源的全消纳。

To exploit the schedulable potential of electric vehicles(EVs)efficiently and relieve the energy supply pressure of microgrids with a high proportion of new energy sources,a multi-time-scale optimization scheduling model of the microgrid is proposed,considering the participation of EV resources combined with the multi-demand response technology.In the day-ahead scheduling stage,some EV resources are combined with the price-based demand response technology to optimize comprehensive user satisfaction.Based on the scheduling plan of the EV resources based on price,the microgrid is optimized focusing on minimizing economic cost,ensuring low-carbon expenditure,and maximizing flexibility satisfaction,and the scheduling arrangement of the adjustable resources on each side is determined.In the intra-day scheduling phase,another portion of the EV resources is combined with the incentive demand response technology.The microgrid energy management center,as the leader,aims to minimize the operating costs,and the incentive EV group,as the follower,aims to minimize the electricity costs.The intra-day master–slave game model of the microgrid was constructed for rolling optimization,and the two sides played the game based on a subsidized price and energy use strategy.Finally,a simulation verification was conducted based on a microgrid scenario,and the results show that the proposed model can reduce the electricity cost of users,reduce the peak-valley difference of the load curve,and realize the full absorption of new energy.