基于模型预测控制含充换储一体站的配电网优化运行

Model Predictive Control Based Optimal Operation of Distribution Network with Charging-Swapping-Storage Integrated Station

提出一种综合考虑电动汽车充换储一体站与主动配电网的优化调度模型。基于快充用户行驶行为特点、城市道路速度-流量实用模型分别建立快充站和换电站模型,并结合梯级储能集成为一体站模型。在含有风机、光伏、微型燃气轮机和一体站接入的主动配电网中建立优化调度模型,并将模型转化为混合整数二阶锥模型求解。使用基于模型预测控制的多时间尺度优化调度策略实现对配电网日前调度、日内滚动调度和实时反馈校正,减少了分布式电源和负荷的预测误差对配电网运行的影响。以某市公交线路实际道路情况为例,验证了所提出的优化调度策略具有能够满足电动汽车充电负荷需求、抑制功率波动并降低配电网运行维护费用的优势。

An optimal scheduling model is proposed, which comprehensively considers electric vehicle(EV) charging-swappingstorage integrated station and active distribution network. Based on driving behavior characteristics of fast-charging users and speedflow practical model of city roads, the fast charging station model and battery swapping station model are established respectively,which are combined with the cascaded energy storage system to form the integrated station model. The optimal scheduling model is established in the active distribution network, which includes wind turbines, photovoltaics, micro-turbines and the integrated station, and the model is transformed into a mixed integer second-order cone model to solve the problem. The multi-time scale optimal scheduling strategy based on model predictive control is used to realize day-ahead scheduling, intra-day rolling scheduling and real-time feedback correction of distribution network, which reduces the impact of distributed generator and load prediction errors on the distribution network operation. Taking the actual road conditions of bus lines in a city as an example, it is verified that the proposed optimal scheduling strategy has advantages of meeting the charging load demand of EVs, suppressing power fluctuation and reducing operation maintenance cost of distribution network.