In order to reduce the influence of photovoltaic output uncertainty on the economy and safety of a multi-region integrated energy system(IES)and improve the stable operation capability of a multi-area IES system in various extreme scenarios,a multi-scene optimization scheduling strategy for multi-area integrated energy system considering the uncertainty of photovoltaic output is proposed.Aiming at the uncertainty of photovoltaic power generation,Latin hypercube sampling and improved artificial bee colony K-means clustering algorithm are used to form a typical photovoltaic scene sets.A thermal network model is established according to the thermal characteristics of heating pipes and the dynamic characteristics of thermal energy transmission.Based on photovoltaic scene information,the operating cost in the day-ahead stage and the adjustment cost of the system under the worst photovoltaic scenario in the real-time stage are taken as the optimization objectives,and a two-stage distribution robust optimization scheduling model is constructed.The two-stage model is solved using a column-and-constraint generation(C&CG)algorithm.Finally,the correctness and feasibility of the proposed strategy are verified by an example.
关键词
可再生能源/不确定性分析/调度算法/多区域综合能源系统/多场景/分布鲁棒优化
Key words
renewable energy/uncertainty analysis/scheduling algorithms/multi-area integrated energy system/multi-scenario/distribution robust optimization
维普
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