MULTI-SCENARIO DISTRIBUTED ROBUST OPTIMAL SCHEDULING OF MULTI-AREA INTEGRATED ENERGY SYSTEMS CONSIDERING PHOTOVOLTAIC UNCERTAINTY
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.
renewable energyuncertainty analysisscheduling algorithmsmulti-area integrated energy systemmulti-scenariodistribution robust optimization
万方数据
维普
