Study on Day-ahead Optimization Strategy of Integrated Energy System Based on Distributionally Robust Optimization in Electricity Spot Market

The participation of new emerging market entities represented by integrated energy system(IES) is an important trend of China's electricity spot market development, also brings new challenges to IES economic optimization caused by much more uncertain variables. Focusing on electricity day-ahead spot market, a financial cost model of IES considering market participation is proposed based on the common mechanism of China's electricity market, together with one IES day-ahead optimization model. By introducing the distributionally robust optimization(DRO) algorithm, an uncertain set of distribution functions including multiple uncertain variables like electricity price, renewable energy output, cooling, heating and power load is established, with the deterministic constraint condition expression of robust chance constraints model is derived. On the nonlinear uncertainty problem of objective function caused by electricity price uncertainty factors, a method of uncertainty sinking is proposed to turn the objective function into a deterministic mixed integer linear optimization model. Case study shows that the method proposed in the paper can effectively solve the problem of multiple uncertainties met by IES participating in electricity spot market, therefore improve the economic level of IES optimization decision.