面向微电网交互的区域电-热综合能源系统风险规避优化调度

A regional electricity-heating integrated energy sys-tem(REH-IES)can make extensive use of renewable energy sources,realize complementary and coordinated operation of multiple energy sources,reduce carbon emissions and promote the development of zero/low carbon systems.This paper proposes a risk-averse stochastic optimal scheduling model for REH-IES.An energy flow framework for the REH-IES is proposed considering energy interaction between the electric-heating mi-crogrids(EHMs)and electricity distribution network and the heating network.Then,considering the uncertainties of power output of renewable energy sources,dynamic characteristics of pipelines in the heating network,and thermal inertia of smart buildings,a stochastic optimal scheduling model for the REH-IES is established.Uncertainties of renewable energy sources bring financial risks to optimal scheduling of the REH-IES.Therefore,conditional value-at-risk(CVaR)theory is adopted to measure the risk and to limit the risk within an acceptable range,to achieve minimum expected scheduling cost of the REH-IES.The stochastic programming-based problem is transformed into a second-order cone programming(SOCP)model through second-order cone relaxation method.Case studies verify the stochastic optimal scheduling model can reduce expected scheduling cost of the REH-IES,promote consumption of renewable energy sources and reduce carbon emissions.