Optimal Scheduling of Electricity-Gas Integrated Energy System Based on Conditional Value at Risk Theory

With the large-scale grid connection of wind power with strong uncertainty, the output of power generation side is uncontrollable, which affects the reliable operation of power system and reduces the social benefits of renewable energy generation. In order to effectively reduce the adverse impact of wind power consumption on power grid, an optimal dispatching model of electricity-gas integrated energy system (EGIES) considering the uncertainty of wind power output is established. Firstly, based on the mathematical model of power grid, natural gas network and coupling equipment, the economic dispatch of integrated energy system (IES) is studied. In addition, the conditional value at risk (CVaR) theory is used to describe the risk loss faced by wind power uncertainty, and the risk loss function evaluated by CVaR theory is introduced into the objective function. Finally, taking IEEE33-24 as an example, it is verified that introducing CVaR into IES scheduling model can effectively reduce the running cost of the system and improve the running security. At the same time, the simulation results also show the influence of the change of confidence level and risk coefficient on IES.