Optimal Scheduling of Electricity-Gas Integrated Energy System Considering Wind Power Uncertainty

In recent years, the proportion of wind power in power grid has increased rapidly, and the uncertainty of wind power brings challenges to the smooth operation of power grid. This paper establishes an optimal dispatch model for an electricity-gas integrated energy system (EGIES) with power-to-gas (P2G) technique considering the uncertainty of wind power by minimizing the operating cost of the system. Firstly, the wind power probability model is established based on nonparametric kernel density estimation. The wind power scenario is generated by Monte Carlo simulation method, and the typical wind power scenario is obtained by backward scenario reduction technology. Secondly, an optimization model is established to minimize the operation cost of EGIES. Finally, a six-bus power system and a seven-node natural gas system are used as the coupling system, and the gas turbine and the P2G are used as the coupling nodes. The necessity and economy of considering the uncertainty of wind power in the optimal scheduling of EGIES are verified.