结合M-Copula理论与半不变量的随机潮流方法

With more and more renewable energy, such as photovoltaic and wind power, integrated into power systems, random problem of power system operation becomes increasingly prominent. Traditional deterministic power flow will not reflect actual operation status of power systems, while probabilistic load flow can fully consider various kinds of operating conditions of power systems and provide a guidance for power system planning and operation. However, nonlinear correlation with renewable energy is complex due to time and spatial coupling of natural conditions. In order to deal with this nonlinear correlation, a new cumulant method based on M-Copula theory combining cumulants for probabilistic load flow is proposed, and multiple Copula function models are chosen to describe complex correlation between random variables. The proposed method can deal with the nonlinear correlation with renewable energy and maintain fast computation speed of cumulant method. The fast computation speed and high accuracy of this algorithm is proved with case study in a modified IEEE 14 system by comparing with Monte Carlo simulations.