A novel evolutionary algorithm for solving large-scale dynamic economic dispatch problem integrated with wind power

Abstract

With the development of large-scale power systems, wind power has become the mainstream. Wind power is clean energy, but its uncertainty will bring risks to the economic dispatch of the power system. This paper adopts an adjustable robust optimization method to deal with the uncertainty of wind power output, so that the power system can achieve an acceptable balance between economy and safety. In addition, this paper also proposes a novel evolutionary algorithm (NEA) to solve the large-scale dynamic economic dispatch problem with wind power. The case contains 10 generators, 4 wind farms and 96 time periods in a day are used as scheduling cycles, and there are 960 decision variables in total. The experimental results verify the effectiveness and efficiency of the robust optimization method and the NEA.