ABSTRACT

Energy shortage needs the electric power industry improve efficiency, realizing the maximize utilization of resources. Only pursue power system economic dispatch already can’t satisfy the requirements, multi-objective optimization scheduling[1-3] become the current research hot spot. Conventional algorithms for processing high-dimensional multi-objective optimization of hydro-thermal have certain limitations, people turn to the intelligent optimization algorithms, such as genetic algorithm[4], particle swarm algorithm[5], because they have faster convergence performance and higher convergence precision. Standard PSO can effectively optimize the single objective problem, then people usually adopt weight coefficient, goal programming method or other method convert multi-objective problem into single objective problem to optimize. These processing methods need to have strong prior knowledge, cannot effectively response the actual operation situation.