Comparison and Analysis of Multiobjective Evolutionary Algorithm for Reactive Power Optimization

Reactive power optimization based on multiobjective evolutionary algorithms (MOEAs) was studied. Different with the traditional approach that combines multiple objective functions into a single one by setting preference parameters, the approach adopts and optimizes the multiobjective models directly. The uniform framework of MOEAsbased reactive power optimization was proposed and the detailed procedures were discussed. Based on the test case of IEEE 30 bus system, from the view point of Pareto fronts, outer solutions and C metric, the computing performances of five MOEAs were compared, which were classified into five performance levels. According to the levels, the advantages as well as disadvantages of all the MOEAs were outlined. These conclusions may be a great reference for further application and improvements of MOEAs in reactive power optimization and other optimization problems of electric power systems.