Differential evolution based dynamic decomposed strategy for solution of large practical economic dispatch

This paper presents an Improved Parallel Differential Evolution (IPDE) optimization algorithm based dynamic decomposed strategy to solving large economic dispatch (ED) with consideration of practical generators constraints. The migration operation inspired from Biogeography-based Optimization algorithm (BBO) is newly introduced in the parallel DE approach, thereby can effectively explore and exploit promising regions in a search space by creating dynamically new efficient partitions. This new mechanism based migration between individuals from different subsystems makes to react more by exchanging experiences. The algorithm is applied to large electrical network test system, 40 thermal units with non-smooth cost function. The simulation results compared with the other recent techniques. From the different case studies, it is observed that the proposed approach improves the performances of the standard Differential Evolution algorithm (DE) and gives results with qualitative solution and less computational time.