A hunger game search algorithm for economic load dispatch

Abstract

This work proposes a new approach to solve the economic load dispatch (ELD) issue in power systems by metaheuristic algorithms inspired by natural life. The problem to be resolved is to optimize the power system network with various constraints by considering the cutting in the cost of the resulting in the transmission of the electric system. The method used in this study is the hunger games search (HGS). This method duplicates the hungerdriven activity and the animal's choice of behavior. The proposed method is to add the concept of starvation as a process structure. Adaptive weights based on the concept of hunger are designed and used to simulate the effects of hunger on each trace process. To get the performance of the proposed method, this research uses mathematical methods, particle swarm optimization (PSO), differential evolution (DE), giza pyramids construction (GPC), and sine tree-seed algorithm (STSA) as a comparison. This study uses 2 case studies. In case study 1, the proposed method has a 0.16% better cost of generation than the mathematical method. Comparison of the HGS method with the PSO method in the second case study, it was found that the HGS method was 0.018% better than the PSO. From the research, it was found that the HGS method was superior.