Managing Economic Load Dispatch through Multi-swarm Statistical Particle Swarm Optimization

In power systems, the ELD is crucial for managing the minimum generation cost of electrical-generating units while fulfilling the constraints and maintaining the load demand. Traditional optimization techniques do not provide an optimum solution for nonlinear, large, and complex ELD data. This study proposed a multiswarm statistical particle swarm optimization algorithm for solving the ELD problem. This paper presents a multiswarm statistical particle swarm optimization algorithm to solve nonlinear and complex ELD problems. Multi-swarm statistical particle swarm optimization (MSPSO) is a new and strong type of PSO that uses multiple swarms and statistical adaptation mechanisms to improve swarm exploration and convergence in search spaces. This makes MSPSO a good way to solve difficult nonlinear ELD problems. This work considered two case studies of 10 and 15 generatinlg unit data to examine the performance of MSPSO in terms of minimization of cost, speed of convergence, and computation time. The results obtained by MSPSO for both case studies were compared with those of the other optimization techniques. The results shown by MSPSO are better than those of the others.