A Comparative Study of Genetic Algorithm based Optimization and Particle Swarm Optimization in Economic Load Dispatch

摘要

Economic load dispatch (ELD) is the scheduling of generators to minimize the total operating cost depending on equality and inequality constraints. The transmission line loss also is to be kept as minimum as possible. So, the problem is of multi-objective op timization. The authors have studied the comparative effectiveness of GA, particle swarm optimization (PSO) for such multi-objective optimization in two standard test cases of 13 and 40 thermal generators with non-monotonically increasing cost functions. The generators are interconnected through lossy transmission lines. Numerical results indicate PSO techniques yield optimal results up to 10/13 units and GA proves to be better than PSOs for more number of units in terms of operating costs but inferior to PSOs in terms of transmission line losses. But, PSOs execute in the least time, yielding near optimal results and this is the major merit of PSO techniques over any other evolutionary technique.