A Novel P- PSO Algorithm Solution of Dynamic Economic Dispatch

In solving the electrical power systems economic dispatch (ED) problems, the goal is to schedule the committed generating units outputs so as to meet the required load demand at the minimum operating cost while satisfying all units and system equality and inequality constraints. This paper presents a different approach to economic dispatch problems with particle swarm optimization (PSO) technique. In proposed method to achieve better control on the algorithm’s exploration and exploitation capabilities, particles velocity is dependent on both particle’s fitness and time. Perturbation module is adopted to perform perturbation on some particles and provide extra diversity for it to jump out from local optima and avoid premature convergence. The proposed P-PSO method solves both, the ED problem with nonconvex/nonsmooth cost functions due to valve-point loading and the ED problem that takes into account nonlinear generator characteristics such as ramp-rate limits and prohibited operating zones in the power system operation. The performance of the P-PSO method is evaluated on four different power systems, and compared with that of other effective optimization methods in terms of the solution quality and convergence performance. The outcome is very encouraging and suggests that the P- PSO algorithm is very efficient to solve power system economic dispatch problem.