Simple particle swarm optimization for economic dispatch with piecewise quadratic fuel cost function

Economic power dispatch problem plays an important role in the operation of the power systems. The objective of economic dispatch problem is to schedule output of the committed units such that the total fuel cost is minimized while meeting a set of operating constraints. In this paper, two modified particle swarm optimization algorithms with one of the accelerating coefficients being constant are proposed to solve the economic power dispatch problem with piecewise quadratic cost functions. The proposed algorithm was verified by applying to a 10-unit system available in literature. The results demonstrate that the feasibility and capability of the proposed method for solving economic dispatch problems with nonsmooth cost functions. Without generating one random number during the process, computation time is saved. Meantime, work for parameter tuning of the proposed algorithm is also reduced with fewer parameters.