QUANTUM PARTICLE SWARM OPTIMIZATION FOR ECONOMIC DISPATCH PROBLEM USING CUBIC FUNCTION CONSIDERING POWER LOSS CONSTRAINT

Abstract

In this paper, quantum computing (QC) inspired particle swarm optimization (QPSO) technique is
utilized to solve economic dispatch (ED) problem, which has strong, robust and reliable search capability with
powerful convergence properties. Here, authors use cubic criterion function to represent ED instead of the
traditional quadratic function, to make the system robust against nonlinearities of actual power generators. Power
balance, power loss and generator limit constraints are considered in this research work. To show the efficiency
and robustness of the proposed method, authors have compared the obtained results with other algorithms like
PSO and GA for ED problem on 3-unit and 5-unit power generating systems. The obtained results demonstrate
QPSO’s superiority over other methods in terms of providing quality solutions with significant amount of
robustness and computationally efficiency.