Fuzzified Particle Swarm Optimization Algorithm for Multi-area Security Constrained Economic Dispatch

This article presents a new computationally efficient fuzzified particle swarm optimization algorithm for solving the security-constrained multi-area economic dispatch of an interconnected power system. The core objective of the security-constrained multi-area economic dispatch is to determine the generation allocation of each committed unit in the system and the power exchange between areas so as to minimize the total generation cost without violating the tie-line constraint. The proposed fuzzified particle swarm optimization algorithm is based on the combined application of fuzzy logic strategy incorporated in the particle swarm optimization algorithm. The proposed method was tested on a system of three interconnected areas. The investigation reveals that the proposed method can provide an accurate solution with fast convergence and has the potential to be applied to other power system optimization problems.