Table of Contents
Advances in Electrical Engineering
Volume 2014, Article ID 301615, 13 pages
Research Article

Nonconvex Economic Dispatch Using Particle Swarm Optimization with Time Varying Operators

Malaviya National Institute of Technology, Jaipur 302017, India

Received 23 May 2014; Revised 17 September 2014; Accepted 18 September 2014; Published 12 October 2014

Academic Editor: Nikos D. Lagaros

Copyright © 2014 Vinay Kumar Jadoun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a particle swarm optimization (PSO) to solve hard combinatorial constrained optimization problems such as nonconvex and discontinuous economic dispatch (ED) problem of large thermal power plants. Several measures have been suggested in the control equation of the classical PSO by modifying its operators for better exploration and exploitation. The inertia operator of the PSO is modulated by introducing a new truncated sinusoidal function. The cognitive and social behaviors are dynamically controlled by suggesting new exponential constriction functions. The overall methodology effectively regulates the velocity of particles during their flight and results in substantial improvement in the classical PSO. The effectiveness of the proposed method has been tested for economic load dispatch of three standard test systems considering various operational constraints like valve-point loading effect, prohibited operating zones (POZs), network power loss, and so forth. The application results show that the proposed PSO method is very promising.