This paper describes a successful adaptation of the particle swarm optimisation (PSO) algorithm to solve various types of economic dispatch (ED) problems in power systems such as, multi-area ED with tie line limits, ED with multiple fuel options, combined environmental economic dispatch, and the ED of generators with prohibited operating zones. Numerical examples typical to each type are solved on Matlab 6.5 platform, using both the PSO method and the classical evolutionary programming (CEP) approach. The results obtained show that the proposed PSO based ED algorithm can provide comparable dispatch solutions with reduced computation time for all types of ED problems. © 2005 Elsevier Ltd. All rights reserved.

Jayabarathi T

Department of Electrical Engineering

School of Electrical Engineering

Vellore Campus

Raghunathan T

Department of Control and Automation

Jeyakumar D.N

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

International Journal of Electrical Power & Energy Systems

Fulltext

IOP Conference Series: Materials Science and Engineering

PID controller tuning using metaheuristic optimization algorithms for benchmark problems

This paper presents the application of one of the latest swarm intelligence algorithms, the grey wolf optimizer, for solving economic dispatch problems that are nonlinear, non-convex and discontinuous in nature, with numerous equality and inequality constraints. Grey wolf optimizer is a new metaheuristic algorithm that is loosely based on the behavior of the grey wolves. The optimizer has been hybridized to include crossover and mutation for better performance. Four economic dispatch problems (6, 15, 40, and 80 generators), with prohibited operating zones, valve point loading effect and ramp rate limit constraints have been solved, with and without transmission losses. The losses are calculated using B-coefficients. The results obtained are compared with those reported using other methods in the literature. The comparisons show that the hybrid grey wolf optimizer used in this paper either matches or outperforms the other methods. © 2016 Elsevier Ltd.

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Economic dispatch using hybrid grey wolf optimizer

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Combined economic emission dispatch problem using chaotic self adaptive PSO

Chaotic self adaptive particle swarm approach for solving economic dispatch problem with valve-point effect

In this paper the invasive weed optimization algorithm has been applied to a variety of economic dispatch (ED) problems. The ED problem is concerned with minimizing the fuel cost by optimally loading the electrical generators which are committed to supply a given demand. Some involve prohibited operating zones, transmission losses and valve point loading. In general, they are non-linear non-convex optimization problems which cannot be directly solved by conventional methods. In this work the invasive weed algorithm, a meta-heuristic method inspired by the proliferation of weeds, has been applied to four numerical examples and has resulted in promising solutions compared to published results. © 2012 Higher Education Press and Springer-Verlag Berlin Heidelberg.

Frontiers in Energy

Application of the invasive weed optimization algorithm to economic dispatch problems

Electric Machines & Power Systems

Evolutionary Programming-Based Multiarea Economic Dispatch with Tie Line Constraints

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Particle swarm optimization to solving the economic dispatch considering the generator constraints

Comparison and application of evolutionary programming techniques to combined economic emission dispatch with line flow constraints

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region

IEEE TENCON 2003. Conference on Convergent Technologies for the Asia-Pacific Region (IEEE Cat. No.03CH37503)

Adaptive Hopfield neural networks for economic load dispatch

Particle swarm optimization for various types of economic dispatch problems

Journal	Data powered by TypesetInternational Journal of Electrical Power & Energy Systems
Publisher	Data powered by TypesetElsevier BV
ISSN	0142-0615
Open Access	No