A hybrid differential evolution algorithm based on particle swarm optimization for nonconvex economic dispatch problems

Authors:
Samir Sayah;Abdellatif Hamouda
Affiliations:
QUERE Laboratory, Department of Electrical Engineering, University of Ferhat Abbas, Setif 19000, Algeria;QUERE Laboratory, Department of Electrical Engineering, University of Ferhat Abbas, Setif 19000, Algeria
Venue:
Applied Soft Computing
Year:
2013

Citing 4
Cited 0

Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces

Journal of Global Optimization
Solution of nonconvex and nonsmooth economic dispatch by a new Adaptive Real Coded Genetic Algorithm

Expert Systems with Applications: An International Journal
Enhancement of Self-adaptive real-coded genetic algorithm using Taguchi method for Economic dispatch problem

Applied Soft Computing
Evolutionary programming techniques for economic load dispatch

IEEE Transactions on Evolutionary Computation

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Abstract

This paper presents the design and application of an efficient hybrid heuristic search method to solve the practical economic dispatch problem considering many nonlinear characteristics of power generators, and their operational constraints, such as transmission losses, valve-point effects, multi-fuel options, prohibited operating zones, ramp rate limits and spinning reserve. These practical operation constraints which can usually be found at the same time in realistic power system operations make the economic load dispatch problem a nonsmooth optimization problem having complex and nonconvex features with heavy equality and inequality constraints. The proposed approach combines in the most effective way the properties of two of the most popular evolutionary optimization techniques now in use for power system optimization, the Differential Evolution (DE) and Particle Swarm Optimization (PSO) algorithms. To improve the global optimization property of DE, the PSO procedure is integrated as additional mutation operator. The effectiveness of the proposed algorithm (termed DEPSO) is demonstrated by solving four kinds of ELD problems with nonsmooth and nonconvex solution spaces. The comparative results with some of the most recently published methods confirm the effectiveness of the proposed strategy to find accurate and feasible optimal solutions for practical ELD problems.