Abstract
Economic dispatch (ED) is a power system optimization problem, and its objective is to reduce the total generation cost of units while satisfying constraints. the presence of nonlinearities in practical generator operation makes solving the ED problem more challenging. These generator nonlinearities are modeled as constraints to be met in the form of ramp-rate limits and prohibited operating zones. This paper proposes three heuristic algorithms, namely, the genetic algorithm (GA), differential evolution (DE) and modified particle swarm optimization (MPSO) to solve this ED problem for two test systems. Simulation, numerical results and convergence performances of these three algorithms are presented and compared as a way of demonstrating and validating the heuristic algorithms in solving this complex and challenging power system problem characterized by practical and nonconvex generator constraints. © 2009 IEEE.
Recommended Citation
Y. Yare et al., "Heuristic Algorithms for Solving Convex and Nonconvex Economic Dispatch," 2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09, article no. 5352852, Institute of Electrical and Electronics Engineers, Dec 2009.
The definitive version is available at https://doi.org/10.1109/ISAP.2009.5352852
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Differential evolution; Economic cost function; Economic dispatch; Generation cost; Genetic algorithm; Particle swarm optimization; Prohibited operating zones; Ramp-rate limits
International Standard Book Number (ISBN)
978-142445098-5
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
09 Dec 2009
