Evolutionary Algorithms for Dynamic Economic Dispatch Problems

The dynamic economic dispatch problem is a high-dimensional complex constrained optimization problem that determines the optimal generation from a number of generating units by minimizing the fuel cost. Over the last few decades, a number of solution approaches, including evolutionary algorithms, ha...

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Bibliographic Details
Published in:IEEE transactions on power systems Vol. 31; no. 2; pp. 1486 - 1495
Main Authors: Zaman, M. F., Elsayed, Saber M., Ray, Tapabrata, Sarker, Ruhul A.
Format: Journal Article
Language:English
Published: New York IEEE 01.03.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Constrained optimization
constraint handling
Cost engineering
Design engineering
differential evolution
dynamic economic dispatch
Dynamics
Economics
Evolutionary algorithms
genetic algorithm
Genetic algorithms
Heuristic algorithms
non-uniform mutation
Optimization
Power dispatch
Power system dynamics
Production scheduling
Sociology
State of the art
Statistics
ISSN:0885-8950, 1558-0679
Online Access:Get full text
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Summary:The dynamic economic dispatch problem is a high-dimensional complex constrained optimization problem that determines the optimal generation from a number of generating units by minimizing the fuel cost. Over the last few decades, a number of solution approaches, including evolutionary algorithms, have been developed to solve this problem. However, the performance of evolutionary algorithms is highly dependent on a number of factors, such as the control parameters, diversity of the population, and constraint-handling procedure used. In this paper, a self-adaptive differential evolution and a real-coded genetic algorithm are proposed to solve the dynamic dispatch problem. In the algorithm design, a new heuristic technique is introduced to guide infeasible solutions towards the feasible space. Moreover, a constraint-handling mechanism, a dynamic relaxation for equality constraints, and a diversity mechanism are applied to improve the performance of the algorithms. The effectiveness of the proposed approaches is demonstrated on a number of dynamic economic dispatch problems for a cycle of 24 h. Their simulation results are compared with each other and state-of-the-art algorithms, which reveals that the proposed method has merit in terms of solution quality and reliability.
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ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2015.2428714