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Evolutionary Algorithm Applied to Economic Load Dispatch

Evolutionary Algorithm Applied to Economic Load Dispatch

Copyright: © 2019 |Pages: 52
ISBN13: 9781522569718|ISBN10: 1522569715|ISBN13 Softcover: 9781522587699|EISBN13: 9781522569725
DOI: 10.4018/978-1-5225-6971-8.ch003
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MLA

Provas Kumar Roy and Susanta Dutta. "Evolutionary Algorithm Applied to Economic Load Dispatch." Optimal Power Flow Using Evolutionary Algorithms, IGI Global, 2019, pp.65-116. https://doi.org/10.4018/978-1-5225-6971-8.ch003

APA

P. Roy & S. Dutta (2019). Evolutionary Algorithm Applied to Economic Load Dispatch. IGI Global. https://doi.org/10.4018/978-1-5225-6971-8.ch003

Chicago

Provas Kumar Roy and Susanta Dutta. "Evolutionary Algorithm Applied to Economic Load Dispatch." In Optimal Power Flow Using Evolutionary Algorithms. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-6971-8.ch003

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Abstract

This chapter introduces various evolutionary algorithms, namely grey wolf optimization (GWO), teaching-learning-based optimization (TLBO), biogeography-based optimization (BBO), krill herd algorithm (KHA), chemical reaction optimization (CRO) algorithms, for solving the economic load dispatch (ELD) problem of various power systems. To demonstrate the superiority of the proposed approaches in solving non-convex, non-linear and constrained ELD problem, the aforesaid approaches are implemented on 10-unit, 15-unit, 40-unit, 80-unit, and 140-unit test systems. It is observed from the simulation results that HCRO exhibits significantly better performance in terms of solution quality and convergence speed for all the cases compared to other discussed algorithms. Furthermore, the statistical results confirm the robustness of the proposed HCRO algorithm.

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