Abstract
The Economic Load Dispatch Problem (ELD) is an important optimization problem in the power system domain. Due to some deficiencies exist in the traditional methods, researchers have been investigating new methods ranging from artificial intelligent methods to optimization algorithms to further extend the quality of the solution. Among the methods, the meta-heuristic method is a popular choice for their unique searching power collectively and iteratively refining the solution by mimicking the moving patterns of biological creatures. However, there are many different kinds of heuristic algorithms available. The objective of this article is to compare their performance in solving ELD. Although it is difficult to look into each different one in depth, our evaluation is on the typical meta-heuristics algorithms which have certain history and application track records. Extensive simulation experiments are performed. It is found that good results are achieved among these algorithms under different cases experiment, especially the CS, FPA, FA, Maniac Fireflies Algorithm (MFA).
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Fong, S., Li, T., Qu, Z. (2021). Comparison of Contemporary Meta-Heuristic Algorithms for Solving Economic Load Dispatch Problem. In: Fong, S., Millham, R. (eds) Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-15-6695-0_7
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