Truong, K.H. and Vasant, P. and Sing, M.S.B. and Vo, D.N. (2015) Swarm based mean-variance mapping optimization for solving economic dispatch with cubic fuel cost function. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9012. pp. 3-12. ISSN 03029743
Full text not available from this repository.Abstract
In power generation system, the economic dispatch (ED) is used to allocate the real power output of thermal generating units to meet required load demand so as their total operating cost is minimized while satisfying all units and system constraints. This paper proposes a novel swarm based meanvariance mapping optimization (MVMOS) for solving the ED problem with the cubic fuel cost function. The special feature of the proposed algorithm is a mapping function applied for the mutation based on the mean and variance of nbest population. This method has been tested on 3, 5 and 26 units and the obtained results are compared to those from genetic algorithm (GA), particle swarm optimization (PSO) and firefly algorithm (FA). Test results have indicated that the proposed method is efficient for solving the ED problem with cubic fuel cost function. © Springer International Publishing Switzerland 2015.
Item Type: | Article |
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Additional Information: | cited By 6; Conference of 7th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2015 ; Conference Date: 23 March 2015 Through 25 March 2015; Conference Code:115609 |
Uncontrolled Keywords: | Cost functions; Costs; Database systems; Fuels; Genetic algorithms; Mapping; Optimization; Scheduling, Economic Dispatch; Firefly algorithms; Fuel cost; Mapping functions; Mapping optimization; Power generation systems; System constraints; Thermal generating units, Particle swarm optimization (PSO) |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 09 Nov 2023 16:18 |
Last Modified: | 09 Nov 2023 16:18 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/6370 |