Abstract
This paper presents a bacterial foraging-based optimization (BFBO) technique to solve non-convex economic load dispatch (NCELD) problem of thermal plants. The presented methodology can take care of economic dispatch problems involving constraints such as transmission losses, valve point loading, ramp rate limits and prohibited operating zones. The idea of BFBO is motivated by the natural selection which tends to eliminate the animals with poor foraging strategies and favour those having successful foraging strategies. The BFBO method is tested with two power system cases consisting of 6 and 13 thermal units. Comparison with similar approaches including Genetic Algorithm (GA), particle swarm optimization (PSO) and other versions of differential evolution (DE) are given. The presented method outperforms other state-of-the-art algorithms in solving economic load dispatch problems with the valve-point effect.
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Padmanabhan, B., Sivakumar, R.S., Jasper, J., Victoire, T.A.A. (2011). Bacterial Foraging Approach to Economic Load Dispatch Problem with Non Convex Cost Function. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27172-4_68
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DOI: https://doi.org/10.1007/978-3-642-27172-4_68
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