Economic load dispatch using a chemotactic differential evolution algorithm

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Abstract

This paper presents a novel stochastic optimization approach to solve constrained economic load dispatch (ELD) problem using Hybrid Bacterial Foraging-Differential Evolution optimization algorithm. In this hybrid approach computational chemotaxis of BFOA, which may also be viewed as a stochastic gradient search, has been coupled with DE type mutation and crossover of the optimization agents. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints (ramp rate limits) and prohibited operating zones. Simulations were performed over various standard test systems with different number of generating units and comparisons are performed with other existing relevant approaches. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques. © 2009 Springer Berlin Heidelberg.

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Biswas, A., Dasgupta, S., Panigrahi, B. K., Pandi, V. R., Das, S., Abraham, A., & Badr, Y. (2009). Economic load dispatch using a chemotactic differential evolution algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5572 LNAI, pp. 252–260). https://doi.org/10.1007/978-3-642-02319-4_30

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