Abstract
The Dynamic economic dispatch (DED) is an optimization problem with an objective to determine the optimal combination of power outputs for all generating units over a certain period of time in order to minimize the total fuel cost while satisfying dynamic operational constraints and load demand in each interval. Recently social foraging behavior of Escherichia coli bacteria has been explored to develop a novel algorithm for distributed optimization and control. The Bacterial Foraging Optimization Algorithm (BFOA) is currently gaining popularity in the community of researchers, for its effectiveness in solving certain difficult real-world optimization problems. This article comes up with a hybrid approach involving Differential Evolution (DE) and BFOA algorithm for solving the DED problem of generating units considering valve-point effects. The proposed hybrid algorithm has been extensively compared with the classical approach and those reported in the literature. The new method is shown to be statistically significantly better on two test systems consisting of five and ten generating units.
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Vaisakh, K., Praveena, P., Sujatah, K.N. (2013). Differential Evolution and Bacterial Foraging Optimization Based Dynamic Economic Dispatch with Non-smooth Fuel Cost Functions. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2013. Lecture Notes in Computer Science, vol 8298. Springer, Cham. https://doi.org/10.1007/978-3-319-03756-1_52
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DOI: https://doi.org/10.1007/978-3-319-03756-1_52
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