Abstract
As energy costs are expected to keep rising in the coming years, mostly due to a growing worldwide demand, optimizing power generation is of crucial importance for utilities. Economic power dispatch is a tool commonly used by electric power plant operators to optimize the use of generation units. Optimization algorithms are at the center of such techniques and several different types of algorithms, such as genetic or particle swarm algorithms, have been proposed in the literature. This paper proposes the use of a new metaheuristic called imperialist competitive algorithm (ICA) for solving the economic dispatch problem. The algorithm performance is compared with the ones of other common algorithms. The accuracy and speed of the algorithm are especially studied. Results are obtained through several simulations on power plants and microgrids in which variable numbers of generators, storage units, loads and grid import/export lines are connected.
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Roche, R., Idoumghar, L., Blunier, B., Miraoui, A. (2012). Imperialist Competitive Algorithm for Dynamic Optimization of Economic Dispatch in Power Systems. In: Hao, JK., Legrand, P., Collet, P., Monmarché, N., Lutton, E., Schoenauer, M. (eds) Artificial Evolution. EA 2011. Lecture Notes in Computer Science, vol 7401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35533-2_19
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DOI: https://doi.org/10.1007/978-3-642-35533-2_19
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