A T-cell algorithm for solving dynamic economic power dispatch problems

Victoria Aragón; Carlos A. Coello Coello; Mario A. Leguizamón

doi:10.24215/16666038.20.e01

Authors

Victoria Aragón Universidad Nacional de San Luis, Argentina
Carlos A. Coello Coello CINVESTAV-IPN (Evolutionary Computation Group), Departamento de Computación, Av. IPN No. 2508, Col. San Pedro Zacatenco, México D.F. 07300, MÉXICO
Mario A. Leguizamón Laboratorio de Investigación y Desarrollo en Inteligencia Computacional, Universidad Nacional de San Luis - Ej. de Los Andes 950, San Luis (5700), ARGENTINA

DOI:

https://doi.org/10.24215/16666038.20.e01

Keywords:

Artificial immune systems, dynamic economic dispatch problem, dynamic economic emission dispatch problem, metaheuristics

Abstract

This paper presents the artificial immune system IA_DED (Immune Algorithm Dynamic Economic Dispatch) to solve the Dynamic Economic Dispatch (DED) problem and the Dynamic Economic Emission Dispatch (DEED) problem. Our approach considers these as dynamic problems whose constraints change over time. IA\DED is inspired on the activation process that T cells suffer in order to find partial solutions. The proposed approach is validated using several DED problems taken from specialized literature and one DEED problem. The latter is addressed by transforming a multi-objective problem into a single-objective problem by using a linear aggregating function that combines the (weighted) values of the objectives into a single scalar value. Our results are compared with respect to those obtained by other approaches taken from the specialized literature. We also provide some statistical analysis in order to determine the sensitivity of the performance of our proposed approach to its parameters. Part of this work was presented at the XXV Argentine Congress of Computer Science (CACIC), 2019.

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