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Título del libro: 2019 Ieee Pes Conference On Innovative Smart Grid Technologies, Isgt Latin America 2019
Título del capítulo: An Adaptable Hybrid Optimization Algorithm for Solving the Economic and Emission Dispatch Problem

Autores UNAM:
MARIO ROBERTO ARRIETA PATERNINA;
Autores externos:

Idioma:
Inglés
Año de publicación:
2019
Palabras clave:

Electric power transmission networks; Heuristic algorithms; Multiobjective optimization; Simulated annealing; Smart power grids; Adaptive simulated annealing; Economic and emission dispatch; Genetic operators; Metaheuristic; Robust optimization; Electric load dispatching


Resumen:

This paper proposes an adaptive hybrid robust optimization approach harnessing two meta-heuristic algorithms for solving the Economic and Emission Dispatch (EED) problem, this is a typical multi-objective optimization problem with conflicting fuel costs and pollution emission objectives. Thus, the essential idea behind of the proposed hybrid optimization framework is focused on the abilities of the adaptive simulated annealing (ASA) algorithm and genetic operators for evaluating the economic and emission dispatch problem, which allow to accelerate the convergence and to reduce the total number of evaluations. This proposal optimizes the solution of the non-convex EED problem, reducing the generation costs and emissions, and demonstrating a better performance during its convergence characteristics. Numerical tests are carried out in two power grids, aiming to demonstrate the strength of this work and to remark the new advantages regarding other algorithms. © 2019 IEEE.


Entidades citadas de la UNAM: