Optimal power management in a grid-connected microgrid, based on Multi-Objective Genetic Algorithm MOG
No Thumbnail Available
Date
Advisors
Evaluators
Journal Title
Journal ISSN
Volume Title
Publisher
Universidad Industrial de Santander
Abstract
Description
Las microrredes son un concepto revolucionario que enfrenta algunos problemas de los grandes sistemas eléctricos centralizados. Aunque este concepto promete numerosos beneficios, también presenta nuevos desafíos en materia de control y operación. Uno de los desafíos más importantes es gestionar, de manera óptima, la energía producida por las microrredes. Este artículo presenta una estrategia de gestión de potencia en una microrred conectada, basada en el algoritmo MOGA. La estrategia se formula con base en dos objetivos conflictivos entre sí: la reducción de los costos operacionales de la microrred y la reducción de la cantidad de emisiones de gases contaminantes. Los resultados de simulación muestran los beneficios de usar la estrategia de gestión basada en MOGA, en comparación con una estrategia de importación total de la red principal, lo cual hace a MOGA una técnica competitiva para integrar el núcleo optimizador de un sistema de gestión de energía en microrredes.
Microgrids are a revolutionary concept to face some problems of the big and centralized power systems. Although emerging concept promises to offer numerous benefits, also presents new challenges in control and operation. One of the most important challenges is to make optimal power management into the microgrid. This power management must ensure maximum use of available resources; at same time it must reduce environmental contamination. Based on Multi-Objective Genetic Algorithm MOGA, this paper presents one strategy to make optimal power management in a grid-connected microgrid. The strategy runs over two conflictive objectives: to reduce microgrid operational cost and greenhouse emissions. Simulation results show benefits using the MOGA strategy, in comparison with a strategy of full importation from main grid. In this manner, the proposed strategy is a good option to build the optimizer kernel of energy management system EMS in microgrids.
Microgrids are a revolutionary concept to face some problems of the big and centralized power systems. Although emerging concept promises to offer numerous benefits, also presents new challenges in control and operation. One of the most important challenges is to make optimal power management into the microgrid. This power management must ensure maximum use of available resources; at same time it must reduce environmental contamination. Based on Multi-Objective Genetic Algorithm MOGA, this paper presents one strategy to make optimal power management in a grid-connected microgrid. The strategy runs over two conflictive objectives: to reduce microgrid operational cost and greenhouse emissions. Simulation results show benefits using the MOGA strategy, in comparison with a strategy of full importation from main grid. In this manner, the proposed strategy is a good option to build the optimizer kernel of energy management system EMS in microgrids.
Keywords
energy management system (EMS), microgrid, multi-objective optimization, multi-objective genetic algorithm (MOGA), multi-objective optimization evolutionary algorithms (MOEA), optimal power management., algoritmos evolutivos de optimización multiobjetivo, algoritmo genético multiobjetivo, gestión óptima de potencia, microrred, optimización multiobjetivo, sistema de gestión de energía