DOI:
https://doi.org/10.14483/23448393.23474Published:
2025-08-01Issue:
Vol. 30 No. 2 (2025): May-AugustSection:
Electrical, Electronic and Telecommunications EngineeringEnergy Management System using Particle Swarm Optimization for Operating Costs Reduction in AC Microgrids with Battery Storage during Grid-Connected and Islanded Operation
Sistema de gestión de energía mediante optimización por enjambre de partículas para la reducción de costos operativos en microrredes de CA con almacenamiento en baterías durante la operación interconectada y aislada
Keywords:
Energy management system, battery energy storage, microgrids, swarm optimization, grid-on, grid-off (en).Keywords:
Sistema de gestión de energía, Almacenamiento de energía en baterías, Microrred, Optimización por cúmulo de ´´´ partículas (es).Downloads
Abstract (en)
Context: This paper proposes an energy management system (EMS) for battery energy storage systems (BESS) to reduce operating costs in AC microgrids (MGs) operating in grid-connected (GON) and islanded (GOFF) mode, considering energy purchase, conventional generation, and maintenance costs while accounting for all the operational constraints of the system and its components.
Method: A master-slave methodology based on particle swarm optimization (PSO) and an hourly power flow based on the successive approximations method (SAM) is used as a smart BESS operation strategy. This proposal is validated in a 33-bus AC-MG operating in GON and GOFF modes, in comparison with two methods utilizing the vortex search algorithm (VSA) and conitnuos version of the Chu & Beasley genetic algorithm (CBGA) and the same power flow.
Results: The PSO-based EMS achieved the lowest costs i.e., 6897.59 USD/day (GON) and 17 527.42 USD/day (GOFF), with cost reductions of 1.45 and 0.13 %, and low standard deviation values (0.067 and 0.014 %), which confirms its efficiency, robustness, and constraint compliance.
Conclusions: The EMS based on PSO/SAM delivers superior solution quality and processing times in both modes of operation. In GON mode, it reduces the mean costs by 0.0287%compared to the VSA and 0.2252%vs. the CBGA, whereas, in GOFF mode, the reductions are 0.0191 and 0.0355 %, respectively. These results reflect a more effective cost reduction than exact methods, which constitutes this paper’s main contribution.
Abstract (es)
Contexto: En este artículo se propone un sistema de gestión energética (EMS) para sistemas de almacenamiento de energía en baterías (BESS) orientado a la reducción de costos operativos en microrredes (MG) AC que operan conectados a la red (GON) y en modo isla (GOFF), considerando los costos de compra de energía, generación convencional y mantenimiento a la vez que se cumple con todas las restricciones operativas del sistema y sus componentes.
Métado: Como estrategia de operación inteligente del sistema de almacenamiento en baterías, se utiliza una metodología maestro-esclavo basada en optimización por enjambre de partículas y un flujo de potencia horario basado en el método de aproximaciones sucesivas (SAM). Esta propuesta se valida en una MG-AC de 33 nodos, operando en modos GON y GOFF, en comparación con dos métodos alternativos que utilizan el algoritmo de búsqueda por vórtices (VSA) y el algoritmo genético continuo de Chu & Beasley (CBGA) y el mismo método de flujo de potencia.
Resultados: El EMS basado en PSO alcanzó los menores costos, i.e., 6897.59 USD/día (GON) y 17 527.42 USD/día (GOFF), con reducciones en costos del 1.45 y el 0.13% respectivamente y bajas desviaciones estándar (0.067 y 0.014 %), lo que confirma su eficiencia, robustez y cumplimiento de restricciones.
Conclusiones: El EMS basado en PSO/SAM ofrece una calidad de solución y un tiempo de procesamiento superiores en ambos modos de operación. En el modo GON, reduce los costos promedio en un 0.0287% en comparación con el VSA y en un 0.2252% con respecto al CBGA, mientras que, en el modo GOFF, las reducciones son de 0.0191 y 0.0355% respectivamente. Estos resultados reflejan una reducción de costos más efectiva que la obtenida por métodos exactos, lo que constituye la principal contribución de este artículo.
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