Título Optimising microgrid energy management: Leveraging flexible storage systems and full integration of renewable energy sources
Autores Álvarez-Arroyo C. , Vergine S. , SÁNCHEZ DE LA NIETA LÓPEZ, AGUSTÍN ALEANDRO, ALVARADO BARRIOS, LÁZARO, D'Amico G.
Publicación externa No
Medio RENEWABLE ENERGY
Alcance Article
Naturaleza Científica
Cuartil JCR 1
Cuartil SJR 1
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195081727&doi=10.1016%2fj.renene.2024.120701&partnerID=40&md5=2071e850b21cb649287402b95601eb33
Fecha de publicacion 01/01/2024
Scopus Id 2-s2.0-85195081727
DOI 10.1016/j.renene.2024.120701
Abstract The significance of microgrid systems has grown considerably. This research proposes an innovative approach to manage uncertainty in microgrids by employing energy storage systems as the exclusive flexible resource. To address this challenge, a mathematical problem is formulated as a two-stage stochastic programming model, considering two uncertainties in the microgrid: wind and photovoltaic production. The microgrid system encompasses multiple components, including a diesel generator, a microturbine, wind and photovoltaic power generation, an energy storage system, and the microgrid\'s demand. Notably, the microgrid exhibits two distinctive features: (i) the complete integration of wind and photovoltaic production, and (ii) the utilisation of an energy storage system as the sole flexible resource. The objective is to minimise the expected cost of the microgrid system while determining the optimal capacity of the energy storage system to meet the energy balance constraint. This constraint takes into account the varying scenarios of wind and photovoltaic production. The decisions are taking for a duration of 8760 h, a long-term evaluation. A case study is presented for actual data from Greece and the results show high volatility of the renewable energy sources implies higher energy storage system capacity as a sole flexible source for avoiding renewable curtailment. © 2024 Elsevier Ltd
Palabras clave Greece; Digital storage; Energy storage; Natural resources; Solar energy; Stochastic models; Stochastic systems; Storage management; Wind power; Energy source; Energy storage system; Flexible energy source; Microgrid; Microgrid systems; Photovoltaic power; Photovoltaic productions; Renewable energy source; Storage systems; Uncertainty; alternative energy; energy balance; energy management; energy storage; photovoltaic system; stochasticity; wind power; Stochastic programming
Miembros de la Universidad Loyola

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