Título Optimal management of a hybrid and isolated microgrid in a random setting
Autores Vergine S. , Álvarez-Arroyo C. , D'Amico G. , Escaño J.M. , ALVARADO BARRIOS, LÁZARO
Publicación externa No
Medio Energy Reports
Alcance Article
Naturaleza Científica
Cuartil JCR 2
Cuartil SJR 2
Impacto JCR 5.2
Impacto SJR 0.973
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135133926&doi=10.1016%2fj.egyr.2022.07.044&partnerID=40&md5=991b55645cc9ba56a71502d277a63ce5
Fecha de publicacion 01/11/2022
ISI 000861228800011
Scopus Id 2-s2.0-85135133926
DOI 10.1016/j.egyr.2022.07.044
Abstract Nowadays, governments and electricity companies are making efforts to increase the integration of renewable energy sources into grids and microgrids, thus reducing the carbon footprint and increasing social welfare. Therefore, one of the purposes of the microgrid is to distribute and exploit more zero emission sources. In this work, a Stochastic Unit Commitment of a hybrid and isolated microgrid is developed. The microgrid supplies power to satisfy the demand response by managing a photovoltaic plant, a wind turbine, a microturbine, a diesel generator and a battery storage system. The optimization problem aims to reduce the operating cost of the microgrid and is divided into three stages. In the first stage, the uncertainties of the wind and photovoltaic powers are modeled through Markov processes, and the demand power is predicted using an ARMA model. In the second stage, the stochastic unit commitment is solved by considering the system constraints, the renewable power production, and the predicted demand. In the last stage, the real-time operation of the microgrid is modeled, and the error in the demand forecast is calculated. At this point, the second optimization problem is solved to decide which generators must supply the demand variation to minimize the total cost. The results indicate that the stochastic models accurately simulate the production of renewable energy, which strongly influences the total cost paid by the microgrid. Wind production has a daily impact on total cost, whereas photovoltaic production has a smoother impact, shown in terms of general trend. A comparison study is also considered to emphasize the importance of correctly modeling the uncertainties of renewable power production in this context. © 2022 The Author(s)
Palabras clave Carbon footprint; Electric load dispatching; Electric power generation; Microgrids; Natural resources; Optimization; Renewable energy resources; Scheduling; Stochastic models; Stochastic systems; Uncertainty analysis; Economic Dispatch; Microgrid; Optimal management; Optimization problems; Power; Renewable energy source; Renewable power production; Stochastic unit commitments; Uncertainty; Unit Commitment; Markov processes
Miembros de la Universidad Loyola

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