Reliability Assessment in Rural Distribution Systems with Microgrids: A Computational- Based Approach

Jose L. Lopez-Prado, Jorge W. Gonzalez-Sanchez, Jorge I. Velez, Guisselle A. Garcia-Llinas

    Producción científica: Contribución a una revistaArtículo en revista científica indexadarevisión exhaustiva

    5 Citas (Scopus)


    Rural distribution systems, especially in developing countries, tend to be less reliable than urban distribution systems because customers are (1) located remotely and (2) connected to weak aerial networks with radial topologies without redundancy. To improve reliability in rural areas, microgrids (MGs) are being integrated into conventional power systems. This study evaluates the effect on the reliability of rural distribution systems when MGs are introduced considering different penetration levels for renewable and nonrenewable distributed generation, and under rated power of energy storage. Here, we first formulate a reliability model for a rural distribution system with MGs. Based on this model, an interactive method using a sequential Monte Carlo simulation method is proposed and applied to calculate different conventional reliability indices. We show that this approach facilitates the selection of the parameters of the different systems constituting the MGs in order to comply with a predefined reliability objective. For instance, by introducing only photovoltaic distributed generation systems to the rural distribution systems under study, achieving the reliability objective is next to impossible. However, when correctly dimensioned-hybrid MGs are introduced, such an objective is successfully achieved. In the future, our model and the results provided herein could be combined with technical and economic studies to obtain an optimal solution that meets a certain reliability objective.

    Idioma originalInglés
    Páginas (desde-hasta)43327-43340
    Número de páginas14
    PublicaciónIEEE Access
    EstadoPublicada - 2022

    Nota bibliográfica

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    © 2013 IEEE.

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    • Artículos de investigación con calidad A1 / Q1


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