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    Operations of a microgrid with renewable energy integration and line switching

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    Name:
    Microgrid+RES(v13_revision).pdf
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    Description:
    Final Accepted Manuscript
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    Author
    Ruiz Duarte, José Luis
    Fan, Neng
    Affiliation
    Univ Arizona, Dept Syst & Ind Engn
    Issue Date
    2019-05
    Keywords
    Microgrid
    Renewable energy sources
    Strorage systems
    Line switching
    Robust optimization
    Column-and-constraint generation algorithm
    
    Metadata
    Show full item record
    Publisher
    SPRINGER HEIDELBERG
    Citation
    Ruiz Duarte, J.L. & Fan, N. Energy Syst (2019) 10: 247. https://doi.org/10.1007/s12667-018-0286-8
    Journal
    ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS
    Rights
    © Springer-Verlag GmbH Germany, part of Springer Nature 2018.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    With the development of new technologies and their integration to the conventional power grid, the smart grid with the capacity of satisfying power demand by large amount of renewable energy is emerging. Microgrid, a small-scale power system with clearly defined electrical boundaries and ability of self-supply, especially by distributed renewable energy, plays a big role in this process. In this paper, we study the operations of a microgrid with solar photovoltaic generators, energy storage system, and power exchanges with main power grid. More specifically, a mixed integer programming model is formulated for decision-making, such as scheduling of generators within the microgrid, islanding operations through line switching and power trades between microgrid and the main grid, charging and discharging operations of storage system, and also line switching within the microgrid, by robust optimization for capturing the uncertainties of solar power generation. To solve the robust optimization formulation, we formulate our model in order to apply the column-and-constraint generation algorithm, and perform numerical experiments on several test cases to validate the proposed model and algorithm.
    Note
    12 month embargo; published online: 03 April 2018
    ISSN
    1868-3967
    1868-3975
    DOI
    10.1007/s12667-018-0286-8
    Version
    Final accepted manuscript
    Sponsors
    Mexican National Council of Science and Technology (CONACYT); Mexican Department of Energy (SENER); University of Arizona
    Additional Links
    http://link.springer.com/10.1007/s12667-018-0286-8
    ae974a485f413a2113503eed53cd6c53
    10.1007/s12667-018-0286-8
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