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Optimal Load Shedding for Maximizing Satisfaction in an Islanded Microgrid

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  • Yeongho Choi

    (Department of Information Technology Engineering, Sookmyung Women’s University, Seoul 04310, Korea)

  • Yujin Lim

    (Department of Information Technology Engineering, Sookmyung Women’s University, Seoul 04310, Korea)

  • Hak-Man Kim

    (Department of Electrical Engineering, Incheon National University, Incheon 22012, Korea)

Abstract

A microgrid (MG) is a discrete energy system that can operate either in parallel with or independently from a main power grid. It is designed to enhance reliability, carbon emission reduction, diversification of energy sources, and cost reduction. When a power fault occurs in a grid, an MG operates in an islanded manner from the grid and protects its power generations and loads from disturbance by means of intelligent load shedding. A load shedding is a control procedure that results in autonomous decrease of the power demands of loads in an MG. In this study, we propose a load shedding algorithm for the optimization problem to maximize the satisfaction of system components. The proposed algorithm preferentially assigns the power to the subdemand with a high preference to maximize the satisfaction of power consumers. In addition, the algorithm assigns the power to maximize the power sale and minimize the power surplus for satisfaction of power suppliers. To verify the performance of our algorithm, we implement a multi-agent system (MAS) on top of a conventional development framework and assess the algorithm’s adaptability, satisfaction metric, and running time.

Suggested Citation

  • Yeongho Choi & Yujin Lim & Hak-Man Kim, 2017. "Optimal Load Shedding for Maximizing Satisfaction in an Islanded Microgrid," Energies, MDPI, vol. 10(1), pages 1-13, January.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:1:p:45-:d:86803
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    References listed on IDEAS

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    1. Yujin Lim & Hak-Man Kim & Tetsuo Kinoshita, 2014. "Distributed Load-Shedding System for Agent-Based Autonomous Microgrid Operations," Energies, MDPI, vol. 7(1), pages 1-17, January.
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    Cited by:

    1. Jinghan He & Ninghui Han & Ziqi Wang, 2021. "Optimization Method for Multiple Measures to Mitigate Line Overloads in Power Systems," Energies, MDPI, vol. 14(19), pages 1-19, September.
    2. Zizzo, G. & Beccali, M. & Bonomolo, M. & Di Pietra, B. & Ippolito, M.G. & La Cascia, D. & Leone, G. & Lo Brano, V. & Monteleone, F., 2017. "A feasibility study of some DSM enabling solutions in small islands: The case of Lampedusa," Energy, Elsevier, vol. 140(P1), pages 1030-1046.
    3. Robert Antonio Salas-Puente & Silvia Marzal & Raúl González-Medina & Emilio Figueres & Gabriel Garcera, 2018. "Power Management of the DC Bus Connected Converters in a Hybrid AC/DC Microgrid Tied to the Main Grid," Energies, MDPI, vol. 11(4), pages 1-22, March.
    4. Kai Wang & Lixia Kang & Songhao Yang, 2022. "A Coordination Optimization Method for Load Shedding Considering Distribution Network Reconfiguration," Energies, MDPI, vol. 15(21), pages 1-18, November.

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