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A Mixed-Integer Programming Approach for Unit Commitment in Micro-Grid with Incentive-Based Demand Response and Battery Energy Storage System

Author

Listed:
  • Tuyen Nguyen-Duc

    (School of Electrical Engineering, Hanoi University of Science and Technology, Hanoi 11615, Vietnam
    Department of Electrical Engineering, Shibaura Institute of Technology, Tokyo 135-8548, Japan)

  • Linh Hoang-Tuan

    (School of Electrical Engineering, Hanoi University of Science and Technology, Hanoi 11615, Vietnam)

  • Hung Ta-Xuan

    (School of Electrical Engineering, Hanoi University of Science and Technology, Hanoi 11615, Vietnam)

  • Long Do-Van

    (School of Electrical Engineering, Hanoi University of Science and Technology, Hanoi 11615, Vietnam)

  • Hirotaka Takano

    (Department of Electrical, Electronic and Computer Engineering, Gifu University, Gifu 501-1193, Japan)

Abstract

In the context of the increasing penetration of intermittent renewable energy resources (RES), one of the significant challenges facing traditional bulk power systems and microgrids is the scheduling generation units problem. Many studies have focused on solving the energy management problem for microgrids integrating RES. To address the intermittency caused by RES, flexible components such as battery energy storage systems (BESS) or demand response (DR) are considered. To clarify the problem of integrating these flexible components, a mixed-integer programming (MIP) approach for the unit commitment (UC) problem for microgrids with BESS and DR is proposed in this paper. An incentive-based demand response model as a negative power source and a detailed model for the vanadium redox battery (VRB) are introduced to improve the efficiency and reliability of microgrids. The objective optimization function, including the costs of generation, emissions, and maintenance, is minimized considering the uncertainty of the load and renewable energy sources. The obtained simulation results are compared with the genetic algorithm (GA) method as the basis for verification in different case studies. The obtained results have clarified the effect of using the BESS model and DR program on system operation.

Suggested Citation

  • Tuyen Nguyen-Duc & Linh Hoang-Tuan & Hung Ta-Xuan & Long Do-Van & Hirotaka Takano, 2022. "A Mixed-Integer Programming Approach for Unit Commitment in Micro-Grid with Incentive-Based Demand Response and Battery Energy Storage System," Energies, MDPI, vol. 15(19), pages 1-26, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:19:p:7192-:d:929579
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    References listed on IDEAS

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    1. Cagnano, A. & De Tuglie, E. & Mancarella, P., 2020. "Microgrids: Overview and guidelines for practical implementations and operation," Applied Energy, Elsevier, vol. 258(C).
    2. Astriani, Yuli & Shafiullah, GM & Shahnia, Farhad, 2021. "Incentive determination of a demand response program for microgrids," Applied Energy, Elsevier, vol. 292(C).
    3. Bernard Knueven & James Ostrowski & Jean-Paul Watson, 2020. "On Mixed-Integer Programming Formulations for the Unit Commitment Problem," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 857-876, October.
    4. L. Alvarado-Barrios & A. Rodríguez del Nozal & A. Tapia & J. L. Martínez-Ramos & D. G. Reina, 2019. "An Evolutionary Computational Approach for the Problem of Unit Commitment and Economic Dispatch in Microgrids under Several Operation Modes," Energies, MDPI, vol. 12(11), pages 1-23, June.
    5. Gomes, I.L.R. & Melicio, R. & Mendes, V.M.F., 2021. "A novel microgrid support management system based on stochastic mixed-integer linear programming," Energy, Elsevier, vol. 223(C).
    6. Masoud Dashtdar & Aymen Flah & Seyed Mohammad Sadegh Hosseinimoghadam & Hossam Kotb & Elżbieta Jasińska & Radomir Gono & Zbigniew Leonowicz & Michał Jasiński, 2022. "Optimal Operation of Microgrids with Demand-Side Management Based on a Combination of Genetic Algorithm and Artificial Bee Colony," Sustainability, MDPI, vol. 14(11), pages 1-26, May.
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