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Impact of Demand Response Programs on Optimal Operation of Multi-Microgrid System

Author

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  • Anh-Duc Nguyen

    (Department of Electrical Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406840, Korea)

  • Van-Hai Bui

    (Department of Electrical Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406840, Korea)

  • Akhtar Hussain

    (Department of Electrical Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406840, Korea)

  • Duc-Huy Nguyen

    (Department of Electrical Engineering, Hanoi University of Science and Technology, Hanoi 112400, Vietnam)

  • Hak-Man Kim

    (Department of Electrical Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406840, Korea
    Research Institute for Northeast Asian Super Grid, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406840, Korea)

Abstract

The increased penetration of renewables is beneficial for power systems but it poses several challenges, i.e., uncertainty in power supply, power quality issues, and other technical problems. Backup generators or storage system have been proposed to solve this problem but there are limitations remaining due to high installation and maintenance cost. Furthermore, peak load is also an issue in the power distribution system. Due to the adjustable characteristics of loads, strategies on demand side such as demand response (DR) are more appropriate in order to deal with these challenges. Therefore, this paper studies how DR programs influence the operation of the multi-microgrid (MMG). The implementation is executed based on a hierarchical energy management system (HiEMS) including microgrid EMSs (MG-EMSs) responsible for local optimization in each MG and community EMS (C-EMS) responsible for community optimization in the MMG. Mixed integer linear programming (MILP)-based mathematical models are built for MMG optimal operation. Five scenarios consisting of single DR programs and DR groups are tested in an MMG test system to evaluate their impact on MMG operation. Among the five scenarios, some DR programs apply curtailing strategies, resulting in a study about the influence of base load value and curtailable load percentage on the amount of curtailed load and shifted load as well as the operation cost of the MMG. Furthermore, the impact of DR programs on the amount of external and internal trading power in the MMG is also examined. In summary, each individual DR program or group could be handy in certain situations depending on the interest of the MMG such as external trading, self-sufficiency or operation cost minimization.

Suggested Citation

  • Anh-Duc Nguyen & Van-Hai Bui & Akhtar Hussain & Duc-Huy Nguyen & Hak-Man Kim, 2018. "Impact of Demand Response Programs on Optimal Operation of Multi-Microgrid System," Energies, MDPI, vol. 11(6), pages 1-18, June.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1452-:d:150625
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    References listed on IDEAS

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    1. Songli Fan & Qian Ai & Longjian Piao, 2018. "Hierarchical Energy Management of Microgrids including Storage and Demand Response," Energies, MDPI, vol. 11(5), pages 1-23, May.
    2. Shakeel, Shah Rukh & Takala, Josu & Shakeel, Waqas, 2016. "Renewable energy sources in power generation in Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 421-434.
    3. Manfred Lenzen, 2010. "Current State of Development of Electricity-Generating Technologies: A Literature Review," Energies, MDPI, vol. 3(3), pages 1-130, March.
    4. Hee-Jun Cha & Dong-Jun Won & Sang-Hyuk Kim & Il-Yop Chung & Byung-Moon Han, 2015. "Multi-Agent System-Based Microgrid Operation Strategy for Demand Response," Energies, MDPI, vol. 8(12), pages 1-15, December.
    5. Mohammed, Y.S. & Mustafa, M.W. & Bashir, N. & Mokhtar, A.S., 2013. "Renewable energy resources for distributed power generation in Nigeria: A review of the potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 257-268.
    6. Faruqui, Ahmad & George, Stephen, 2005. "Quantifying Customer Response to Dynamic Pricing," The Electricity Journal, Elsevier, vol. 18(4), pages 53-63, May.
    7. Gyamfi, Samuel & Krumdieck, Susan & Urmee, Tania, 2013. "Residential peak electricity demand response—Highlights of some behavioural issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 71-77.
    8. Kris Kessels & Carolien Kraan & Ludwig Karg & Simone Maggiore & Pieter Valkering & Erik Laes, 2016. "Fostering Residential Demand Response through Dynamic Pricing Schemes: A Behavioural Review of Smart Grid Pilots in Europe," Sustainability, MDPI, vol. 8(9), pages 1-21, September.
    9. Simona-Vasilica Oprea & Adela Bâra & Adriana Reveiu, 2018. "Informatics Solution for Energy Efficiency Improvement and Consumption Management of Householders," Energies, MDPI, vol. 11(1), pages 1-31, January.
    10. Hak-Man Kim & Yujin Lim & Tetsuo Kinoshita, 2012. "An Intelligent Multiagent System for Autonomous Microgrid Operation," Energies, MDPI, vol. 5(9), pages 1-16, September.
    11. Akhtar Hussain & Van-Hai Bui & Hak-Man Kim, 2017. "Impact Analysis of Demand Response Intensity and Energy Storage Size on Operation of Networked Microgrids," Energies, MDPI, vol. 10(7), pages 1-19, June.
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