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Robust Optimization-Based Optimal Operation of Islanded Microgrid Considering Demand Response

Author

Listed:
  • Monir Sadat AlDavood

    (Science and Research Branch, Department of Electrical and Mechanical Engineering, Islamic Azad University, Tehran 14778-93855, Iran)

  • Abolfazl Mehbodniya

    (Department of Electronics and Communication Engineering, Kuwait College of Science and Technology (KCST), Doha Area, 7th Ring Road, Kuwait City 20185145, Kuwait)

  • Julian L. Webber

    (Department of Electronics and Communication Engineering, Kuwait College of Science and Technology (KCST), Doha Area, 7th Ring Road, Kuwait City 20185145, Kuwait)

  • Mohammad Ensaf

    (Chemical Engineering Department, Sharif University of Technology, Tehran 1136511155, Iran)

  • Mahdi Azimian

    (Department of Electrical and Computer Engineering, Kashan Branch, Islamic Azad University, Kashan 8715998151, Iran)

Abstract

This paper presents a new robust scheduling model for an islanded microgrid (MG) considering demand response. The model is expressed as a min–max bilevel optimization problem that tries to minimize the total costs of MG including operation cost of conventional distributed generators, energy storages, renewable energy sources (RES), cost of load shifting, and interruptible/non-interruptible load shedding in the worst situation of uncertainties. The uncertainties associated with renewable power generations and MG demand are modeled via robust optimization method. A hybrid method based on the genetic algorithm (GA) and mixed-integer programming technique is utilized to solve the bilevel optimization problem. The proposed model is utilized on a typical MG, and the outcomes are analyzed to show the effectiveness of the proposed method.

Suggested Citation

  • Monir Sadat AlDavood & Abolfazl Mehbodniya & Julian L. Webber & Mohammad Ensaf & Mahdi Azimian, 2022. "Robust Optimization-Based Optimal Operation of Islanded Microgrid Considering Demand Response," Sustainability, MDPI, vol. 14(21), pages 1-17, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14194-:d:958687
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    References listed on IDEAS

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    1. Xiao, Yiyong & Zhang, Yue & Kaku, Ikou & Kang, Rui & Pan, Xing, 2021. "Electric vehicle routing problem: A systematic review and a new comprehensive model with nonlinear energy recharging and consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    2. Elgamal, M. & Korovkin, Nikolay & Abdel Menaem, A. & Elmitwally, Akram, 2022. "Day-ahead complex power scheduling in a reconfigurable hybrid-energy islanded microgrid with responsive demand considering uncertainty and different load models," Applied Energy, Elsevier, vol. 309(C).
    3. Azimian, Mahdi & Amir, Vahid & Javadi, Saeid, 2020. "Economic and Environmental Policy Analysis for Emission-Neutral Multi-Carrier Microgrid Deployment," Applied Energy, Elsevier, vol. 277(C).
    4. Karimi, Hamid & Jadid, Shahram, 2020. "Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework," Energy, Elsevier, vol. 195(C).
    5. Hessam Golmohamadi, 2022. "Demand-Side Flexibility in Power Systems: A Survey of Residential, Industrial, Commercial, and Agricultural Sectors," Sustainability, MDPI, vol. 14(13), pages 1-16, June.
    6. Mahyar Alinejad & Omid Rezaei & Reza Habibifar & Mahdi Azimian, 2022. "A Charge/Discharge Plan for Electric Vehicles in an Intelligent Parking Lot Considering Destructive Random Decisions, and V2G and V2V Energy Transfer Modes," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
    7. Golmohamadi, Hessam, 2022. "Demand-side management in industrial sector: A review of heavy industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    8. Abdul Wahid & Javed Iqbal & Affaq Qamar & Salman Ahmed & Abdul Basit & Haider Ali & Omar M. Aldossary, 2020. "A Novel Power Scheduling Mechanism for Islanded DC Microgrid Cluster," Sustainability, MDPI, vol. 12(17), pages 1-14, August.
    9. Zia, Muhammad Fahad & Elbouchikhi, Elhoussin & Benbouzid, Mohamed, 2018. "Microgrids energy management systems: A critical review on methods, solutions, and prospects," Applied Energy, Elsevier, vol. 222(C), pages 1033-1055.
    10. Guodong Liu & Thomas B. Ollis & Maximiliano F. Ferrari & Aditya Sundararajan & Kevin Tomsovic, 2022. "Robust Scheduling of Networked Microgrids for Economics and Resilience Improvement," Energies, MDPI, vol. 15(6), pages 1-19, March.
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    Cited by:

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    3. Priyadharshini Ramu & Sivasankar Gangatharan & Sankar Rangasamy & Lucian Mihet-Popa, 2023. "Categorization of Loads in Educational Institutions to Effectively Manage Peak Demand and Minimize Energy Cost Using an Intelligent Load Management Technique," Sustainability, MDPI, vol. 15(16), pages 1-28, August.
    4. Yujiang Ye & Ruifeng Shi & Yuqin Gao & Xiaolei Ma & Di Wang, 2023. "Two-Stage Optimal Scheduling of Highway Self-Consistent Energy System in Western China," Energies, MDPI, vol. 16(5), pages 1-18, March.

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