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Multiple Objective Compromised Method for Power Management in Virtual Power Plants

Author

Listed:
  • Jinxia Gong

    (School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang, Shanghai 200240, China)

  • Da Xie

    (School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang, Shanghai 200240, China)

  • Chuanwen Jiang

    (School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang, Shanghai 200240, China)

  • Yanchi Zhang

    (Department of Automation, East China University of Science and Technology, Shanghai 200237, China)

Abstract

In practical optimization, a priority requirement for different objectives of multiple objective optimization problems should be considered. In this paper, the distributed power management of a Virtual Power Plant (VPP) with priority requirement is optimized by the compromised method. The operation optimization model of VPP is formulated as a fuzzy multiple objective optimization problem considering the satisfaction of customers and suppliers, the system stability, the power quality, and costs with operation limitations. The multiple objective optimization algorithm with the compromise of the satisfactory degree and the priority of objectives is studied based on the principle of two-step interactive satisfactory optimization. This method is also applied in a test system.

Suggested Citation

  • Jinxia Gong & Da Xie & Chuanwen Jiang & Yanchi Zhang, 2011. "Multiple Objective Compromised Method for Power Management in Virtual Power Plants," Energies, MDPI, vol. 4(4), pages 1-17, April.
    • Handle: RePEc:gam:jeners:v:4:y:2011:i:4:p:700-716:d:12144
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    References listed on IDEAS

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    1. Chen, Liang-Hsuan & Tsai, Feng-Chou, 2001. "Fuzzy goal programming with different importance and priorities," European Journal of Operational Research, Elsevier, vol. 133(3), pages 548-556, September.
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    Cited by:

    1. Amit Kumer Podder & Sayemul Islam & Nallapaneni Manoj Kumar & Aneesh A. Chand & Pulivarthi Nageswara Rao & Kushal A. Prasad & T. Logeswaran & Kabir A. Mamun, 2020. "Systematic Categorization of Optimization Strategies for Virtual Power Plants," Energies, MDPI, vol. 13(23), pages 1-46, November.
    2. Michał Jasiński & Tomasz Sikorski & Dominika Kaczorowska & Jacek Rezmer & Vishnu Suresh & Zbigniew Leonowicz & Paweł Kostyła & Jarosław Szymańda & Przemysław Janik & Jacek Bieńkowski & Przemysław Prus, 2021. "A Case Study on Data Mining Application in a Virtual Power Plant: Cluster Analysis of Power Quality Measurements," Energies, MDPI, vol. 14(4), pages 1-14, February.
    3. Jingmin Wang & Wenhai Yang & Huaxin Cheng & Lingyu Huang & Yajing Gao, 2017. "The Optimal Configuration Scheme of the Virtual Power Plant Considering Benefits and Risks of Investors," Energies, MDPI, vol. 10(7), pages 1-12, July.
    4. Luis Hernández-Callejo, 2019. "A Comprehensive Review of Operation and Control, Maintenance and Lifespan Management, Grid Planning and Design, and Metering in Smart Grids," Energies, MDPI, vol. 12(9), pages 1-50, April.
    5. Michal Jasiński & Tomasz Sikorski & Dominika Kaczorowska & Jacek Rezmer & Vishnu Suresh & Zbigniew Leonowicz & Paweł Kostyla & Jarosław Szymańda & Przemysław Janik, 2020. "A Case Study on Power Quality in a Virtual Power Plant: Long Term Assessment and Global Index Application," Energies, MDPI, vol. 13(24), pages 1-20, December.
    6. Syed Ali Abbas Kazmi & Muhammad Khuram Shahzad & Akif Zia Khan & Dong Ryeol Shin, 2017. "Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective," Energies, MDPI, vol. 10(4), pages 1-47, April.
    7. Michał Jasiński & Tomasz Sikorski & Dominika Kaczorowska & Jacek Rezmer & Vishnu Suresh & Zbigniew Leonowicz & Paweł Kostyła & Jarosław Szymańda & Przemysław Janik & Jacek Bieńkowski & Przemysław Prus, 2021. "A Case Study on a Hierarchical Clustering Application in a Virtual Power Plant: Detection of Specific Working Conditions from Power Quality Data," Energies, MDPI, vol. 14(4), pages 1-13, February.

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