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Systematic Categorization of Optimization Strategies for Virtual Power Plants

Author

Listed:
  • Amit Kumer Podder

    (Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh)

  • Sayemul Islam

    (Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna 9203, Bangladesh)

  • Nallapaneni Manoj Kumar

    (School of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong)

  • Aneesh A. Chand

    (School of Engineering and Physics, The University of the South Pacific, Suva, Fiji)

  • Pulivarthi Nageswara Rao

    (Department of Electrical Electronics and Communication Engineering, Gandhi Institute of Technology and Management (Deemed to be University), Visakhapatnam 530045, Andhra Pradesh, India)

  • Kushal A. Prasad

    (School of Engineering and Physics, The University of the South Pacific, Suva, Fiji)

  • T. Logeswaran

    (Department of Electrical and Electronics Engineering, Kongu Engineering College, Perundurai, Erode 638060, Tamil Nadu, India)

  • Kabir A. Mamun

    (School of Engineering and Physics, The University of the South Pacific, Suva, Fiji)

Abstract

Due to the rapid growth in power consumption of domestic and industrial appliances, distributed energy generation units face difficulties in supplying power efficiently. The integration of distributed energy resources (DERs) and energy storage systems (ESSs) provides a solution to these problems using appropriate management schemes to achieve optimal operation. Furthermore, to lessen the uncertainties of distributed energy management systems, a decentralized energy management system named virtual power plant (VPP) plays a significant role. This paper presents a comprehensive review of 65 existing different VPP optimization models, techniques, and algorithms based on their system configuration, parameters, and control schemes. Moreover, the paper categorizes the discussed optimization techniques into seven different types, namely conventional technique, offering model, intelligent technique, price-based unit commitment (PBUC) model, optimal bidding, stochastic technique, and linear programming, to underline the commercial and technical efficacy of VPP at day-ahead scheduling at the electricity market. The uncertainties of market prices, load demand, and power distribution in the VPP system are mentioned and analyzed to maximize the system profits with minimum cost. The outcome of the systematic categorization is believed to be a base for future endeavors in the field of VPP development.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:23:p:6251-:d:452165
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    References listed on IDEAS

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    3. Lucas Feksa Ramos & Luciane Neves Canha & Josue Campos do Prado & Leonardo Rodrigues Araujo Xavier de Menezes, 2022. "A Novel Virtual Power Plant Uncertainty Modeling Framework Using Unscented Transform," Energies, MDPI, vol. 15(10), pages 1-13, May.
    4. Mulusew Ayalew & Baseem Khan & Issaias Giday & Om Prakash Mahela & Mahdi Khosravy & Neeraj Gupta & Tomonobu Senjyu, 2022. "Integration of Renewable Based Distributed Generation for Distribution Network Expansion Planning," Energies, MDPI, vol. 15(4), pages 1-17, February.
    5. Aleksandra V. Varganova & Vadim R. Khramshin & Andrey A. Radionov, 2022. "Improving Efficiency of Electric Energy System and Grid Operating Modes: Review of Optimization Techniques," Energies, MDPI, vol. 15(19), pages 1-16, September.
    6. Aleksandra V. Varganova & Vadim R. Khramshin & Andrey A. Radionov, 2023. "Operating Modes Optimization for the Boiler Units of Industrial Steam Plants," Energies, MDPI, vol. 16(6), pages 1-14, March.

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