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Virtual Power Plant Operational Strategies: Models, Markets, Optimization, Challenges, and Opportunities

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  • Mohammad Mohammadi Roozbehani

    (Department of Electrical and Computer Engineering, Qom University of Technology, Qom 37195-195, Iran)

  • Ehsan Heydarian-Forushani

    (Department of Electrical and Computer Engineering, Qom University of Technology, Qom 37195-195, Iran)

  • Saeed Hasanzadeh

    (Department of Electrical and Computer Engineering, Qom University of Technology, Qom 37195-195, Iran)

  • Seifeddine Ben Elghali

    (Laboratory of Information & Systems (LIS-UMR CNRS 7020), Aix-Marseille University, 13007 Marseille, France)

Abstract

High penetration of distributed generation and renewable energy sources in power systems has created control challenges in the network, which requires the coordinated management of these resources. Using virtual power plants (VPPs) on a large scale has solved these challenges to a significant extent. VPPs can be considered systems consisting of distributed generations, energy storage, controllable loads, electric vehicles (EVs), and other types of resources to provide energy and ancillary services. VPPs face various challenges such as energy management, operation, resource uncertainty, participation in electricity markets, etc. This paper discusses an overview of the basic challenges of VPPs, including control and communication issues, electricity markets, its different models, and energy management issues. The main purpose is to investigate the performance of VPP in different markets, energy management of VPP in different operating conditions and strategies, and compare different planning methods for VPP. Note that the application of blockchain to control and improve VPP performance has been investigated, taking into account the different layers of this technology.

Suggested Citation

  • Mohammad Mohammadi Roozbehani & Ehsan Heydarian-Forushani & Saeed Hasanzadeh & Seifeddine Ben Elghali, 2022. "Virtual Power Plant Operational Strategies: Models, Markets, Optimization, Challenges, and Opportunities," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12486-:d:930543
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    as
    1. Ju, Liwei & Tan, Zhongfu & Yuan, Jinyun & Tan, Qingkun & Li, Huanhuan & Dong, Fugui, 2016. "A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response," Applied Energy, Elsevier, vol. 171(C), pages 184-199.
    2. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    3. Zamani, Ali Ghahgharaee & Zakariazadeh, Alireza & Jadid, Shahram, 2016. "Day-ahead resource scheduling of a renewable energy based virtual power plant," Applied Energy, Elsevier, vol. 169(C), pages 324-340.
    4. Yang, Qing & Wang, Hao & Wang, Taotao & Zhang, Shengli & Wu, Xiaoxiao & Wang, Hui, 2021. "Blockchain-based decentralized energy management platform for residential distributed energy resources in a virtual power plant," Applied Energy, Elsevier, vol. 294(C).
    5. Ju, Liwei & Yin, Zhe & Zhou, Qingqing & Li, Qiaochu & Wang, Peng & Tian, Wenxu & Li, Peng & Tan, Zhongfu, 2022. "Nearly-zero carbon optimal operation model and benefit allocation strategy for a novel virtual power plant using carbon capture, power-to-gas, and waste incineration power in rural areas," Applied Energy, Elsevier, vol. 310(C).
    6. Tomasz Sikorski & Michał Jasiński & Edyta Ropuszyńska-Surma & Magdalena Węglarz & Dominika Kaczorowska & Paweł Kostyła & Zbigniew Leonowicz & Robert Lis & Jacek Rezmer & Wilhelm Rojewski & Marian Sobi, 2019. "A Case Study on Distributed Energy Resources and Energy-Storage Systems in a Virtual Power Plant Concept: Economic Aspects," Energies, MDPI, vol. 12(23), pages 1-21, November.
    7. Shabanzadeh, Morteza & Sheikh-El-Eslami, Mohammad-Kazem & Haghifam, Mahmoud-Reza, 2016. "A medium-term coalition-forming model of heterogeneous DERs for a commercial virtual power plant," Applied Energy, Elsevier, vol. 169(C), pages 663-681.
    8. Sinsel, Simon R. & Riemke, Rhea L. & Hoffmann, Volker H., 2020. "Challenges and solution technologies for the integration of variable renewable energy sources—a review," Renewable Energy, Elsevier, vol. 145(C), pages 2271-2285.
    9. Hadayeghparast, Shahrzad & SoltaniNejad Farsangi, Alireza & Shayanfar, Heidarali, 2019. "Day-ahead stochastic multi-objective economic/emission operational scheduling of a large scale virtual power plant," Energy, Elsevier, vol. 172(C), pages 630-646.
    10. Tajeddini, Mohammad Amin & Rahimi-Kian, Ashkan & Soroudi, Alireza, 2014. "Risk averse optimal operation of a virtual power plant using two stage stochastic programming," Energy, Elsevier, vol. 73(C), pages 958-967.
    11. Andoni, Merlinda & Robu, Valentin & Flynn, David & Abram, Simone & Geach, Dale & Jenkins, David & McCallum, Peter & Peacock, Andrew, 2019. "Blockchain technology in the energy sector: A systematic review of challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 143-174.
    12. Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2016. "Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy," Applied Energy, Elsevier, vol. 164(C), pages 590-606.
    13. Robu, Valentin & Chalkiadakis, Georgios & Kota, Ramachandra & Rogers, Alex & Jennings, Nicholas R., 2016. "Rewarding cooperative virtual power plant formation using scoring rules," Energy, Elsevier, vol. 117(P1), pages 19-28.
    14. Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2017. "A comprehensive review on microgrid and virtual power plant concepts employed for distributed energy resources scheduling in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 341-363.
    15. Rahmani-Dabbagh, Saeed & Sheikh-El-Eslami, Mohammad Kazem, 2016. "A profit sharing scheme for distributed energy resources integrated into a virtual power plant," Applied Energy, Elsevier, vol. 184(C), pages 313-328.
    16. Wang, Han & Riaz, Shariq & Mancarella, Pierluigi, 2020. "Integrated techno-economic modeling, flexibility analysis, and business case assessment of an urban virtual power plant with multi-market co-optimization," Applied Energy, Elsevier, vol. 259(C).
    17. Shayegan-Rad, Ali & Badri, Ali & Zangeneh, Ali, 2017. "Day-ahead scheduling of virtual power plant in joint energy and regulation reserve markets under uncertainties," Energy, Elsevier, vol. 121(C), pages 114-125.
    18. Kong, Xiangyu & Xiao, Jie & Wang, Chengshan & Cui, Kai & Jin, Qiang & Kong, Deqian, 2019. "Bi-level multi-time scale scheduling method based on bidding for multi-operator virtual power plant," Applied Energy, Elsevier, vol. 249(C), pages 178-189.
    19. Wilkens, Jens & Thulesius, Hans & Schmidt, Ingrid & Carlsson, Christina, 2016. "The 2015 National Cancer Program in Sweden: Introducing standardized care pathways in a decentralized system," Health Policy, Elsevier, vol. 120(12), pages 1378-1382.
    20. Tan, Caixia & Wang, Jing & Geng, Shiping & Pu, Lei & Tan, Zhongfu, 2021. "Three-level market optimization model of virtual power plant with carbon capture equipment considering copula–CVaR theory," Energy, Elsevier, vol. 237(C).
    21. Su, Yu-Wen, 2019. "Residential electricity demand in Taiwan: Consumption behavior and rebound effect," Energy Policy, Elsevier, vol. 124(C), pages 36-45.
    22. Zuoyu Liu & Weimin Zheng & Feng Qi & Lei Wang & Bo Zou & Fushuan Wen & You Xue, 2018. "Optimal Dispatch of a Virtual Power Plant Considering Demand Response and Carbon Trading," Energies, MDPI, vol. 11(6), pages 1-19, June.
    23. Soares, João & Fotouhi Ghazvini, Mohammad Ali & Vale, Zita & de Moura Oliveira, P.B., 2016. "A multi-objective model for the day-ahead energy resource scheduling of a smart grid with high penetration of sensitive loads," Applied Energy, Elsevier, vol. 162(C), pages 1074-1088.
    24. Adhikari, Arnab & Sharma, Megha & Basu, Sumanta & Jha, Ashish Kumar, 2022. "Uniform or spatially differentiated? Pricing Strategies for Information Goods under simultaneous and sequential decision-making in multi-market context," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    25. Wu, Wenqing & Huang, Xuan & Wu, Chia-Huei & Tsai, Sang-Bing, 2022. "Pricing strategy and performance investment decisions in competitive crowdfunding markets," Journal of Business Research, Elsevier, vol. 140(C), pages 491-497.
    26. Wei, Congying & Xu, Jian & Liao, Siyang & Sun, Yuanzhang & Jiang, Yibo & Ke, Deping & Zhang, Zhen & Wang, Jing, 2018. "A bi-level scheduling model for virtual power plants with aggregated thermostatically controlled loads and renewable energy," Applied Energy, Elsevier, vol. 224(C), pages 659-670.
    27. Luo, Xing & Wang, Jihong & Dooner, Mark & Clarke, Jonathan, 2015. "Overview of current development in electrical energy storage technologies and the application potential in power system operation," Applied Energy, Elsevier, vol. 137(C), pages 511-536.
    28. Pandžić, Hrvoje & Kuzle, Igor & Capuder, Tomislav, 2013. "Virtual power plant mid-term dispatch optimization," Applied Energy, Elsevier, vol. 101(C), pages 134-141.
    29. Yu, Songyuan & Fang, Fang & Liu, Yajuan & Liu, Jizhen, 2019. "Uncertainties of virtual power plant: Problems and countermeasures," Applied Energy, Elsevier, vol. 239(C), pages 454-470.
    30. Dong, Lianxin & Fan, Shuai & Wang, Zhihua & Xiao, Jucheng & Zhou, Huan & Li, Zuyi & He, Guangyu, 2021. "An adaptive decentralized economic dispatch method for virtual power plant," Applied Energy, Elsevier, vol. 300(C).
    31. Ramos, Carmen & García, Ana Salomé & Moreno, Blanca & Díaz, Guzmán, 2019. "Small-scale renewable power technologies are an alternative to reach a sustainable economic growth: Evidence from Spain," Energy, Elsevier, vol. 167(C), pages 13-25.
    32. Hany Elgamal, Ahmed & Kocher-Oberlehner, Gudrun & Robu, Valentin & Andoni, Merlinda, 2019. "Optimization of a multiple-scale renewable energy-based virtual power plant in the UK," Applied Energy, Elsevier, vol. 256(C).
    33. Steffen, Bjarne, 2020. "Estimating the cost of capital for renewable energy projects," Energy Economics, Elsevier, vol. 88(C).
    34. Pandžić, Hrvoje & Morales, Juan M. & Conejo, Antonio J. & Kuzle, Igor, 2013. "Offering model for a virtual power plant based on stochastic programming," Applied Energy, Elsevier, vol. 105(C), pages 282-292.
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    Cited by:

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    2. Lazar Gitelman & Mikhail Kozhevnikov, 2023. "New Business Models in the Energy Sector in the Context of Revolutionary Transformations," Sustainability, MDPI, vol. 15(4), pages 1-21, February.

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