IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v217y2025ics1364032125003922.html
   My bibliography  Save this article

Carbon-billed future for virtual power plants: A comprehensive review

Author

Listed:
  • Wang, Guotao
  • Lin, Zhenjia
  • Chen, Yuntian
  • Qiu, Rui
  • Zhang, Haoran
  • Yan, Jinyue

Abstract

Virtual power plants function as pivotal platforms for managing operations and facilitating transactions, significantly enhancing the visibility and collaborative operational efficiency of distributed energy resources within the main power grid. With the increasing focus on carbon reduction in the power sector, carbon trading is increasingly being integrated into virtual power plants in related research. However, a comprehensive review of carbon trading connected virtual power plants is still lacking. Therefore, this study conducts a comprehensive review and analysis of how a carbon-constrained future impacts the development and research directions of virtual power plants. An in-depth evaluation of carbon flow modeling methods employed in virtual power plants operations is provided, highlighting their respective advantages, limitations, and practical application scenarios. It analyzes how carbon transactions can be effectively integrated with the electricity market through virtual power plants and reviews the roles of virtual power plants in facilitating carbon reduction. By summarizing real-world VPPs projects, this work highlights current achievements and outlines future challenges and opportunities. It underscores the importance of developing uniform carbon accounting mechanism for market participates and electricity-carbon market coordinative scheduling method, crucial for achieving economic efficiency and social fairness in the transitioning energy sector. Additionally, further research should focus on developing new business models and advanced engagement strategies to increase consumer participation in virtual power plants.

Suggested Citation

  • Wang, Guotao & Lin, Zhenjia & Chen, Yuntian & Qiu, Rui & Zhang, Haoran & Yan, Jinyue, 2025. "Carbon-billed future for virtual power plants: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 217(C).
    • Handle: RePEc:eee:rensus:v:217:y:2025:i:c:s1364032125003922
    DOI: 10.1016/j.rser.2025.115719
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032125003922
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2025.115719?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. D. M. Davies & M. G. Verde & O. Mnyshenko & Y. R. Chen & R. Rajeev & Y. S. Meng & G. Elliott, 2019. "Combined economic and technological evaluation of battery energy storage for grid applications," Nature Energy, Nature, vol. 4(1), pages 42-50, January.
    2. Chang, Xin & Wu, Zhaoyuan & Wang, Jingting & Zhang, Xingyu & Zhou, Ming & Yu, Tao & Wang, Yuyang, 2023. "The coupling effect of carbon emission trading and tradable green certificates under electricity marketization in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    3. Feng, Huchen & Hu, Yu-Jie & Li, Chengjiang & Wang, Honglei, 2023. "Rolling horizon optimisation strategy and initial carbon allowance allocation model to reduce carbon emissions in the power industry: Case of China," Energy, Elsevier, vol. 277(C).
    4. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    5. Bhuiyan, Erphan A. & Hossain, Md. Zahid & Muyeen, S.M. & Fahim, Shahriar Rahman & Sarker, Subrata K. & Das, Sajal K., 2021. "Towards next generation virtual power plant: Technology review and frameworks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    6. Yihsu Chen & Jos Sijm & Benjamin Hobbs & Wietze Lise, 2008. "Implications of CO 2 emissions trading for short-run electricity market outcomes in northwest Europe," Journal of Regulatory Economics, Springer, vol. 34(3), pages 251-281, December.
    7. Rehman, Shafiqur & Al-Hadhrami, Luai M. & Alam, Md. Mahbub, 2015. "Pumped hydro energy storage system: A technological review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 586-598.
    8. Wang, Yun & Xie, Haipeng & Sun, Xiaotian & Tang, Lingfeng & Bie, Zhaohong, 2022. "A cross-chain enabled day-ahead collaborative power-carbon-TGC market," Energy, Elsevier, vol. 258(C).
    9. Ping Ma & Shuhui Cui & Mingshuai Chen & Shengzhe Zhou & Kai Wang, 2023. "Review of Family-Level Short-Term Load Forecasting and Its Application in Household Energy Management System," Energies, MDPI, vol. 16(15), pages 1-17, August.
    10. Sheng, Xuerou & Chen, Leping & Liu, Mengyue & Wang, Qingsong & Ma, Qiao & Zuo, Jian & Yuan, Xueliang, 2025. "Input-output models for carbon accounting: A multi-perspective analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
    11. Wakiyama, Takako & Kuriyama, Akihisa, 2018. "Assessment of renewable energy expansion potential and its implications on reforming Japan's electricity system," Energy Policy, Elsevier, vol. 115(C), pages 302-316.
    12. Huiru Zhao & Chao Zhang & Yihang Zhao & Xuejie Wang, 2022. "Low-Carbon Economic Dispatching of Multi-Energy Virtual Power Plant with Carbon Capture Unit Considering Uncertainty and Carbon Market," Energies, MDPI, vol. 15(19), pages 1-25, October.
    13. Li, Yaowang & Yang, Xuxin & Du, Ershun & Liu, Yuliang & Zhang, Shixu & Yang, Chen & Zhang, Ning & Liu, Chang, 2024. "A review on carbon emission accounting approaches for the electricity power industry," Applied Energy, Elsevier, vol. 359(C).
    14. Singh, Nitin & Mohanty, Soumya Ranjan & Dev Shukla, Rishabh, 2017. "Short term electricity price forecast based on environmentally adapted generalized neuron," Energy, Elsevier, vol. 125(C), pages 127-139.
    15. Zhu, Bangzhu & Han, Dong & Chevallier, Julien & Wei, Yi-Ming, 2017. "Dynamic multiscale interactions between European carbon and electricity markets during 2005–2016," Energy Policy, Elsevier, vol. 107(C), pages 309-322.
    16. Li, Wei & Becker, Denis Mike, 2021. "Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling," Energy, Elsevier, vol. 237(C).
    17. Panapakidis, Ioannis P. & Dagoumas, Athanasios S., 2016. "Day-ahead electricity price forecasting via the application of artificial neural network based models," Applied Energy, Elsevier, vol. 172(C), pages 132-151.
    18. Loßner, Martin & Böttger, Diana & Bruckner, Thomas, 2017. "Economic assessment of virtual power plants in the German energy market — A scenario-based and model-supported analysis," Energy Economics, Elsevier, vol. 62(C), pages 125-138.
    19. Franco, Carlos J. & Castaneda, Monica & Dyner, Isaac, 2015. "Simulating the new British Electricity-Market Reform," European Journal of Operational Research, Elsevier, vol. 245(1), pages 273-285.
    20. Wang, Xuejie & zhao, Huiru & Lu, Hao & Zhang, Yuanyuan & Wang, Yuwei & Wang, Jingbo, 2022. "Decentralized coordinated operation model of VPP and P2H systems based on stochastic-bargaining game considering multiple uncertainties and carbon cost," Applied Energy, Elsevier, vol. 312(C).
    21. George Daskalakis & Lazaros Symeonidis & Raphael N. Markellos, 2015. "Electricity Futures Prices in an Emissions Constrained Economy: Evidence from European Power Markets," The Energy Journal, , vol. 36(3), pages 1-34, July.
    22. Budt, Marcus & Wolf, Daniel & Span, Roland & Yan, Jinyue, 2016. "A review on compressed air energy storage: Basic principles, past milestones and recent developments," Applied Energy, Elsevier, vol. 170(C), pages 250-268.
    23. Song, Yazhi & Liu, Tiansen & Ye, Bin & Li, Yin, 2020. "Linking carbon market and electricity market for promoting the grid parity of photovoltaic electricity in China," Energy, Elsevier, vol. 211(C).
    24. 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.
    25. Guo, Hongye & Davidson, Michael R. & Chen, Qixin & Zhang, Da & Jiang, Nan & Xia, Qing & Kang, Chongqing & Zhang, Xiliang, 2020. "Power market reform in China: Motivations, progress, and recommendations," Energy Policy, Elsevier, vol. 145(C).
    26. Haben, Stephen & Arora, Siddharth & Giasemidis, Georgios & Voss, Marcus & Vukadinović Greetham, Danica, 2021. "Review of low voltage load forecasting: Methods, applications, and recommendations," Applied Energy, Elsevier, vol. 304(C).
    27. Mousavi G, S.M. & Faraji, Faramarz & Majazi, Abbas & Al-Haddad, Kamal, 2017. "A comprehensive review of Flywheel Energy Storage System technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 477-490.
    28. Chang, Weiguang & Yang, Qiang, 2023. "Low carbon oriented collaborative energy management framework for multi-microgrid aggregated virtual power plant considering electricity trading," Applied Energy, Elsevier, vol. 351(C).
    29. Smith, Alexander M. & Brown, Marilyn A., 2015. "Demand response: A carbon-neutral resource?," Energy, Elsevier, vol. 85(C), pages 10-22.
    30. Zhao, Ning & You, Fengqi, 2020. "Can renewable generation, energy storage and energy efficient technologies enable carbon neutral energy transition?," Applied Energy, Elsevier, vol. 279(C).
    31. Shahram Hanifi & Xiaolei Liu & Zi Lin & Saeid Lotfian, 2020. "A Critical Review of Wind Power Forecasting Methods—Past, Present and Future," Energies, MDPI, vol. 13(15), pages 1-24, July.
    32. 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.
    33. Mahmud, Khizir & Khan, Behram & Ravishankar, Jayashri & Ahmadi, Abdollah & Siano, Pierluigi, 2020. "An internet of energy framework with distributed energy resources, prosumers and small-scale virtual power plants: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    34. Naval, Natalia & Yusta, Jose M., 2021. "Virtual power plant models and electricity markets - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    35. Tascikaraoglu, A. & Erdinc, O. & Uzunoglu, M. & Karakas, A., 2014. "An adaptive load dispatching and forecasting strategy for a virtual power plant including renewable energy conversion units," Applied Energy, Elsevier, vol. 119(C), pages 445-453.
    36. Alva, Guruprasad & Lin, Yaxue & Fang, Guiyin, 2018. "An overview of thermal energy storage systems," Energy, Elsevier, vol. 144(C), pages 341-378.
    37. Gavrilova, Olga & Jonas, Matthias & Erb, Karlheinz & Haberl, Helmut, 2010. "International trade and Austria's livestock system: Direct and hidden carbon emission flows associated with production and consumption of products," Ecological Economics, Elsevier, vol. 69(4), pages 920-929, February.
    38. Olabi, A.G. & Onumaegbu, C. & Wilberforce, Tabbi & Ramadan, Mohamad & Abdelkareem, Mohammad Ali & Al – Alami, Abdul Hai, 2021. "Critical review of energy storage systems," Energy, Elsevier, vol. 214(C).
    39. Naval, Natalia & Sánchez, Raul & Yusta, Jose M., 2020. "A virtual power plant optimal dispatch model with large and small-scale distributed renewable generation," Renewable Energy, Elsevier, vol. 151(C), pages 57-69.
    40. Li, Yan & Feng, Tian-tian & Liu, Li-li & Zhang, Meng-xi, 2023. "How do the electricity market and carbon market interact and achieve integrated development?--A bibliometric-based review," Energy, Elsevier, vol. 265(C).
    41. 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.
    42. Khalil Gholami & Behnaz Behi & Ali Arefi & Philip Jennings, 2022. "Grid-Forming Virtual Power Plants: Concepts, Technologies and Advantages," Energies, MDPI, vol. 15(23), pages 1-26, November.
    43. Ibrahim Salem Jahan & Vaclav Snasel & Stanislav Misak, 2020. "Intelligent Systems for Power Load Forecasting: A Study Review," Energies, MDPI, vol. 13(22), pages 1-12, November.
    44. Guo, Yi & Han, Xuejiao & Zhou, Xinyang & Hug, Gabriela, 2023. "Incorporate day-ahead robustness and real-time incentives for electricity market design," Applied Energy, Elsevier, vol. 332(C).
    45. Abdul Ghani Olabi & Tabbi Wilberforce & Mohammad Ali Abdelkareem & Mohamad Ramadan, 2021. "Critical Review of Flywheel Energy Storage System," Energies, MDPI, vol. 14(8), pages 1-33, April.
    46. Gao, Hongchao & Jin, Tai & Feng, Cheng & Li, Chuyi & Chen, Qixin & Kang, Chongqing, 2024. "Review of virtual power plant operations: Resource coordination and multidimensional interaction," Applied Energy, Elsevier, vol. 357(C).
    47. Arslan, Okan & Karasan, Oya Ekin, 2013. "Cost and emission impacts of virtual power plant formation in plug-in hybrid electric vehicle penetrated networks," Energy, Elsevier, vol. 60(C), pages 116-124.
    48. Wei Li & Denis Mike Becker, 2021. "Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling," Papers 2101.05249, arXiv.org, revised Jul 2021.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kaiss, Mateus & Wan, Yihao & Gebbran, Daniel & Vila, Clodomiro Unsihuay & Dragičević, Tomislav, 2025. "Review on Virtual Power Plants/Virtual Aggregators: Concepts, applications, prospects and operation strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 211(C).
    2. 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.
    3. Gao, Hongchao & Jin, Tai & Feng, Cheng & Li, Chuyi & Chen, Qixin & Kang, Chongqing, 2024. "Review of virtual power plant operations: Resource coordination and multidimensional interaction," Applied Energy, Elsevier, vol. 357(C).
    4. Li, Yan & Feng, Tian-tian & Liu, Li-li & Zhang, Meng-xi, 2023. "How do the electricity market and carbon market interact and achieve integrated development?--A bibliometric-based review," Energy, Elsevier, vol. 265(C).
    5. Xie, Haonan & Ahmad, Tanveer & Zhang, Dongdong & Goh, Hui Hwang & Wu, Thomas, 2024. "Community-based virtual power plants’ technology and circular economy models in the energy sector: A Techno-economy study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    6. Mahmud, Khizir & Khan, Behram & Ravishankar, Jayashri & Ahmadi, Abdollah & Siano, Pierluigi, 2020. "An internet of energy framework with distributed energy resources, prosumers and small-scale virtual power plants: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    7. Sun, Yaling & Che, Yanbo & Guo, Xiao & Zhang, Shangyuan, 2025. "Optimal modelling and analysis of DG-GC joint multilateral transaction in energy blockchain environment: from the REP perspective," Energy, Elsevier, vol. 335(C).
    8. Zheng, Zixuan & Li, Jie & Liu, Xiaoming & Huang, Chunjun & Hu, Wenxi & Xiao, Xianyong & Zhang, Shu & Zhou, Yongjun & Yue, Song & Zong, Yi, 2025. "A De-aggregation strategy based optimal co-scheduling of heterogeneous flexible resources in virtual power plant," Applied Energy, Elsevier, vol. 383(C).
    9. Jiang, Yuzheng & Dong, Jun & Huang, Hexiang, 2024. "Optimal bidding strategy for the price-maker virtual power plant in the day-ahead market based on multi-agent twin delayed deep deterministic policy gradient algorithm," Energy, Elsevier, vol. 306(C).
    10. 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.
    11. Mejia, Cristian & Kajikawa, Yuya, 2020. "Emerging topics in energy storage based on a large-scale analysis of academic articles and patents," Applied Energy, Elsevier, vol. 263(C).
    12. Naval, Natalia & Yusta, Jose M., 2021. "Virtual power plant models and electricity markets - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    13. Esfahani, Moein & Alizadeh, Ali & Cao, Bo & Kamwa, Innocent & Xu, Minghui, 2025. "Bridging theory and practice: A comprehensive review of virtual power plant technologies and their real-world applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 222(C).
    14. 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.
    15. Fang Guo & Shangyun Deng & Weijia Zheng & An Wen & Jinfeng Du & Guangshan Huang & Ruiyang Wang, 2022. "Short-Term Electricity Price Forecasting Based on the Two-Layer VMD Decomposition Technique and SSA-LSTM," Energies, MDPI, vol. 15(22), pages 1-20, November.
    16. Toufani, Parinaz & Nadar, Emre & Kocaman, Ayse Selin, 2022. "Short-term assessment of pumped hydro energy storage configurations: Up, down, or closed?," Renewable Energy, Elsevier, vol. 201(P1), pages 1086-1095.
    17. Dounia El Bourakadi & Hiba Ramadan & Ali Yahyaouy & Jaouad Boumhidi, 2023. "A robust energy management approach in two-steps ahead using deep learning BiLSTM prediction model and type-2 fuzzy decision-making controller," Fuzzy Optimization and Decision Making, Springer, vol. 22(4), pages 645-667, December.
    18. Madadkhani, Shiva & Ikonnikova, Svetlana, 2024. "Toward high-resolution projection of electricity prices: A machine learning approach to quantifying the effects of high fuel and CO2 prices," Energy Economics, Elsevier, vol. 129(C).
    19. 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.
    20. Ghorbani, Narges & Sihvonen, Ville & Gulagi, Ashish & Makian, Hamed & Breyer, Christian & Honkapuro, Samuli, 2025. "Developing a replicable methodology for assessing pumped hydro energy storage potential: Mapping, estimation, and economic analysis," Energy, Elsevier, vol. 334(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:217:y:2025:i:c:s1364032125003922. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.