RAS Energy, Mechanics & ControlИзвестия Российской академии наук. Энергетика Bulletin of the Russian Academy of Sciences. Energetics

  • ISSN (Print) 0002-3310
  • ISSN (Online) 3034-6495

Modeling the Behavior of Prosumers in Cooperation Using Agent Technologies

PII
S0002331025040038-1
DOI
10.31857/S0002331025040038
Publication type
Article
Status
Published
Authors
Volume/ Edition
Volume / Issue number 4
Pages
28-44
Abstract
The intelligent integration of electricity, heat, cold and gas supply systems is a promising technology for creating integrated energy systems. Within integrated energy systems, prosumers are widely developed, which have a significant impact on the operation of the system by regulating their load schedules and having energy sources independent of the centralized energy system. Management of integrated energy systems that include prosumers with their own energy sources is a complex task and requires the use of the latest methods and approaches that take into account the following features: complex behavior of objects of integrated energy systems, the presence of different interests among participants in the energy supply process. In connection with the listed features, this study proposes to use a multi-agent approach as a tool for research and optimal management of prosumers in integrated energy systems. To describe the interaction of the centralized system and prosumers in cooperation, a mathematical model has been developed that has a two-level hierarchical formulation. The structure of a multi-agent system is proposed, including three levels of interaction of agents, on the basis of which a number of experiments on the study of the interaction of prosumers in cooperation are carried out. The obtained results showed the effectiveness and efficiency of the proposed principles and mechanisms for organizing the interaction of a centralized system and prosumers during their cooperation in integrated energy systems.
Keywords
теория кооперативных игр мультиагентный подход агентное моделирование активные потребители интегрированная энергетическая система
Date of publication
14.09.2025
Year of publication
2025
Number of purchasers
0
Views
11

References

  1. 1. Voropai N.I., Stennikov V.A., Barakhtenko E.A. Integrated energy systems: challenges, trends, philosophy // Studies on Russian Economic Development, 2017. V. 28. № 5. P. 492–499.
  2. 2. Yang C., Liu J., Liao H., Liang G., Zhao J. An improved carbon emission flow method for the power grid with prosumers // Energy Reports, 2023. V. 9. P. 114–121.
  3. 3. Oprea S.V., Bára A. Generative literature analysis on the rise of prosumers and their influence on the sustainable energy transition // Utilities Policy, 2024. V. 90. 101799.
  4. 4. Mehdinejad M., Shayanfar H., Mohammadi-Ivaino B. Peer-to-peer decentralized energy trading framework for retailers and prosumers // Applied Energy, 2022. V. 308. 118310.
  5. 5. Pipiciello M., Caldera M., Cozzini M., Ancona M.A., Melino F., Di Pietra B. Experimental characterization of a prototype of bidirectional substation for district heating with thermal prosumers // Energy, 2021. V. 223. 120036.
  6. 6. Churkin A., Bialek J., Pozo D., Sauma E., Korgin N. Review of cooperative game theory applications in power system expansion planning // Renewable and Sustainable Energy Reviews, 2021. V. 145. 111056.
  7. 7. Gao Y., Zhou X., Ren J., Wang X., Li D. Double layer dynamic game bidding mechanism based on multi-agent technology for virtual power plant and internal distributed energy resource // Energies, 2018. V. 11. 3072.
  8. 8. Prete C.L., Hobbs B.F. A cooperative game theoretic analysis of incentives for microgrids in regulated electricity markets // Applied energy, 2016. V. 169. P. 524–541.
  9. 9. Khan M.W., Wang J., Xiong L., Ma M. Modelling and optimal management of distributed microgrid using multiagent systems // Sustainable Cities and Society, 2018. V. 41. P. 154–169.
  10. 10. Kyriakou D.G., Kanellos F.D., Ipsakis D. Multi-agent-based real-time operation of microgrids employing plug-in electric vehicles and building prosumers // Sustainable Energy, Grids and Networks, 2024. V. 37. 101229.
  11. 11. Gomes L., Vale Z., Corchado J.M. Microgrid management system based on a multi-agent approach: An office building pilot // Measurement, 2020. V. 154. 107427.
  12. 12. Stennikov V., Barakhtenko E., Mayorov G., Sokolov D., Zhou B. Coordinated management of centralized and distributed generation in an integrated energy system using a multi-agent approach // Applied Energy, 2022. V. 309. 118487.
  13. 13. May R., Huang P. A multi-agent reinforcement learning approach for investigating and optimising peer-to-peer prosumer energy markets // Applied Energy, 2023. V. 334. 120705.
  14. 14. Stennikov V., Barakhtenko E., Mayorov G. An approach to energy distribution between sources in a hierarchical integrated energy system using multi-agent technologies // Energy Reports, 2023. V. 9. P. 856–865.
  15. 15. Wooldridge M., Jennings N. Intelligent agents: theory and practice // The Knowledge Engineering Review, 1995. V. 10. № 2. P. 115–152.
  16. 16. Fisher K., Muller J.P., Heimig I., Scheer A-W. Intelligent agents in virtual enterprises // In Proceedings of the First International. Conference “The Practical Application of Intelligent Agents and Multi-Agent Technology”, London, UK, 1996. P. 205–224.
  17. 17. Peleg B., Sudhöller P. Introduction to the theory of cooperative games / Springer Berlin, Heidelberg, 2007.
  18. 18. Arrow K.J., Debreu G. Existence of an equilibrium for a competitive economy // Econometrica, 1954. V. 22. P. 265–290.
  19. 19. Fundenberg D., Tirole J. Game theory / Cambridge, Mass: The MIT Press, 1996.
  20. 20. Aizenberg N., Barakhtenko E., Mayorov G. Cooperative behavior of prosumers in integrated energy systems // Mathematics, 2024. V. 12(24). 4005.
QR
Translate

Индексирование

Scopus

Scopus

Scopus

Crossref

Scopus

Higher Attestation Commission

At the Ministry of Education and Science of the Russian Federation

Scopus

Scientific Electronic Library