Welfare Optimization in Energy Communities with P2P Markets

Optimización de bienestar en comunidades energéticas con mercados P2P

Authors

Keywords:

Energy Community, Energy Management System, Peer-to-Peer Market, Resource optimization

Abstract

We address the requirement for Energy Communities (ECs) to integrate efficient Energy Management Systems (EMSs) that optimize resource operation and maximize the benefits for participants. In this work, we implement an EMS that considers the supply and demand profiles of agents, fostering their engagement and ensuring their continued involvement within the community. We establish a mathematical model of an EC composed of prosumers with different types of distributed energy resources and pure consumers. The EMS integrates game theory and optimization techniques to coordinate and schedule energy transactions using welfare functions. Through the developed algorithm, the maximization of community welfare is ensured. This method is compared with the traditional Interior-Point Method (IPM). The results indicate a normalized error average of 0.23%. We simulate a community with six agents and analyze two case studies. The results show that the EMS promotes agent participation by optimizing their resources and achieving more competitive buy and sell prices compared to the main grid. Furthermore, the EMS prioritizes energy dispatch within the EC over transactions with the main grid and accounts for generation costs. The implementation of the EMS improves community welfare, thus contributing to the sustainability of the EC.

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Author Biographies

Sofía Chacón, Universidad de Nariño

Sofia Chacón is a physical and electronic engineer from the Universidad Nacional de Colombia, Manizales. She is currently pursuing a master's degree in Electronic Engineering from the Universidad de Nariño (Colombia). Additionally, she is certified in artificial intelligence. She works as a research assistant on project BPIN 2021000100499 focused on energy transactions for multiple agents. Her main research interests include energy management systems, optimization in power systems, game theory applications, distributed energy management, and peer-to-peer energy markets.

Katerine Guerrero, Fundación Centro de Investigación y Desarrollo Tecnológico en Ciencias Aplicadas - CIDTCA

Katerine Guerrero received the B.S. degree in electronics from Universidad de Nariño (Colombia), in 2007; the M.S. degree in electronics engineering from Pontificia Universidad Javerica - Cali (Colombia), in 2012; and the Ph.D. degree in engineering from Universidad del Valle (Colombia), in 2021. She has experience as professor of Universidad de Nariño and Universidad Mariana (Colombia), and as formulator, principal investigator and research coordinator of R&D projects funded by Minciencias and SGR (Colombia). Currently, Guerrero is the research coordinator of project BPIN 2021000100499, Universidad de Nariño, and the principal investigator of the project 100088 (posdoctoral fellowship at CIDTCA). Her research areas includes complex systems and energy management systems.

Germán Obando, Universidad de Narino

German Obando received the B.S. degree in electronics from Universidad de Nariño (Colombia), in 2008; the M.S. degree in electronics engineering from Universidad de los Andes (Colombia), in 2010; and the Ph.D. degree in engineering from Universidad de los Andes and Ecole des Mines de Nantes (France), in 2016. He joined the Department of Electronics of Universidad de Nariño in 2023, where he is currently an Associate Professor. His research interests include population dynamics, particularly the application of game theory to model engineering problems; distributed control, with a focus on consensus algorithms; and time-delayed systems.

Andrés Pantoja, Departamento de Electronica ´Universidad de Narino

Andrés Pantoja received the B.S. degree in electronics engineering from the Universidad Nacional - Manizales (Colombia), in 1999, and the M.S. and Ph.D. degrees in electronics engineering from the Universidad de los Andes (Colombia), in 2008 and 2012 respectively. In 2003, he joined the Department of Electronics of Universidad de Nariño (Colombia), where he is currently an Associate Professor and researcher with the GIIEE group. His areas of interest include distributed optimization, control systems, and optimization in microgrids.

References

E. Barabino, D. Fioriti, E. Guerrazzi, I. Mariuzzo, D. Poli, M. Raugi, E. Razaei, E. Schito, and D. Thomopulos, “Energy communities: A review on trends, energy system modelling, business models, and opti-misation objectives,” Sustainable Energy, Grids and Networks, vol. 36,p. 101187, 2023. https://doi.org/10.1016/j.segan.2023.101187.

W. Tushar, T. K. Saha, C. Yuen, D. Smith, and H. V. Poor, “Peer-to-peer trading in electricity networks: An overview,” IEEE Transactions on Smart Grid, vol. 11, no. 4, pp. 3185–3200, 2020. 10.1109/TSG.2020.2969657.

B. Mao, D. Han, Y. Wang, X. Dong, and Z. Yan, “Pricing mechanism for community prosumers in decentralized electricity market,” CSEE Journal of Power and Energy Systems, vol. 9, no. 5, pp. 1905–1917, 2023. 10.17775/CSEEJPES.2020.06480.

A. Paudel, K. Chaudhari, C. Long, and H. B. Gooi, “Peer-to-peer energy trading in a prosumer-based community microgrid: A game-theoretic model,” IEEE Transactions on Industrial Electronics, vol. 66, no. 8, pp. 6087–6097, 2019. 10.1109/TIE.2018.2874578.

T. Perger, “Fair energy sharing in local communities: Dynamic participation of prosumers,” in 2020 17th International Conferen-ce on the European Energy Market (EEM), pp. 1–6, IEEE, 2020. 10.1109/EEM49802.2020.9221933.

T. Perger and H. Auer, “Dynamic participation in local energy communi- ties with peer-to-peer trading,” Open Research Europe, vol. 2, pp. 5–20, 2022. 10.12688/openreseurope.14332.2.

M. Tofighi-Milani, S. Fattaheian-Dehkordi, M. Gholami, M. Fotuhi- Firuzabad, and M. Lehtonen, “A novel distributed paradigm for energy scheduling of islanded multiagent microgrids,” IEEE Access, vol. 10, pp. 83636–83649, 2022. 10.1109/ACCESS.2022.3197160.

Y. Xia, Q. Xu, S. Li, R. Tang, and P. Du, “Reviewing the peer- to-peer transactive energy market: Trading environment, optimization methodology, and relevant resources,” Journal of Cleaner Production, vol. 383, p. 135441, 2023. 10.1016/j.jclepro.2022.135441.

S. Suthar, S. H. C. Cherukuri, and N. M. Pindoriya, “Peer-to-peer energy trading in smart grid: Frameworks, implementation methodologies, and demonstration projects,” Electric Power Systems Research, vol. 214, p. 108907, 2023. 10.1016/j.epsr.2022.108907.

A. L. Bukar, M. F. Hamza, S. Ayub, A. K. Abobaker, B. Modu, S. Mohseni, A. C. Brent, C. Ogbonnaya, K. Mustapha, and H. O. Idakwo, “Peer-to-peer electricity trading: A systematic review on current developments and perspectives,” Renewable Energy Focus, vol. 44, pp. 317–333, 2023. 10.1016/j.ref.2023.01.008.

S. Xuanyue, X. Wang, X. Wu, Y. Wang, Z. Song, B. Wang, and Z. Ma, “Peer-to-peer multi-energy distributed trading for interconnected microgrids: A general Nash bargaining approach,” International Journal of Electrical Power & Energy Systems, vol. 138, p. 107892, 2022. https://doi.org/10.1016/j.ijepes.2021.107892.

X. Yu, D. Pan, and Y. Zhou, “A Stackelberg game-based peer-to-peer energy trading market with energy management and pricing mechanism: A case study in Guangzhou,” Solar Energy, vol. 270, p. 112388, 2024. https://doi.org/10.1016/j.solener.2024.112388.

D. Erazo-Caicedo, A. Cusva-Garc´ıa, N. Quijano, G. Jim´enez-Est´evez, J. Revelo-Fuelag´an, and A. Pantoja, “Differentiation price mechanism for loss minimization in peer-to-peer local energy markets,”

in 2024 IEEE ANDESCON, pp. 1–6, 2024. 10.1109/ANDES-CON61840.2024.10755935.

M. Choobineh, A. Arabnya, A. Khodaei, and H. Zheng, “Game-theoretic peer-to-peer solar energy trading on blockchain-based transaction infrastructure,” e-Prime-Advances in Electrical Engineering, Electronics and Energy, vol. 5, p. 100192, 2023. https://doi.org/10.1016/j.prime.2023.100192.

M. Khorasany, A. Paudel, R. Razzaghi, and P. Siano, “A new method for peer matching and negotiation of prosumers in peer-to-peer energy markets,” IEEE Transactions on Smart Grid, vol. 12, no. 3, pp. 2472–2483, 2021. 10.1109/TSG.2020.3048397.

A. Thomas, M. P. Abraham, and A. M. G, “Analysis of peer-to-peer energy trading in a dynamic environment using Stackelberg game,” in 2021 Seventh Indian Control Conference (ICC), pp. 412–417, 2021. 10.1109/ICC54714.2021.9703159.

D. Yang, Z. He, Y. Sun, B. Li, D. Li, X. Liu, and C. Jiang, “Optimised operation of integrated community energy system con-sidering integrated energy pricing strategy: A two-layer stackelberg game approach,” Journal of Energy Storage, vol. 87, p. 111383, 2024. https://doi.org/10.1016/j.est.2024.111383.

J. Liu, S. Y. Samson, H. Hu, and H. Trinh, “A combinato-rial auction energy trading approach for VPPs consisting of in-terconnected microgrids in demand-side ancillary services market,” Electric Power Systems Research, vol. 224, p. 109694, 2023. https://doi.org/10.1016/j.epsr.2023.109694.

X. Zhu, J. Xue, M. Hu, Z. Liu, X. Gao, and W. Huang, “Low-carbon economy dispatching of integrated energy system with P2G-HGT coupling wind power absorption based on stepped carbon emission trading,” Energy Reports, vol. 10, pp. 1753–1764, 2023. https://doi.org/10.1016/j.egyr.2023.08.023.

Y. Yang, X. Xu, L. Pan, J. Liu, J. Liu, and W. Hu, “Distributed prosumer trading in the electricity and carbon markets considering user utility,” Renewable Energy, vol. 228, p. 120669, 2024. https://doi.org/10.1016/j.renene.2024.120669.

COMISI ´ON DE REGULACI ´ON DE ENERG´IA Y GAS, “Proyecto de resoluci´on CREG 701 051 de 2024,” 2024. https://gestornormativo.creg.gov.co/.

Published

2025-06-26

How to Cite

Chacón, S., Guerrero, K., Obando, G. ., & Pantoja, A. . (2025). Welfare Optimization in Energy Communities with P2P Markets: Optimización de bienestar en comunidades energéticas con mercados P2P. IEEE Latin America Transactions, 23(8), 687–695. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/9626