A new decentralized Multi-agent System for Peer-to-Peer energy market considering variable prosumer penetration with privacy protection

GÖKÇEK T., Turan M. T., Ateş Y.

Sustainable Energy, Grids and Networks, vol.38, 2024 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 38
  • Publication Date: 2024
  • Doi Number: 10.1016/j.segan.2024.101328
  • Journal Name: Sustainable Energy, Grids and Networks
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
  • Keywords: ADMM, Distributed optimization, Electric vehicle, Multi-agent system, Peer-to-peer energy trading
  • Yıldız Technical University Affiliated: Yes


The requirement of large scale optimization of the power system environment brings out decentralized solutions in terms of applicability and economic feasibility, and trade relationship between prosumers at different power levels fed from the same point of common coupling point is important for a balanced economic profit. Moreover, ideal segmentation with a large scale participation is another economic issue in terms of allocation of total profit among aggregators. In this context, this study proposes a decentralized Peer-to-Peer (P2P) market incorporating Multi-agent System (MAS) which consists different three agents with variable power levels. In the MAS environment, while Agent-1 represents a community which has variable household number according to the case studies, Agent-2 is an independent aggregator who is not included in, and does not influence the transactions of the Agent-1. Finally, Agent-3 is the ENKA Insaat ve Sanayi A.S. which has office buildings equipped with electric vehicle parking lot (EVPL) and photovoltaic (PV) panels. In the paper, all the agents simultaneously solve their own sub-problems by distributed way according to the received dynamic price signals along with the availability of the responsive demands. Moreover, 132 case studies consisting of low, medium, and large scale with different prosumer penetration are created in order to obtain optimal grouping strategy. The obtained results indicate that the group formation under middle penetrations gives the highest cost reductions, and the total cost reductions of Agent-1 and Agent-3 are 24.9% and 13.14%, respectively, while the total profit of Agent-2 is 4.53$ according to the best solution.