Abstract

Peer-to-Peer (P2P) energy trading is one of the emerging approaches for managing energy within microgrids. Various methods and mechanisms have been proposed for market settlement in P2P energy trading. One of the challenges in these approaches is the underutilization of the maximum capacity of the P2P energy market. In this article, to maximize the utilization of the P2P market capacity and address the buying and selling requests, a combination of auction-based and bilateral negotiation approaches has been utilized. One of the advantages of double auction-based approaches is the ability to maximize social welfare due to the presence of an auctioneer in their structure. On the other hand, one of the challenges of these approaches is that some buyers and sellers may exit the market clearing process based on their own bids and asks. As a result, they would need to find alternative ways to sell and buy their energy. In the proposed approach, buyers and sellers are divided into two groups. The first group consists of participants who have won in the auction process. In this scenario, buyers engage in a Stackelberg game with the P2P energy trading platform, which acts as the auctioneer. In this game, the auctioneer plays the role of the leader, and the buyers play the role of followers. Each of them strives to maximize their social welfare function. After the completion of the market settlement process for the first group, the buyers and sellers of the second group attempt to match their contracts with each other through bilateral negotiations. Another challenge in P2P energy trading is the lack of simultaneous consideration of both economic (market settlement) and technical aspects (network constraints). In the proposed mechanism, constraints and network topology are also considered in the transactions process to minimize the possibility of overload and line congestion. The proposed mechanism has been implemented on the IEEE 37-feeder test system, and the results show that the proposed mechanism performs significantly better than other existing methods.

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