Peer-to-Peer Electricity Market Based on Local Supervision

The active participation of small-scale prosumers and consumers with demand-response capability and renewable resources can be a potential solution to the environmental issues and flexibility-related challenges. Local energy markets based on peer-to-peer trading is defined as one of solutions to exploit the maximum flexibility potential of prosumers. However, the existing literature that proposed peer-to-peer based local energy markets did not lead to respecting the peers’ energy trading preferences simultaneously in the profitable market settlement. To solve this issue, a new local energy market model is presented in which network users can trade with their preferred trading partners within the local market as well as the grid. The proposed trading model includes two levels to consider both the democracy and the profitability of energy trading. At the first level, the model considers the trading preferences of each player to respect the peers’ choices. The second level matches the rest of the bids and offers of the local buyers and sellers aiming to maximize the social welfare of all of the players participating in the local market. Our proposed local market is implemented for a test system consisting of fifteen residential players, and the results are compared to other trading models through different comparison criteria such as social-welfare of all players and the net cost of each individual player from consuming electricity. According to the results, the proposed model stands in the second rank compared to the other models that do not simultaneously consider preferences and social welfare of the peers, in terms of social welfare, total profits of the players, and the sustainability and liquidity-based criteria. The proposed model achieves 1416-Cent as the total net energy costs of all peers and the total accepted blocks equaling 76. This means that the proposed local market model can still be profitable and liquid while respecting the players’ trading preferences and choices.