A MODEL FOR P2P ENERGY TRADING IN A MICROGRID UNDER SCHEDULED BLACKOUTS

Abstract

Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid, allowing each network prosumer to trade energy with one another and with the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interests and motivating prosumers to participate in energy trading to achieve different energy management goals. In this thesis, we propose a novel game-theoretic model for peer-to-peer (P2P) energy trading among prosumers in a residential microgrid. During the trading process, there are two separate competitions. The first one is between the registered sellers to offer their energy prices and is modeled as a non-cooperative game. The second game is between the registered buyers for the process of selecting the appropriate seller and it is modeled as an evolutionary game. To model the interaction between both the sellers and the buyers, an M-leader N-follower game is used. Iterative algorithms are proposed for the game modeling to find the equilibrium state which corresponds to their convergence. The proposed trading method is applied to a residential microgrid characterized by a heavy reliance on the intermittent grid and diesel generation units. Results demonstrate the applicability of the proposed P2P trading method among prosumers making sure that it provides significant financial and technical benefits for the whole system.