An optimal P2P energy trading model for smart homes in the smart grid

This research addresses a demand side management (DSM) system coordinated with Peer-to-Peer (P2P) energy trading among the households in the smart grid. It considers the components which have significant impact on cost optimization, e.g., storage, renewables, and microgrid. The model utilizes load and source scheduling, and energy trading strategies for cost optimization. It also addresses the inconvenience created to the users by delaying certain tasks. The contributions of the research are threefold. First, to our knowledge, this is the first optimal model which integrates DSM with P2P energy trading. The solutions of the proposed model determine optimal microgrid energy and price for P2P trading, which was not considered previously. Second, P2P energy trading in the microgrid potentially results in an unfair cost distribution among the participating households. We address this unfair cost distribution problem by employing Pareto optimality, ensuring that no households will be worse off to improve the cost of others. Third, our proposed trading strategy considers total cost optimization in a microgrid. The model utilizes all available energy to minimize energy cost. Therefore, there is a very low risk of energy waste, which is typically neglected in other energy trading strategies.