Risk-aware sellers and comfort-driven buyers: A game-theoretic P2P energy trading framework

A transitional shift from the centralized energy system to the distributed energy system has promised to address several concerns of today’s energy system such as rising pollution, variation in energy price, energy availability, and sustainability. However, the increased penetration of renewable energy sources and their stochastic nature also create challenges for the grid, such as economic threats, and meeting energy demand for consumers with limited generation capacity to cope with the buyers’ comfort level. This paper presents a novel method based on a game-theoretic framework for energy trading in the peer-to-peer energy market to meet these challenges. For this purpose, firstly, a model is proposed which invites energy buyers and sellers to form a trading place. Then, a model has been proposed to determine how the energy demand of the buyers and their comfortable index varies. In the case of uncertainty in supply from the grid and when the sellers have no prior information about it determining a fair energy trading price becomes a challenging task. For this purpose, a game-theoretic framework is proposed among energy sellers and the grid to determine the optimal energy price. Thirdly, a game-theoretic framework is used for energy allocation policy, ensuring the buyers’ comfortable index. Fourth, Vogel’s approximation-based optimization problem is proposed to minimize energy losses. The proposed model is evaluated on an IEEE-14 interconnected bus system having 22 players i.e., (11 buyers and 11 sellers) for the dataset of one year. Simulation results show that the proposed model helps to satisfy the energy demand of buyers with an increase in profitability to the sellers and grid. The proposed framework also helps to reduce stress on the grid • Proposes a two-stage game model for optimal pricing and energy allocation. • Framework achieves satisfaction level 1 for comfort-driven buyers. • Risk-taking sellers gain up to 30% higher revenue than risk-averse ones. • Grid earns up to 38.13 cents per slot by penalizing risk-taking sellers.