This paper proposes a game-theoretic model for peer-to-peer (P2P) energy trading between a consumer and a prosumer living in a community. The proposed real-time pricing model is based on the Stackelberg game, and the consumer and prosumer are the follower and leader in the game, respectively. Therefore, the prosumer first proposes the trading price and then proposes the trading quantity based on the optimal scheduling of the energy storage system considering the determined trading price, load profile, P2P trading demand, etc. Subsequently, the consumer decides to purchase quantity by adjusting his/her load usage according to the trading price and quantity suggested by the prosumer. In this regard, a power flow analysis was conducted based on the participants' bidding strategy to analyze the changes in the electricity flow in a distribution system in which P2P energy trading occurs. Consequently, changes in power flow from the point of common coupling before and after P2P trading were verified, and the voltage stability of each bus was confirmed. In addition, the distribution system usage charge was calculated to reduce the operational burden of the distribution system operator and suggest an operation strategy that can enable P2P energy trading.

This study provides a better explanation for the continued prevalence of high–low (Hi–Lo) pricing strategy. We investigate the impact of market competition on adopting two different pricing strategies in the retail industry: everyday low price (EDLP) strategy and Hi–Lo strategy. We developed two analytic models using a game‐theoretic modeling approach: the profit maximization model and the sales revenue maximization model. We then conducted an econometric analysis based on retail store‐level dataset. The result shows that an EDLP player's equilibrium price depends highly on the cost level rather than competitor's price whereas the Hi–Lo player's equilibrium price depends mainly on the range of promotional basket as well as the cost level.