Bayesian game-theoretic energy management for residential users in smart grid

摘要

Plug-in Electric Vehicles (PEVs) are attracting much attention in Demand-side management (DSM) for the function of shifting loads from peak hours and discharging to the smart grid. In this paper, energy consumption scheduling of residential users with PEVs is proposed with incomplete information. In our proposed scenario, PEVs can be employed as vehicles or storage device which can discharge to the grid. Residential users are divided into different types according to the consumption preference on PEVs as vehicles. The type is private information, thus users don't know other users' types. In order to shift loads from peak hours and minimize the cost of residential users, we formulate a Bayesian game model where users must evaluate other users' types with probability distribution of the types before scheduling their energy consumption. Simulation results show that the proposed Bayesian game model is beneficial for all users.