Reward-Punishment based User Utility Maximization Model for Optimal Real-time Pricing in Electricity Energy Supply

Due to uncertainty factors such as renewable energy, imbalance between supply and demand has a great impact on the stable operation of the smart grid. The demand response (DR) program can effectively solve the imbalance issue by guiding users to adopt reasonable electricity consumption manner. In addition, users should be able to benefit from participating in DR by changing the habit of using energy. In the present study, a dynamic reward-punishment based user utility maximization model is proposed for optimal real-time pricing (RTP) in electricity energy supply to reach the supply-demand balance and provide the optimal reward and punishment for users. Based on the dynamic reward and punishment mechanism, the proposed model can obtain the optimal electricity consumption by maximizing user utility and encourage users to adopt a reasonable electricity consumption manner. From the perspective of algorithm implementation, a distributed algorithm is proposed to achieve the purpose of the supply-demand balance with the optimal electricity price and optimal electricity consumption. The simulation results show that the proposed utility model and distributed algorithm are reasonable and effective in dealing with the imbalance problem between supply and demand.