Energy Management Optimization Strategy of User Side in Smart Grid Based on Model Predictive Control

This paper proposes a multi-time scale coordinated optimal scheduling model based on model predictive control, which realizes energy management optimization of user side in smart grid. Firstly, the model of user side in smart grid including seven parts is constructed, which is more comprehensive and specific than previous research. Secondly, a multi-time scale optimal scheduling control strategy based on model predictive control is proposed. With the objective of minimizing the total cost in one day, a day-ahead economic optimization model has established. Then the model is solved by mixed integer non-linear programming. With the objective of minimizing the error between the daily scheduling and the actual output of the day, the intra-day rolling optimal scheduling model is established. Then the tracking of the daily schedule is realized by solving the model with rolling time-domain optimization strategy, which is based on model predictive control. Finally, the strategy is applied to a user side in smart grid in Beijing. The simulation results verify the feasibility and effectiveness of the optimization strategy. At the same time, the influence of different parameters (prediction time domain and unit climbing rate) on energy scheduling results is analyzed.