Adaptive Model Predictive Control for Electrothermal Conversion Device: A Virtual Power Plant Operation Mode

Some mathematical models are commonly used to express the storage and conversion between electric energy and heat energy in the electric-heat conversion system participating in the virtual power plant scheduling and the simulation calculation of electric and thermal systems. However, in the actual electric-heat conversion, the electric-heat conversion and storage is a very complex and time-varying process of various parameters. Therefore, it is not reasonable to simply use mathematical models to participate in the simulation calculation of power system and thermal system and the scheduling of virtual power plants. To solve this problem, this paper proposes an automatic parameter correction method for electric-heat conversion system based on AMPC adaptive model predictive control algorithm. In order to participate in the scheduling of virtual power plant more accurately, firstly, the fine modeling is carried out in Ansys, and the operation results show that the simulation results based on mathematical model operation are not completely reliable. Based on this, an adaptive model predictive control (AMPC) algorithm is proposed. The parameters in the mathematical model are automatically corrected in real time to equivalently express the complexity and time-varying of the conversion between electric and thermal energy. The simulation results and the actual results are corrected by correcting the parameters. Finally, a simple electric heating device model is used for example analysis to verify the reliability of the algorithm. The main contribution of this paper is that the system parameters can be corrected in real time by Ansys software and AMPC algorithm, so that the electrothermal simulation is closer to the real situation.