Intelligent Optimal Control Strategy of Heat Pump System Based on Digital Twins

Abstract

In the context of the digital transformation of the power grid, digital twins, as one of the key technologies to promote the digital and intelligent development of the power industry, are still in the theoretical research stage. Focusing on the application of digital twin technology in the power industry, an intelligent optimal control strategy for heat pump system (HPS) based on digital twin technology is proposed. Firstly, the DOE-2 model of HPS and the prediction model of building heat load are established. Secondly, based on the real-time monitoring data, the improved quantum particle swarm optimization algorithm is used for the rolling optimization of model parameters. Finally, the optimal control strategy of the HPS is formulated based on the comprehensive consideration of energy consumption, the number of startups and shutdowns, and the temperature control requirements of the HPS. The example results show that the digital twin model has high accuracy. Compared with the manual control method, the proposed optimal control strategy can effectively improve energy efficiency utilization and has a better control effect, providing technical support for the operation and management of HPS.