Research on MPC control strategy of heat pump based on data-driven hybrid model
YUAN Wenzhao
LI Hao
YANG Qiang
LIANG Yongchao
XIONG Jun
DAI Wenjie
Gao Xun
Abstract：Aiming at the problems of significant differences in user operation habits and insufficient energy-saving awareness in heat pump heating systems,it proposes a Model Predictive Control(MPC)strategy for heat pumps based on a data-driven hybrid model.By analyzing the operational data of 210 users in northern China,user behaviors were categorized into three types:non-adjusting,less-adjusting,and frequent-adjusting,revealing that 60％of users exhibit operational inertia or a lack of knowledge.On this basis,a hybrid model combining a 4R3C building thermal resistance-capacitance model with a BP neural network for heat output prediction was constructed.Parameters were identified using a genetic algorithm,and automatic optimal adjustment of water temperature was achieved through MPC.Experimental results show that this strategy can achieve energy savings of 6.5％to 15.7％while maintaining indoor comfort,verifying its effectiveness and feasibility in practical applications.
Keywords：Heat pumpModel predictive control(MPC)Data-drivenHybrid modelEnergy-saving operationUser behavior analysis
Publication Date：2025-12-09
Online Publishing Date：2026-01-06(First online date of this platform, not the publication date of the document)
Pages：4( 338-341 )