Model predictive control of heat pump based on a regression model fitted to data measured in accordance to EHPA regulation

• Published in: E3S Web of Conferences Vol. 246; p. 11008
• Main Authors: Thorsteinsson, Simon, Jensen, Søren Østergaard, Bendtsen, Jan Dimon
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Les Ulis EDP Sciences 01.01.2021
• Subjects: Algorithms; Control algorithms; Control theory; Floors; Heat exchangers; Heat pumps; Heating; Mixed integer; Nonlinear control; Power consumption; Predictive control; Regression models
• ISSN: 2267-1242; 2555-0403; 2267-1242
• DOI: 10.1051/e3sconf/202124611008

This paper presents a method for fitting a static regression model for the power consumption of a ground-sourced domestic heat pump, based on a low number of sample points extracted from a common measurement report developed in accordance to European Heat Pump Association (EHPA) regulation. Thereafter, we demonstrate how the coefficients can be updated with a Recursive Least Squares algorithm using only commonly accessible measurements. The regression model is designed to be used for control of a heat pump connected to an ON/OFF controlled floor heating system. The target of the method is especially systems where the flow in the floor heating circuits is unknown. The ability of the regression model to predict power consumption of the heat pump is evaluated using measurements obtained from a test-rig having the particular heat pump installed. The regression model is implemented as a module in a Mixed Integer Non-linear Model Predictive Control algorithm to illustrate the applicability of the model for control purposes. The promising results obtained from this investigation raise the question; should quality data be available in order to enable more advanced control of domestic heat pumps?