Influence of control strategy on seasonal coefficient of performance for a heat pump with low-temperature heat storage in the geographical conditions of Central Europe

Influence of control strategy on seasonal coefficient of performance for a heat pump with low-temperature heat storage in the geographical conditions of Central Europe

WoS Article

This paper presents a computational parametric study on increasing the Seasonal Coefficient of Performance (SCOP) for residential heat pumps. The studied system consists of a heat pump, low-temperature heat storage, and a control unit. The heat pump enables selection of a low-temperature heat source between ambient air and water in a tank. Two variants of low-temperature heat storage are tested, particularly, insulated-water heat storage and water heat storage sunken in soil. The study is further complemented with a test of selected algorithms for heat pump control: equithermal regulation, a binary algorithm for temperature source selection, a predictive algorithm for the heat storage discharging, and an algorithm for deferred heat storage discharging. A computational model of the system is made using Python. The assessment of HP operation is made based on meteorological data from the years 2008–2019 recorded in the city of Brno, Czech Republic, Central Europe. The results obtained show that using the approaches tested has the potential for increasing the SCOP. This increase reaches as much as 5.19% and it requires only a simple software change in the heat pump control algorithm and connection to meteorological data prediction.

This paper presents a computational parametric study on increasing the Seasonal Coefficient of Performance (SCOP) for residential heat pumps. The studied system consists of a heat pump, low-temperature heat storage, and a control unit. The heat pump enables selection of a low-temperature heat source between ambient air and water in a tank. Two variants of low-temperature heat storage are tested, particularly, insulated-water heat storage and water heat storage sunken in soil. The study is further complemented with a test of selected algorithms for heat pump control: equithermal regulation, a binary algorithm for temperature source selection, a predictive algorithm for the heat storage discharging, and an algorithm for deferred heat storage discharging. A computational model of the system is made using Python. The assessment of HP operation is made based on meteorological data from the years 2008–2019 recorded in the city of Brno, Czech Republic, Central Europe. The results obtained show that using the approaches tested has the potential for increasing the SCOP. This increase reaches as much as 5.19% and it requires only a simple software change in the heat pump control algorithm and connection to meteorological data prediction.

COP; Heat pump; Heat storage; Predictive control; Heat source

COP; Heat pump; Heat storage; Predictive control; Heat source

KUDELA, L.; ŠPILÁČEK, M.; POSPÍŠIL, J.

2022

18.06.2021

0360-5442

Energy

234

United Kingdom of Great Britain and Northern Ireland

121276

121276

12

https://www.sciencedirect.com/science/article/pii/S0360544221015243

http://hdl.handle.net/