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

Highlights: • Novelty predictive discharge control with real-world data model. • Optimized discharge of acc. in conditions with significant temperature fluctuations. • Mathematical model combining water and ground heat accumulation. • Proposed control strategies provide SCOP increase. 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.