Representative period selection for flexible control strategies on a reversible heat pump in cooling mode: A comparative case study

Rising space-cooling demand is intensifying peak electricity loads. Although reversible heat pumps are widely recognised as a key technology for building decarbonisation, it remains essential to avoid peak loads on the electrical grid and shift demand towards periods characterised by higher renewable energy availability and more favourable electricity prices. It is therefore crucial to investigate flexible control strategies that can manage peak electricity demand and overall energy use, while promoting the self-consumption of energy from renewable sources and ensuring indoor comfort. In this context, identifying week cycles representative of a full year or season allows to assess heat pump behaviour and infer the impact of flexible control strategies on its annual energy performance, especially when annual analyses are not feasible or practical, as in lab or field experiments. This study analyses four representative day selection procedures under two day-ahead price-based control strategies applied to a reversible heat pump operating in cooling mode. A comparative analysis is conducted for three southern Europe locations. The dynamic simulations include the building, the GSHP coupled with radiant panels, and a separately controlled dehumidifier. The results indicate that the clustering method is the most effective method at representing key performance indicators across the climates, whereas the proposed consecutive day selection method provides the most accurate absolute values for extrapolated electricity cost and energy consumption.