Air Source Heat Pump Systems: Control Strategy Based on the Knowledge of the Time Evolution of the Electricity Price in the Italian Context
air-source heat pump, electricity price
Motivation: The transition toward a decentralized energy system and the increased generation of electricity from renewable energy sources, that have low predictability, obviously affects the management of the grid. One of the consequences to be expected is a larger variation of the electricity prices (according to the season and/or the time of the day) as a function of the availability of the renewable sources. When electric heat pumps are used for domestic space heating and cooling the total energy cost can then be reduced if the system is properly controlled. In particular, when the tariff is known in advance (and assuming that such varying cost is linked with the actual grid status), the optimal control of electric appliances such as heat pumps can contribute to reduce both the electricity grid imbalance and the final operating cost. The pursuit of the best rates, however, can lead to problems in the HVAC system management (i.e. sub-optimal comfort conditions) especially when air source heat pumps are installed in high-performance buildings. What was done: In this study, different control algorithms based on the knowledge in advance of the cost of electricity are tested by means of a dynamic simulation code. Coupled dynamic simulations of a building and its HVAC system have been run considering the climate conditions of south Europe (Italy) and the Italian electricity tariffs for the year 2017. The analyzed control strategies are compared to each other and to the base-case without any predictive control. Expected benefits of what was done: The obtained results highlight the extent to which the applied algorithms induce cost savings and reduce the fluctuations of the power input into the grid.