Demand Side Management and Battery Storage Utilization to Increase PV Self-consumption of a Modulating Heat Pump

The combination of photovoltaic (PV) systems and heat pumps for heating and cooling of buildings is a promising solution to increase the share of renewable energy in the residential sector. The interaction between the system components is fundamental to assure a high performance of the system. The level of PV energy self-consumption is strictly dependent on the control strategy applied to the system. The solar source is intermittent and it does not always match the building loads for heating and cooling. Furthermore, even the heating and cooling demands are strongly time-dependent in high performance buildings. For these reasons, an efficient control system is essential to ensure the high performance. Several papers in the literature have proposed advanced control techniques based on the model predictive control (MPC). However, their implementation in residential buildings is often limited due to high device costs. This paper proposes a rule-based control strategy for a modulating air-source heat pump coupled with a PV plant, which provide space heating, space cooling and domestic hot water in a residential building. The proposed control strategy can be easily implemented in residential buildings by using low-cost board shields. The heat pump is modulated and optimized depending on the instantaneous PV production, to maximize the direct use of solar energy onsite. When an overproduction of PV energy occurs, the heat pump operates to store the solar energy as thermal energy, exploiting thermal storage tanks and the building thermal capacitance (aka virtual battery). The heat pump is controlled by varying its compressor rotational speed. The compressor is regulated to operate at the maximum capacity level compatible with the supplied PV power. The control strategy is evaluated in combination with a electric storage system. The efficacy of the control strategy is assessed by means of dynamic energy simulations. The simulations are run for the whole year. A parametric analysis is carried out by considering different PV and battery size, to understand the impact of the system component size on the results