Operational control strategies for the heating system of a single-family house with exhaust air heat pump and photovoltaic system and "smart" utilization of energy storage have been developed and evaluated in a simulation study. The main aim and novelty of this study is to evaluate the impact on the benefit of these advanced control strategies in terms of performance (energy use and economic) for a wide range of boundary conditions (country/climate, occupancy and appliance loads). Short-term weather data and historic price data for the same year as well as stochastic occupancy profiles that include the domestic hot water load are used as boundary for a parametric simulation study for the system modeled in detail in TRNSYS 17. Results show that the control using a forecast of dynamic electricity price leads to greater final energy savings than those due to the control using thermal storage for excess PV production in all of the examined locations except Sweden. The impact on self-consumption using thermal storage of heat produced by the heat pump using excess PV production is found to decrease linearly with increasing household electricity for all locations. A reduction in final energy of up to 842 kWh year −1 can be achieved just by the use of these algorithms. The net energy cost for the end-user follows the same trend as for final energy and can result in cost savings up to 175 € year −1 in Germany and Spain due to the use of the advanced control.Energies 2020, 13, 1413 2 of 25 increase the renewable share of the heating system by means of increasing the self-consumption (SC) of electricity produced by photovoltaics (PV), and by reducing the final energy (FE) purchased from the grid. Moreover, another objective is to reduce the net cost of the final energy using smart control based on forecasts of dynamic electricity price and short-time horizon weather data. In a larger context, at the grid level, the main objective is to match the electricity load of the heating system with the electricity production from renewable sources in order to limit power exchange and reduce the stress to the grid.A number of studies have been conducted in order to propose technical solutions about how to utilize the renewable electricity production in a smart way and how to control the heating or cooling demand. Psimopoulos et al. [4] developed predictive rule-based controls for smart utilization of thermal and electrical storages and analyzed the results for a case study in Sweden. Arteconi et al.[5] utilized the thermal energy storage (TES) of hot water tank, in particular, with heating distribution systems that have a low thermal inertia as radiators, and implemented demand response algorithms based on real-time electricity prices to improve the system operation. However, despite their achievements in load curtailment, higher use of energy and accordingly higher cost of electricity resulted. Thur et al. [6] showed the potential of overheating control using the thermal mass of the building with radiant floor heating together with s...