The objectives of this work are: (a) to present a new system for building heating which is based on underground energy storage, (b) to develop a mathematical model of the system, and (c) to optimise the energy performance of the system. The system includes Photovoltaic Thermal Hybrid Solar Panels (PVT) panels with cooling, an evacuated solar collector and a water-to-water heat pump. Additionally, storage tanks, placed underground, are used to store the waste heat from PVT panels cooling. The thermal energy produced by the solar collectors is used for both domestic hot water preparation and thermal energy storage. Both PVT panels and solar collectors are assembled with a sun-tracking system to achieve the highest possible solar energy gain. Optimisation of the proposed system is considered to achieve the highest Renewable Energy Sources (RES) share during the heating period. Because the resulting optimisation problem is nonlinear, the classical gradient-based optimisation algorithm gives solutions that are not satisfying. As alternatives, three heuristic global optimisation methods are considered: the Genetic Algorithm (GA), the Particle Swarm Optimisation (PSO) algorithm, and the Jaya algorithm. It is shown that the Jaya algorithm outperforms the GA and PSO methods. The most significant result is that 93% of thermal energy is covered by using the underground energy storage unit consisting of two tanks.

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Due to the growing demand for new ecological, low-emission heat sources, there is a need to develop new tools for simulating the operating parameters and costs of the implemented solutions. The article analyses the existing solutions for the simulation of heat pump operation parameters, describes the requirements for a modern building—nZEB and proposes a simulation tool based on thermodynamic parameters of the refrigerant. The script allows for deriving simple linear equations that can be used for the overall simulation of a system in which the heat pump is a key part and the efficiency of the entire system depends on its performance. The developed numerical script allows for reproducing the Linde refrigeration cycle and the parameters of its characteristic points. To calibrate the simulation, historical data obtained from the SOPSAR system were used. These data were pre-cleaned (peaks and other obvious measurement errors were removed). The obtained numerical model in combination with ground and air temperatures, anticipated hot water consumption and energy losses of the building can be used to simulate the annual performance and energy consumption of the heat pump. The obtained linear models have an RSMD error of 8% compared to historical data from SOPSAR system for all sets of simulated temperatures.