Geothermal heat is considered a sustainable energy source with significant global potential. Together with heat distribution networks, it can provide clean thermal energy to individual and commercial consumers. However, peaks in heat demand can require additional peaking sources at times. In this paper, we investigated how wind turbines can act as a peak energy source for a geothermal district heating system. We studied a model consisting of a geothermal heat source, a heat storage and wind power generator using historical weather data of Warsaw (Poland) and showed that wind power could increase the renewable share to supply a considerable heat demand compared to a geothermal heat source alone. The results indicate that wind power can be a suitable complement for a geothermal heat source to provide energy for heating. It is shown that a theoretical geo-wind-thermal storage based district heating network supplying 1000 m², which requires 100 W/m² at an outdoor temperature of −20 °C should have the following parameters: 4.8 MWh of thermal energy storage capacity, 45 kW of geothermal capacity and 5 kW of wind capacity. Such a system would ensure minimal wind curtailment, high utilization of geothermal source and high reliability of supply.

Although geothermal resources are practically independent of climate factors, those factors significantly condition the potential use of the Earth’s natural heat resources. Unlike all the other factors limiting or facilitating the use of geothermal heat (like receivers’ temperature expectation, financial issues or local regulations), climate factors remain immovable. Thus, climate remains the main factor influencing the effective use of geothermal resources. Volumes of sold energy, typical capacity factors and rapid changes in heat demand may all influence the financial and technological performance of an investment. In the current paper, climate factors are translated into heat demand based on historical data (meteorological and district heating logs) by means of a dedicated artificial neural network, and analysed in terms of possible constraints and facilitators that might affect the effective use of geothermal energy. The results of ANN simulation indicate that average and typical operation is expected without any turbulences, yet about 10% of operating hours may require additional technical measures, like peak source support, smart management and buffers in order to limit pumping ramp rate. With appropriate dimensioning and exploitation, capacity factors as high as 60% are available, proving the potential for financially and environmentally effective use of geothermal resources.