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.

中文翻译：

---

影响波兰东南部地热资源有效利用的气候因素：鲁布林谷

尽管地热资源实际上与气候因素无关，但是这些因素极大地限制了地球自然热资源的潜在利用。与限制或促进地热利用的所有其他因素（如接收器的温度预期，财务问题或当地法规）不同，气候因素仍然是不可动摇的。因此，气候仍然是影响有效利用地热资源的主要因素。出售的能源量，典型的容量系数以及热需求的快速变化都可能影响投资的财务和技术绩效。在当前的论文中，通过专门的人工神经网络，根据历史数据（气象和区域供热记录）将气候因素转化为热量需求，并从可能​​影响地热能有效利用的制约因素和促进因素方面进行了分析。ANN模拟的结果表明，预期平均和典型运行不会出现任何紊流，但是约10％的运行小时可能需要其他技术措施，例如峰值源支持，智能管理和缓冲区，以限制泵送斜率。通过适当的尺寸设计和开发，容量因子高达60％，证明了在经济和环境上有效利用地热资源的潜力。例如峰值源支持，智能管理和缓冲区，以限制泵送斜率。通过适当的尺寸设计和开发，容量因子高达60％，证明了在经济和环境上有效利用地热资源的潜力。例如峰值源支持，智能管理和缓冲区，以限制泵送斜率。通过适当的尺寸设计和开发，容量因子高达60％，证明了在经济和环境上有效利用地热资源的潜力。