Since the heating load of central heating systems is significantly influenced by external temperature and other factors, considering weather conditions during load forecasting can lead to more accurate predictions. This paper proposes a method to calculate the real-time heating load of a heat exchange station based on the real-time temperature in the vicinity of the station through data mining, and explores the establishment of a comprehensive adjustment evaluation system. By collecting data from on-site sensors, the system platform calculates the required secondary network supply water temperature and promptly issues control parameters through the upper-level configuration software to achieve real-time control. This method offers significant economic and environmental benefits, has a simple principle, demonstrates obvious effects during initial adjustments, and can be widely promoted in the regulation and control of heat exchange stations.