Based on the current situation of the power plant's automatic control system construction， carrying out intelligent construction in a reasonable manner and enhancing the practicability of the optimization model are the key to improving energy efficiency and reducing consumption for in-service units. Combined with GB/T 44770—2024

Technical Requirements for Intelligent Thermal Power Plant

， a scheme for independently building an intelligent power generation control system for operating power plants was presented. Through comprehensive comparative analysis， the feasibility and safety of the scheme were demonstrated. On this basis， a technical model and implementation

method for auxiliary optimization of thermal power generating units based on operating condition division and data mining were proposed. Firstly， steady-state operating conditions were screened by calculating the load change rate based on a sliding window， and then operating conditions were divided according to boundary parameters. Within each condition， the optimal operating parameters were obtained through clustering algorithms. The feasibility of the model was verified through application in a 2×1 000 MW unit. This optimization method has certain universality， which facilitates power plant professionals to establish optimization tasks according to different optimization objectives and obtain reference values of various operating parameters based on historical data mining.