Abstract: In response to the challenges of energy security and environmental pollution from coal-fired power plants in China, enhancing power generation efficiency is particularly crucial. This study, centered on the Data Mining Process Model, carries out a series of applied research on the optimization of power plant operation. A data mining technique suited for determining target values within power plant operations was established, and a comparison was made between traditional methods of target value determination and a new scheme incorporating data mining techniques. Furthermore, the role of data mining algorithms in optimizing power plant operational parameters is discussed in detail, with special emphasis on the application of fuzzy association rules. Concrete examples demonstrate that the methods proposed in this study can significantly optimize controllable operational parameters, reduce fluctuations in unit load, and achieve energy conservation and emission reduction. The research results not only enhance the overall performance and economic efficiency of the system but also point to potential future directions for power plant development.