Research and Application of Big Data Algorithms in Smart Power Plants

As society progresses, China's power industry continues to improve and upgrade its structure. Large-scale thermal power plants are required to achieve high efficiency, energy savings, low carbon emissions, and environmental protection, as well as in-depth FM and FFM. Therefore, it is imperative to conduct research on smart power plant algorithms based on big data. This paper studies the improved FCM algorithm, which uses adaptive jump probability instead of random probability to adjust the population. This adjustment is more conducive to algorithmic optimization and effectively improves the accuracy of power plant data analysis. The study provides theoretical support for the development of a new type of power system.