Application of Probability Statistics of Set Algebraic Systems Based on Data Mining in the Energy Field

As the global demand for energy continues to grow and the rapid development of renewable energy sources, the energy sector faces complex data processing and analysis challenges. This paper discusses the probabilistic and statistical application of set algebraic system based on data mining in the field of energy, uses data mining technology to effectively integrate multidimensional data such as energy consumption, production and distribution, and uses set algebraic system to build data models. Then, probabilistic statistical methods are used to analyze the energy data to identify potential patterns and trends. Evaluate the economic and environmental impacts of different energy technologies through case studies. The research shows that the set algebra system based on data mining can effectively improve the ability to analyze energy data and help identify the key drivers of energy consumption. At the same time, probability statistical analysis can predict the effects of different energy policies after implementation, providing data support for decision-making. The utilization rate of renewable energy significantly reduces carbon emissions after adopting this method. Therefore, the set algebra system based on data mining combined with probability statistics provides an innovative solution for the energy field, which can better data analysis and decision support, and promote the efficient use of energy and sustainable development.