Intelligent power grid park terminal user energy demand condition dynamic prediction system and method

The invention discloses an intelligent power grid park terminal user energy demand condition dynamic prediction system and a method. The method includes: conducting a main constituent analysis of meteorological factors for influencing the cooling and heating load demand of intelligent power grid park terminal users; converting related variables to a few of linear independent random variables; quantifying the weather factor and the day type, conducting an analysis with historical load data by employing a fuzzy clustering method, and forming a sample; representing load characteristics of various types of loads and various types of distributed energy supply systems in the intelligent power grid park in load curves; and finally solving a model according to the process of a BP neural network algorithm, and obtaining a cooling and heating load prediction result. The system comprises a main constituent analysis module, an analysis sample formation module, a load characteristic curve module, and a load prediction module. According to the method and the system, the network size is reduced, the prediction precision is improved, and advantages of a BP neural network for large-scale parallel processing and adaptive learning ability are fully developed.