Research on medium and long term load forecasting method in courts based on K-means clustering and random forest

With the rapid development of China's economy, people's power consumption level has gradually improved, which has brought great pressure to the distribution and power supply in the distribution station area. Accurate load forecasting of distribution station area provides a reference basis for capacity expansion planning of distribution station area. This paper comprehensively considers the self factors and external influencing factors of the distribution station area, carries out cluster division according to its geographical location and maximum load, analyzes the power consumption behavior of different types of distribution station areas, and establishes the maximum load model of different types of distribution station areas by using the random forest regression cycle, so as to improve the prediction accuracy. This method overcomes the disadvantages of large difference in load data in distribution station area and difficult to quantify.