Short term power prediction method for active distribution networks in mountainous areas based on DKF algorithm

Due to the susceptibility of traditional distribution network short-term power prediction methods to the influence of mountainous weather and terrain, the prediction accuracy is low. To address the aforementioned issues, a short-term power prediction method for active distribution networks in mountainous areas based on the DKF algorithm is proposed. This method first collects and preprocesses short-term power historical data of active distribution networks in mountainous areas. Secondly, a short-term power prediction model for active distribution networks was constructed using the DKF algorithm. Finally, by combining the optimized dynamic Kalman filter with the actual characteristics and historical data of active distribution networks in mountainous areas, accurate prediction of power changes was successfully achieved. The experimental results show that compared with traditional methods, the prediction accuracy is higher and more reliable.