BP Neural Network Based on K-Means++ and Optimized by the Genetic Algorithm

With the continuous improvement of smart grid systems, safe and reliable regional load forecasting has become a prerequisite to ensuring proper power distribution and adequate power supply. Load forecasting is affected by various factors, therefore a single load forecasting method cannot effectively handle the highly nonlinear load data. To this end, this paper proposes a back propagation (BP) neural network model based on k-means++ and genetic algorithm optimization, which avoids the limitations of a single forecasting model and improves the efficiency and accuracy of load forecasting.