Industrial Area Power Load Forecasting Based on Seasonal Kalman Filter
摘要
The stable and economic operation of the power system depends on accurate regional electricity load forecasting. This article proposes a seasonal Kalman filter prediction model based on Fourier transform spectrum maximization period analysis, which solves the problem of electricity load prediction in regions with different data distributions. The results indicate that the seasonal Kalman filter model has good predictive ability, low volatility, and stable error.