Using Combined Forecasts with Changing Weights for Electricity Demand Profiling
研究了在日前半小时间隔电力需求预测中，通过平滑样条改进启发式曲线构建方法，并采用变权重组合预测模型（切换和平滑转换）来整合多个历史需求曲线，权重可随48个时段变化，实证结果令人鼓舞。
Day-ahead half-hourly demand forecasts are required for scheduling and for calculating the daily electricity pool price. One approach predicts turning points on the demand curve and then produces half-hourly forecasts by a heuristic procedure, called profiling, which is based on a past demand curve. This paper investigates possible profiling improvements. Using a cubic smoothing spline in the heuristic leads to a slight improvement. Often, several past curves could reasonably be used in the profiling method. Consequently, there are often several demand curve forecasts available. Switching and smooth transition forecast combination models are considered. These models enable the combining weights to vary across the 48 half-hours which is appealing as different forecasts may be more suitable for different periods. Several criteria are used to control the changing weights, including weather, and the methodology is extended to the case of more than two forecasts. Empirical analysis gives encouraging results.