| Abstract: | A new method is proposed for forecasting electricity load-duration curves. The approach first forecasts the load curve and then uses the resulting predictive densities to forecast the load-duration curve. A virtue of this procedure is that both load curves and load-duration curves can be predicted using the same model, and confidence intervals can be generated for both predictions. The procedure is applied to the problem of predicting New Zealand electricity consumption. A structural time-series model is used to forecast the load curve based on half-hourly data. The model is tailored to handle effects such as daylight savings, holidays and weekends, as well as trend, annual, weekly and daily cycles. Time-series methods, including Kalman filtering, smoothing and prediction, are used to fit the model and to achieve the desired forecasts of the load-duration curve. |
