Long Term Load Forecasting Using Grey System Theory

Abstract

Supply and demand in power system planning and operation is required to be balanced. An operational reserve to provide against faults or accidental demands are also required. Therefore load forecasting is one of the most important fields and various load forecasting methods have been applied.
In this paper the grey system theory, which treats uncertain information, is applied to the long term load forecasting from three aspects: the point prediction, the interval prediction, the topological forecasting. In the point prediction, the annual total demand is predicted. In the interval prediction, the annual peak demand is predicted. And in the topological forecasting, the date where a yearly maximum peak demand would occur is predicted. The grey dynamic model (abbreviated to GM model) is adopted as the predicted model. The GM model is a differential equation model which is different from the most forecasting models. The GM model is quite powerful when combined with the preliminary transformation called the accumulated generating operation (AGO).
This paper proposes a new method for the long term load forecasting problems involving uncertainty. The predicted results have been found very satisfactory. The grey system theory is a new tool very efficient for load forecasting.