Nonlinear combined forecasting method based on fuzzy adaptive variable weight

Different forecasting methods can lead to very different results in power system load forecast, in order to improve forecasting accuracy, a nonlinear combined forecasting method based on fuzzy adaptive variable weight is introduced. Not only the nonlinearity of electric load forecasting is considered, but also the advantage of variable weight combined forecasting is also utilized. The determination of fuzzy weight and gray basic weight is the key aspects of this method. A case study of load forecasting in a certain power network shows that the model proposed here has a better fitting precision. And the combined forecasting model proposed in this paper is very useful for requirement decision in power system.