The Research Of Short Term Load Forecasting In Regional Power Grid Application

The short term load forecasting is very important to the security and stability operation of power systems. The prediction precision will influence the quality of power supply and the operation cost of power grid. A kind of composite gray neural network forecast modeling method is put forward in this paper. The method is useful to avoid the single forecasting risk and improve the prediction precision by taking all kinds of information in the system and reducing the random error. The paper presents a fuzzy logic neuron network forecast model which considers the weather factor temperature as fuzzy variables. The method brings the fuzzy logic module and RBF neuron network module into full play. The empirical study demonstrates the effectiveness and practicality of the method. In all, the presented forecasting methods are useful for the regional power grid both in theory and in practice.