Power system short-term load forecasting based on empirical mode decomposition and dynamic neural network
Liu Yao-nian · Advanced Technology of Electrical Engineering and Energy · 2008
This paper proposed a hybrid model based on Empirical Mode Decomposition(EMD)、dynamic neural network and BP nature network as a short-term load forecasting model.At first,based on EMD the load series is decomposed into different lots of calm series,then according to the features of decomposed components different dynamic neural network model,finally using the BP network to reconstruct the forecasted signals of the components and obtain the ultimate forecasting result.Simulink results show that the proposed forecasting method is accurate.