Title :
Exploring of Related Issues of BP Algorithm in Load Forecasting
Author_Institution :
East China Inst. of Technol., Fuzhou, China
Abstract :
In this paper, the establishment of the neural network model of forecasting short-term power load in an electric power grid is studied. Basing on the model, the BP algorithm for power load is explored. The research on BP network model includes determining the hidden layer number, hidden layer nodes number, training frequency and accuracy of learning rate. In this paper, we focus on that how to give initial weights, select training sample method of normalizing sample and so on. With more further qualitative and quantitative analysis, and through an actual example as comparative test, we have got useful conclusions.
Keywords :
backpropagation; load forecasting; neural nets; power engineering computing; power grids; BP network model; electric power grid; hidden layer nodes number; neural network model; short-term power load forecasting; Artificial neural networks; Computer networks; Frequency; Grid computing; Intelligent networks; Load forecasting; Neural networks; Neurons; Power grids; Predictive models; Artificial neural network; Forecasting; Short-Term Load; improved BP model algorithm;
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Print_ISBN :
978-0-7695-3804-4
DOI :
10.1109/ICICTA.2009.26