A Method of Hourly Load Forecasting by Time Series by Recycle of Predicted Values
SAHAY KULDEEP · International Journal for Research in Applied Science and Engineering Technology · 2019
Electrical load forecasting is a prime factor in planning of networks, saving costs and balancing supply and demand.As population increases, demand for consumer goods increases, all of which need electricity.While all possible ways are being found to generate electrical power, the ever increasing demand puts a strain on the resources.So a method to predict the load needs to be developed for cost effective supply, for planning networks, planning the generation and distribution.A method of using nonlinear autoregressive neural network model is used to predict the load values as a time series from previous historical load values.Autoregressive neural network time series along with triple exponential smoothing is used and run continuously to further predict from the previously forecasted values.