Electricity Load Forecasting by Artificial Neural Network Model Using Weather Data
نویسندگان
چکیده
This paper discusses significant role of advanced technique in short-term load forecasting (STLF), that is, the forecast of the power system load over a period ranging from one hour to one week. An adaptive neuro wavelet time series forecast model is adopted to perform STLF. The model is composed of several neural networks (NN) whose data are processed using a wavelet technique. The data to be used in the model are both the temperature and electricity load historical data. The temperature variable is included because temperature has a close relationship with electricity load. The calculation of mean average percentage error for a specific region under study in India is done and results obtained using MATLAB’S ANN toolbox. This study proposes a STLF model with a high forecasting accuracy. In this study absolute mean error (AME) value calculated is 1.24% which represents a reasonable degree of accuracy.
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