Volume 3, Issue 3, June 2015, Page: 42-47
Short-term Electrical Energy Consumption Forecasting Using GMDH-type Neural Network
Tsado Jacob, Department of Electrical and Electronics Engineering, Federal University of Technology Minna, Niger State, Nigeria
Usman Abraham Usman, Department of Electrical and Electronics Engineering, Federal University of Technology Minna, Niger State, Nigeria
Saka Bemdoo, Transmission Company of Nigeria, TCN Abuja, Nigeria
Ajagun Abimbola Susan, Department of Electrical and Electronics Engineering, Federal University of Technology Minna, Niger State, Nigeria
Received: Apr. 20, 2015;       Accepted: Apr. 29, 2015;       Published: May 19, 2015
DOI: 10.11648/j.jeee.20150303.14      View  5057      Downloads  267
Electric load forecasting plays an important role in the planning and operation of the power system for high productivity in any institution of learning. A short-term electrical energy forecast for Gidan Kwano campus, Federal University of Technology Minna, Nigeria was carried out using GMDH-type neural network and the result was compared to that of regression analysis. GMDH-type neural network was used to train and test weekly energy consumed in the campus from September 2010 to December 2014. The neural network was trained using quadratic neural function. Root mean square error (RMSE) and mean absolute percentage error (MAPE) were used as performance indices to test the accuracy of the forecast. The neural network model gave a root mean square error (RMSE) of 0.1189, a mean absolute percentage error (MAPE) of 0.0922 and a correlation (R) value of 0.8995 while the regression analysis method gave a standard error of 10968.1 and a correlation (R) value of 0.1137. Results obtained show the efficacy of the GMDH-type neural network model in forecasting over the regression analysis method.
Group Method of Data Handling (GMDH), Polynomial Neural Network (PNN), Short Load Term Forecasting (STLF), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE)
To cite this article
Tsado Jacob, Usman Abraham Usman, Saka Bemdoo, Ajagun Abimbola Susan, Short-term Electrical Energy Consumption Forecasting Using GMDH-type Neural Network, Journal of Electrical and Electronic Engineering. Vol. 3, No. 3, 2015, pp. 42-47. doi: 10.11648/j.jeee.20150303.14
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