Forecasting of Electrical Energy Demand in Nigeria using Modified Form of Exponential Model

Journal Title: American journal of Engineering Research - Year 2018, Vol 7, Issue 1

Abstract

This paper presents long term electric power load forecasting for twenty years (20 years) projection, in Nigeria power system using modified form of exponential regression model. The model is implemented in Matlab platform with a plot in residential load demand, commercial load demand and industrial load demand in (MW). To analysis and predict the energy (power) demand (MW) requirement for a projection period of (2013 - 2032), data are collected between 2000 - 2012, from the Central Bank of Nigeria (CBN), and National Bureau of Statistics (NBS). The results obtained shows that energy generated from the respective generating station including Egbin Thermal Power Station, Sapele Thermal Power Station etc. are grossly inadequate and this mismatch is a major problem in power system planning and operation. The result also shows that there is deviation between predicted energy demand (MW) and available power (or capacity allocated). The predicted energy demand into the projected future of 20years is 395,870.2MW. The work also extended the prediction form into: least-square, exponential regression to modified form of exponential regression. Evidently, the comparism plot for least-square, exponential and modified exponential model shows similar predicting pattern: particularly least-square exhibit linear behaviour, while exponential and modified exponential shows non-linear behaviour but the new modified exponential model developed gives more accurate result with percentage error of 1.37% compared to existing model with 1.67%.

Authors and Affiliations

Dikio C. Idoniboyeobu, Aderemi J. Ogunsakin, Biobele A. Wokoma

Keywords

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  • EP ID EP396008
  • DOI -
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How To Cite

Dikio C. Idoniboyeobu, Aderemi J. Ogunsakin, Biobele A. Wokoma (2018). Forecasting of Electrical Energy Demand in Nigeria using Modified Form of Exponential Model. American journal of Engineering Research, 7(1), 122-135. https://europub.co.uk/articles/-A-396008