Analysis of Demand and Supply of Electrical Energy in Cameroon: Influence of Meteorological Parameters on the Monthly Power Peak of South and North Interconnected Electricity Networks
International Journal of Energy and Power Engineering
Volume 3, Issue 4, August 2014, Pages: 168-185
Received: Jul. 17, 2014;
Accepted: Jul. 28, 2014;
Published: Aug. 10, 2014
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Flora Isabelle Métégam Fotsing, Environmental Energy Technologies Laboratory (EETL), University of Yaounde I, PO Box 812, Yaounde, Cameroon; Laboratory of Industrial Systemsand Environment of the University of Dschang, PO BOX 96, Dschang, Cameroon
Donatien Njomo, Environmental Energy Technologies Laboratory (EETL), University of Yaounde I, PO Box 812, Yaounde, Cameroon
Réné Tchinda, Laboratory of Industrial Systemsand Environment of the University of Dschang, PO BOX 96, Dschang, Cameroon
Following the unbalanced provision between supply and demand of electrical energy in Cameroon, it is necessary to perform an analysis of the data since it can provide essential information for an optimal management of the power supply system. This study presents on the one hand an analysis of electrical energy demand and supply in Cameroon, and, on the other hand, the modeling of the monthly peak of the main interconnected network in Cameroon, namely South Interconnected Networks (RIS) and North (RIN) networks using econometrical methods. Meteorological parameters (monthly maximal temperatures and humidity) are considered as exogenous variables of this application. Following the seasonality observed during various months, the introduction of terms of monthly seasonal as well as an average coefficient Ci peculiar to each month will also be introduced into the linear regression model to evaluate the most suitable one for this modeling. From the above analysis, it appears that meteorological parameters have a significant influence on the monthly peak in both networks. As well as the coefficients of these parameters are not the most significant of the various models, the absence of these parameters in different models leads to an increase Akaike (AIC) and Schwartz (SC) criteria. However, the best model is based on the minimum AIC and SC. The monthly peak in both systems is observed at the same time (20h) and one a working day. This peak may be influenced by other parameters such as the return to households and their consumption pattern, the type of equipment they use amongst other.
Flora Isabelle Métégam Fotsing,
Analysis of Demand and Supply of Electrical Energy in Cameroon: Influence of Meteorological Parameters on the Monthly Power Peak of South and North Interconnected Electricity Networks, International Journal of Energy and Power Engineering.
Vol. 3, No. 4,
2014, pp. 168-185.
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