Analysis of Household Electricity Consumption in Nonresident Rent Halls Using Linear Regression Analysis Model
Omondi S. Odhiambo
Department of Mathematics, Kibabii University, Box 1699-50200, Bungoma, Kenya.
Samson W. Wanyonyi *
Department of Mathematics, University of Eldoret, Box 1125-30100 Eldoret, Kenya.
Davis Mwenda Marangu
Department of Mathematics, Kibabii University, Box 1699-50200, Bungoma, Kenya.
Irine Jemutai Nguli
Department of Mathematics, Kibabii University, Box 1699-50200, Bungoma, Kenya.
Mbuba Morris Mwiti
Department of Mathematics, Kibabii University, Box 1699-50200, Bungoma, Kenya.
*Author to whom correspondence should be addressed.
Abstract
This paper is based on electricity consumption pattern in rental houses around Kibabii University (KU) situated in Western region of Kenya. Because of unexpected blackout faced by nonresident students at the time they need electricity most for their studies, this work intends to find out the directive measure to curb this crisis. Since the usage of electricity showed high relationship to the number of households sharing a common meter, Regression analysis prove to be the most effective method to model a solution to this problem. SPSS was used to analyze the data obtained. The results showed the consistency in linear trend of usage of electrical power on a monthly basis among students, it is observed also that the rate of consumption of power among nonresident students of KU is affected by the number of households sharing the meter. The consequence of this study is that with the correct data in place one is able to know the amount of power in kilowatt-hours needed for consumption throughout the semester and plan effectively so that power loss is not experienced. The results will be so useful to the KPLC (Kenya Power and Lighting Company) and KU fraternity for planning purposes.
Keywords: Power, ARIMA model, regression, root mean square error, correlation