End Use Based Model For Residential Power Consumption Forecasting In Nairobi Region, Kenya
Abstract
This study set out to generate baseline data and information through the analysis of
secondary energy consumption data available from the Kenya Power and Lighting
Company Ltd (KPLC) for domestic households in Nairobi region, both urban and rural
based. The accuracy of the current econometric model used for forecasting residential
energy demand for the purposes of planning was assessed. Through interviews,
observations and ownership of electrical appliances, end use patterns for the various
income groups of households were analysed.
It was established that ownership of household appliances and their standard
consumption have an influence on the total energy demand. The average annual
consumption per household in the urban high, medium, and low income groups was
5,767kWh, 1,642kWh and 451kWh respectively, while that of the rural high, middle and
low income households was 1,634kWh, 733kWh and 218kWh per household per year.
Based on the consumption per household and considering demographic, socialeconomic
and penetration level of appliances, an engineering (end use based) model
was developed for forecasting residential electricity demand. The model was used to
estimate the residential consumption in Nairobi region from the year 2009 to 2012.
Using the model, the predicted consumption for the year 2010 was found to compare
better with the actual recorded consumption in KPLC records than the econometric
model. The 2009, 2011and 2012 predictions, though better than the econometric model
predictions yielded less accurate results due to lack of necessary data.
The end use model was found to be more accurate for forecasting of energy demand
and is recommended. It is also recommended that the end use model be developed
further to include other forms of energy and to be used for energy demand forecasting
for the County Governments. Further improvements to this model would consider
urban–rural migration, technological changes (energy efficiency), migration from one
income group to the other and changes in penetration level of appliances.
Citation
Master of Science in Energy ManagementPublisher
University of Nairobi Department of Mechanical and Manufacturing Engineering