End Use Based Model For Residential Power Consumption Forecasting In Nairobi Region, Kenya
Nzia, Margaret Kanini
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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.