The Seasonal Effects of Weather on Residential Electric-Energy Usage

Abstract

Climate change is one of two major challenges humans face in the 21st century. At the heart of climate change is global warming which directly affects the ecology, rainfall, temperatures, and weather systems of all cities. Despite the foregoing, not much research has been conducted in Ghana to assess the effects of the changing weather conditions on residential electric energy consumption. Significant literature exists envisaging probable influence of rising temperatures on residential electric-energy usage, mainly through the use of air conditioning and other mechanical means for cooling. This is expected to be significant especially in developing countries with tropical climates. Currently, 32% of the country’s electricity is consumed by the residential sector. This percentage is anticipated to increase by the end of the decade; considering the existing housing deficit, the rate of urbanization as well as the increasing demand for household appliances. This study assessed the influence of the weather on Ghanaian residential electricity consumption. Empirical enquiries published in peer-reviewed journals and related literature were reviewed. Electricity billing data for twelve calendar months of 153 purposively selected households in Ghana were collected. Weather data for the twelve calendar months were also collected and Microsoft Excel software was used to analyze the frequencies and means of the data. SPSS Spearman’s correlation was also used to establish the relationships between the variables. The results suggest a rather weak correlation (r=0.311) between the weather conditions and residential electric energy usage. The lower economic capacity of occupants and minimum variations in monthly temperature could be the reasons for this. Future studies could focus on establishing the extent of these factors on energy usage. However, the highest and lowest electricity consumptions coincide with the highest and lowest temperature, sunshine and relative humidity. This is critical for adequate electric energy supply and peak load factor forecast.