The residential sector in Ghana accounts for about 40% of aggregate electricity consumption out of which urban centers contribute 70%. The high weighted share of residential electricity use is attributed to high appliance ownership and use, and other household/building factors. The ability to determine how changes in the pattern of these factors influence electricity demand is critical if efforts to reduce consumption are to be effective. This study combines a residential electricity consumption survey (RECS) with electricity end-use monitoring of 60 households in Tema city Ghana, to yield the first ever comprehensive investigation of city-scale electricity consumption in urban Ghanaian homes. A multiple linear regression analysis is used to identify the most statistically significant indicators of appliance ownership and household electricity consumption. Results indicate that ownership of air conditioner, freezer, fan, refrigerator and television; and changes in socio-economic and building factors such as energy efficiency awareness and practice; income; household size and floor space show high statistical significance, and collectively explain 57% variance in households’ total electricity consumption. The presence of dependent children increases ownership of television, iron, washing machine and small kitchen appliances. This work provides a solid foundation for developing more tailored energy-saving policy interventions targeted at households.

Demand-side management initiatives such as voluntary demand response provide significant energy savings in the residential sector, which is a major peak demand contributor. The potential of such savings remains unexplored in Ghanaian households due to insufficient electricity consumption data, lack of end-user behavior information and knowledge about the cost-effectiveness of such programs. This research combines 80 household survey information and energy use monitoring data of household appliances, to assess the residential demand response potential of Ghana. A bottom-up approach based on modified end-use model is used to develop aggregate hourly load curve. The estimated electricity consumption is categorized based on their degree of control to determine peak demand reduction potential for the period 2018-2050. The average daily peak load reduction ranged between 65-406 MW representing 2-14% for the considered scenarios by 2050. The results show appreciable economic viability for investment in demand response with net present value varying between 28-645 million US$. We find that price, energy security and environment signals influence end-users’ electricity use behavior. Authors observe that for energy and cost savings to be realized, utility providers and consumers need effective cooperation on information delivery and feedbacks, and consumers should be incentivized to balance the benefits.