| dc.description.abstract | Energy demand in Africa is projected to surge by more than 75% from 2015 to 2035, primarily driven by population growth. Simultaneously, Africa's energy production is expected to grow by 28% by leveraging local renewable resources like solar energy and hydropower. Remarkably, Africa possesses an impressive 60% of the world's solar resource, with the potential for utilization reaching up to 39.4% by 2040. The solar energy prospects are particularly promising in East Africa, thanks to its equatorial location, which grants an average radiation of 5.2 kWh per square meter per day throughout the year. Despite this abundant solar potential, the widespread adoption of solar home systems (SHS) for residential use has been hampered by affordability. For instance, in 2019, the average cost of a basic solar home system in Uganda was approximately $350, which contrasts significantly against the country's relatively low Gross National Income (GNI) per capita of $760. Presently, Solar Photovoltaic represents only 2% of the total installed 1.245 GW in Uganda.
This study aimed to evaluate the impact of designing Solar Home Systems (SHSs) using time-based scheduling of electrical appliance data to create load profiles, resulting in cost reduction. Load profiles were created by scheduling electrical appliance data from bottom-up load profiles on a twenty-four-hour scale. The created load profiles were used to size solar home systems, which were then compared to ones sized by conventional methods. The two systems were compared in terms of size and cost reduction, economic and technical feasibility, using Net Present Value (NPV) and Internal Rate of Return (IRR), and redundancy, respectively.
Results showed an average 38% reduction in required batteries and an 18.44% cost reduction compared to conventional sizing methods. This reduction had positive financial implications, with positive NPV and IRR of 51.15% and 10.32% increases, respectively. These results indicate that these load profiles can lead to low-cost and efficient solar home systems.
The study concluded that, there was a reduction in the solar home system size after time-based scheduling of electrical appliance data, which is dependent on human behaviour. Therefore, load or demand-side management methods should be employed. It also noted that systems before time-based scheduling of electrical appliance data had been oversized 1.9 times or by a 90% margin.
The research recommended that time-based scheduling of electrical appliance data should be used with caution because under sizing of the SHS can easily be done if human characteristics are not carefully monitored. It further recommended that human behavioural characteristics and demand-side management should be emphasized. SHS users should be advised to use high energy consuming devices during the day because greater reduction in the SHS sizes occurred with predominant day loads. | en_US |
