Lawrence Berkeley National Laboratory

The electricity crisis in South Africa has deteriorated significantly, with the country experiencing frequent and prolonged rolling blackouts. These outages have severe economic repercussions, leading to decreased growth and productivity. Demand Side Management (DSM), particularly focusing on electric water heaters due to their significant energy consumption and peak demand contribution, is identified as a key strategy. The study aims to assess opportunities for DSM programs targeting water heating to reduce energy consumption and peak demand. It entails developing a bottom-up simulation model to establish a baseline scenario of water heating electricity load demand in 2023 and 2033, identifying technologies for energy reduction, estimating the impacts of a selected number of measures and providing recommendations to inform policy makers. The baseline assessment found that the maximum demand was 6,643 MW in 2023 during winter season and will increase to 7,478 MW in 2033, which is almost an increase of one stage of load shedding (1,000 MW). Therefore, this suggests that if no intervention is implemented in the short term, there will be more detrimental issues on the grid in the next 10 years than currently experienced in 2023. Among the ten technologies described, five measures were selected to be simulated to assess their impacts one energy and demand reduction. The study found that all interventions demonstrate a reduction in overall demand. However, the interventions that have a large impact on reducing demand during peak times have the consequence of high restorative loading effects, except indirect water heating load reduction through rooftop PV augmented with external switch. This intervention also shows the highest energy savings from the grid but at the trade-off of some level of user comfort. Insulation of Pipes shows a uniform reduction of demand for all 24 hours in a day and energy reduction of 1.1TWh in 2033 with no discomfort impact to consumers. Reducing the heating element rating has the potential to passively reduce morning and evening peaks and elongate the peak period resulting in a small increase in energy consumption of 0.2TWh. Controlled Switching shows a slight reduction in demand during the switching period with a slightly elevated demand after the switching period. Interestingly, energy is reduced in this scenario by 0.1TWh. Time of use electricity tariffs show a significant peak demand reduction with the consequence of a high restorative load when elements are turned back on. Results show significant energy savings of 1.1TWh due to the shifted load in the morning peak, where the PV systems are absorbing a portion of the restorative load from 10am onward as PV systems are forecasted to increase 30% penetration by 2030 in the baseline scenario. In light of these results, it is clear that no silver bullet exist but that a comprehensive policy package is necessary, combining various strategies, regulations, incentives, and enforcement mechanisms to optimize load management and reduce energy consumption.