Optimal integration of solar home systems and appliance scheduling for residential homes under severe national load shedding - Sakhile Twala; Xianming Ye; Xiaohua Xia; Lijun Zhang (Journal of Automation and Intelligence)
In developing countries like South Africa, users experienced more than 1 030 hours of load shedding outages in just the first half of 2023 due to inadequate power supply from the national grid. Residential homes that cannot afford to take actions to mitigate the challenges of load shedding are severely inconvenienced as they have to reschedule their demand involuntarily. This study presents optimal strategies to guide households in determining suitable scheduling and sizing solutions for solar home systems to mitigate the inconvenience experienced by residents due to load shedding. To start with, we predict the load shedding stages that are used as input for the optimal strategies by using the K-Nearest Neighbour (KNN) algorithm. Based on an accurate forecast of the future load shedding patterns, we formulate the residents’ inconvenience and the loss of power supply probability during load shedding as the objective function. When solving the multi-objective optimisation problem, four different strategies to fight against load shedding are identified, namely (1) optimal home appliance scheduling (HAS) under load shedding; (2) optimal HAS supported by solar panels; (3) optimal HAS supported by batteries, and (4) optimal HAS supported by the solar home system with both solar panels and batteries. Among these strategies, appliance scheduling with an optimally sized 9.6 kWh battery and a 2.74 kWp panel array of five 550 Wp panels, eliminates the loss of power supply probability and reduces the inconvenience by 92% when tested under the South African load shedding cases in 2023.