Optimal sizing of battery-less domestic rooftop PV systems in South Africa using a probabilistic electricity synthesiser

Abstract

Solar Photovoltaic, or PV, systems are the topic of conversation that has transpired globally due to their benefits of decelerating the rapid depletion of fossil fuels, providing a sustainable and clean energy source, and powering communities that lack access to electricity. Despite the abundance of sunshine in South Africa, the adoption of domestic rooftop solar has remained limited. The uncertain cost/benefit of large-scale battery-less solar installations plays a significant role in this, especially with the disparate levels of affluence. To mitigate the uncertainty of large-scale solar deployment, PV system design may be predicted using simulation. This provides users with a better understanding of the power savings that PV system adoption can offer. We present a data-driven model and synthesiser for South African households and a case study to test the suitability of such a model for the design and sizing of fixed-axis rooftop PV systems. The case study findings revealed that PV systems sized using synthesised days were slightly under-designed in comparison to systems sized using measured days. Using a roundup strategy, however, would result in almost all of the systems tested having the correct number of PV modules. Furthermore, we determine the economic viability of the sized PV system in South Africa based on the chosen export tariff.