ENERGY
Building grid-level data infrastructure South African energy startup Asoba is one of the companies enabling this change. While many renewable energy businesses focus on generation, the company focuses on the data and communication infrastructure required to coordinate distributed power. Their software platform integrates batteries, inverters, smart meters and building management systems, giving grid operators real-time visibility of demand, storage capacity and available generation across multiple sites. cost control, predictable pricing and carbon-reduction commitments demanded by international buyers.
Financiers have responded with improved funding models. Operations-and-maintenance contracts, wheeling frameworks and power-purchase agreements have made renewable projects accessible without heavy upfront capital. SMEs are increasingly adopting smaller systems, particularly as solar retailers expand into rentto-own or subscription models.
In eThekwini, for example, Asoba has supported projects that use AI-driven forecasting to predict consumption patterns at manufacturing facilities. When the grid is under pressure, the VPP can automatically draw power from industrial batteries or reduce non-critical usage. When solar panels produce excess energy at midday, that power can be stored or fed back, preventing grid instability. The result is a more resilient distribution system without needing to build a single new power plant.
Why this matters … South Africa’ s legacy grid was not designed for decentralised renewables. Coal stations provide steady baseload power, but intermittent solar and wind require forecasting, coordination and storage. Without datadriven balancing, even high renewable uptake can create instability. VPPs solve this by turning distributed assets into a controllable, dispatchable resource.
Asoba’ s work demonstrates this shift. In one project with a national logistics operator, the company integrated solar and storage across multiple depots and linked them into a central platform. The operator is now able to avoid grid peaks, reduce diesel usage and send power into the network where local infrastructure allows it. Importantly, this adds resilience for the municipality, lowering strain during peak demand hours.
The economics have changed Renewables are no longer a premium option. Solar pricing has steadily declined, and battery costs have dropped sharply as global supply chains scaled up. Grid-tied commercial systems now reach payback in as little as three to five years. For large energy users, it’ s no longer just about backup power; it is about long-term
Is stability guaranteed? Despite this progress, challenges remain. South Africa still requires major investment in transmission lines to connect renewable-rich regions like the Northern and Western Cape with major load centres. Municipalities face capacity and skills gaps in managing wheeling, tariff structures and embedded generation. And while Eskom’ s unplanned outages have decreased, the fleet remains old and maintenance-intensive.
Grid modernisation is therefore the critical next step. Without upgraded substations, automation systems and digital monitoring, municipalities cannot safely integrate high levels of rooftop solar and storage. This is where VPPs and grid-level data platforms become essential. If the country can see and manage real-time energy flows, it can unlock far more private generation without sacrificing stability.
A new model for South African energy
The last year has proven that stability is possible, not because load shedding disappeared on its own, but because the system changed fundamentally. Instead of a single utility supplying the entire nation, South Africa is moving towards a multi-source ecosystem of utility-scale renewables, embedded commercial generation, rooftop solar and coordinated storage.
If policy continues evolving, and if grid operators adopt digital balancing tools at scale, the country can build on its current momentum. A“ load shedding-free” South Africa doesn’ t need to be an exception; it can become the expected norm. �
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