Topic
Energy aggregator: platform diversification for South African businesses
By Andre Nepgen, CEO of Discovery Green 11 September 2026
Commercial and industrial businesses in South Africa require stable, cost-effective renewable energy solutions to maintain long-term competitiveness. As the market evolves beyond traditional supply models, a platform approach provides stability. Discovery Green connects businesses to premium renewable generation facilities across the country. On the supply side, the platform blends solar and wind generation from geographically separate sites, which results in a steadier supply across the platform. On the demand side, it brings together businesses from a wide range of industries, whose different consumption patterns complement one another. The approach delivers greater coverage and cost certainty than standard trading models, enabling businesses to execute their renewable energy strategies efficiently and secure future operational requirements confidently.
For many businesses, renewable energy procurement means balancing three competing objectives: maximising renewable energy coverage, maximising savings and minimising risk. This trilemma is difficult to resolve, because improving one objective usually comes at the expense of another. Pushing coverage higher increases the risk that supply will not match demand, and the cost of wasted energy can erode savings, while keeping risk low tends to limit both coverage and savings. Discovery Green's platform, powered by its proprietary operating system, EnergyOS, is designed to solve this trilemma, helping businesses achieve higher coverage and greater savings while keeping risk in check.
Discovery Green operates a renewable energy platform that provides commercial and industrial businesses with cost certainty and high coverage. By diversifying across generation sources and customer consumption profiles, and managing renewable energy intelligently, the platform achieves higher coverage before wastage than a share-of-plant structure. It absorbs generation variability, offering a highly efficient alternative to standard trader and aggregator structures.
Key takeaways
- The trilemma: Renewable energy procurement involves balancing three competing objectives: high coverage, high savings and low risk. In most procurement models, improving one comes at the expense of the others.
- Share-of-plant limitations: Trader/aggregator models pass generation variability to the buyer via a share-of-plant structure, limiting the maximum coverage level the business can achieve before paying for wasted generation.
- Platform diversification: A platform combines multiple generation sources, such as solar and wind at geographically separate sites, with the consumption profiles of many businesses across different industries. Because these supply and demand patterns offset one another, the platform can deliver higher coverage before wastage than a single plant or business could on its own.
- Risk absorption: Discovery Green's take-and-pay structure absorbs wasted generation risk that trader/aggregator take-or-pay structures pass to the buyer, a structural difference that maximises long-term savings.
- Actuarial precision: Actuarial analysis determines your business's unique proposition before the contract structure is set. It extends into EnergyOS and intelligent risk management which ultimately delivers superior client outcomes. This cannot be replicated by a standard aggregator.
- EnergyOS: Discovery Green's proprietary operating system forecasts consumption, generation and market prices, customises how risk is shared, and allocates energy across the platform to maximise savings while minimising risk. Powered by Energy AI, it learns from actual outcomes with every cycle, allowing the system to become smarter over time.
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What an energy aggregator does in the South African market
The National Energy Regulator of South Africa (NERSA) wheeling framework enables commercial and industrial buyers to purchase privately generated electricity connected to the national grid. Within this regulatory environment, the standard trader or aggregator model uses a share-of-plant approach, selling businesses a fixed proportion of total kilowatt-hours generated by a specific plant each month. This structure means that the energy received by the business fluctuates directly with the generation output of that single facility.
While this approach provides access to renewable energy, it passes the inherent variability of weather-dependent generation directly to the buyer. Businesses must manage the financial implications when generation exceeds their consumption or falls short of their requirements. The legal basis for these transactions rests on the Electricity Regulation Act 4 of 2006 (ERA 2006), which governs how power moves across the national grid. Changes in client consumption can also erode savings under a share-of-plant approach / bilateral PPA due to the fact that a dip in energy consumption means businesses will pay for more energy than they can consume, which will erode savings.
Understanding the structural difference between this trader model and a platform model is essential for corporate energy procurement. The distinction determines long-term coverage and generation cost outcomes for large energy users. By aggregating geographically diverse generation assets and complementary consumption profiles, a platform can smooth portfolio-level variability and achieve higher renewable energy coverage before wastage occurs. This article explains how moving from a simple aggregation model to a sophisticated platform structure changes the risk position for South African businesses, ultimately delivering superior commercial results and greater predictability in energy expenditure.
The trader/aggregator model and its structural limitations
In a trader/aggregator model, the trilemma can show up in the trade-off between coverage and savings. At low levels of coverage, almost all renewable energy supplied is used, and savings rise steadily. As coverage increases, however, the risk of a mismatch between supply and demand grows. At certain times, supply begins to exceed the energy the business can actually use, and that wasted energy carries a cost. Once this cost is taken into account, marginal savings start to decline. Eventually, the cost of wasted energy outweighs the value of additional coverage, and total savings fall.
Businesses structuring their renewable energy procurement must carefully manage the point of declining marginal gains to ensure commercial viability. In the standard trader or aggregator model, as supply scales beyond the wasted generation threshold, the business pays for generation it does not consume. This effect increases the effective per-kWh price exponentially, with the business paying for electricity it does not consume, eroding savings. The share-of-plant structure inherently links the buyer's financial exposure to the specific generation profile of a single asset or a limited pool of assets.
Businesses will procure lower levels of coverage in order to ensure no electricity is wasted, but this in turn leaves a large portion of their consumption uncovered. By capping their renewable energy procurement below their actual consumption needs, these companies protect themselves from paying for wasted power during peak generation periods. While settling for lower coverage manages immediate cost exposure, it ultimately limits the effectiveness of a long-term renewable energy strategy, leaving a larger proportion of the business's consumption exposed to future electricity price increases. It also restricts the business's ability to reduce its carbon footprint and meet environmental targets, as a significant portion of its energy must still be sourced from the carbon-intensive national grid.
Many businesses choose to stop at what is known as the point of first wastage, where savings begin to level off. This carries a low risk of wastage, but it also delivers low coverage and only average savings. The assumption is often that coverage can be increased later by layering additional renewable energy on top. In practice, it is not that simple: adding supply beyond this point often means procuring more energy than the business can consume and paying for the wasted generation.
Other businesses aim for the point of maximum savings from the outset. This offers high coverage and a strong net present value (NPV), but it carries a high level of risk, because the outcome depends on generation performing exactly as expected and the business consuming exactly as forecast, which rarely happens in practice.
The structural limitations of renewable energy procurement strategies force a compromise between achieving high renewable energy coverage and maintaining cost efficiency. When a business relies on a simple pass-through mechanism for variable generation, it assumes the risk of that variability. To achieve higher coverage without incurring exponential costs for wasted generation, businesses require a model that actively manages and absorbs this variability rather than simply passing it through the billing structure.
How the platform model changes the risk position
A diversified platform model fundamentally improves a business's risk position by aggregating complementary generation sources and varied consumption profiles. The Discovery Green 740MW portfolio includes the Overberg Wind Farm (150MW, 489 GWh/year), the Tournee Solar Park (300MW, 720 GWh/year) and the Notsi Solar Farm (290MW, 914 GWh/year). Because solar generation peaks in summer and wind is stronger in winter, these geographically separate sites provide a natural offset. Physical diversification smooths the overall generation curve, providing a more consistent supply of power throughout the year.
Platform diversification across generation sources and consumption profiles significantly increases portfolio coverage before wastage occurs. When multiple industries draw from the same aggregated pool, their different usage patterns complement each other. An analysis included in Discovery Green's whitepaper illustrates the effect: combining the consumption profiles of businesses from different industries raised coverage before wastage from 49% for a single industry to 78% across five industries, as shown in Table 1.
Table 1: Coverage before wastage by number of industries on the platform
| Number of industries | Coverage before wastage |
|---|---|
| 1 industry | 49% |
| 2 industries | 64% |
| 3 industries | 74% |
| 4 industries | 77% |
| 5 industries | 78% |
A platform absorbing wasted generation risk through a take-and-pay structure presents a fundamentally different commercial proposition from a trader passing that risk to the buyer via a take-or-pay agreement. In a take-and-pay model, the business only pays for the electricity it actually consumes, removing the financial penalty associated with over-generation. This structure allows companies to target much higher renewable energy coverage levels without the fear of exponential price increases. By managing the complexity of generation variability at the platform level, Discovery Green provides businesses with the cost certainty required for long-term financial planning and operational stability. Our platform model also allows for this energy to be re-allocated to another client on the platform.
Why the trilemma is so hard to solve
Balancing coverage, savings and risk would be far simpler if the conditions behind each procurement decision stayed fixed: if generation and consumption were consistent, if all businesses were the same, and if energy market prices stayed the same. In reality, each of these conditions is highly variable.
Generation and consumption are volatile
Renewable generation varies from day to day and from month to month. Discovery Green's own wind and solar data shows that no two days, and no two months, produce the same output. Consumption is just as variable. Discovery Green's client data shows that consumption can vary significantly from month to month, even within a single business. Across industries, no two businesses use energy in the same way, at the same times or in the same quantities. A hotel in December and a brick manufacturer during the builders' break have very different energy needs.
Every business has unique operations and needs
Beyond differences in consumption, businesses face different operational realities, risks and priorities. Some schedule planned maintenance that lasts for months at a time, some plan over shorter time horizons, and some prioritise cost savings while others focus on environmental, social and governance (ESG) targets. A single, standardised contract structure cannot serve all of them equally well.
The energy market is constantly changing
South Africa's electricity sector is undergoing significant reform. Tariff structures are being revised, with fixed and variable charges being unbundled. Growing solar adoption is affecting time-of-use pricing, and the development of the South African Wholesale Electricity Market (SAWEM) may change how electricity is priced. A procurement decision based on today's prices alone may not hold in tomorrow's market.
This is what makes the trilemma so difficult to solve: the challenge is to increase coverage, optimise savings and manage risk at the same time, in a market where none of these conditions stay fixed.
EnergyOS: Discovery Green's proprietary operating system
Discovery Green built EnergyOS to solve this trilemma. EnergyOS, Discovery Green's proprietary operating system, underpins the platform. It combines a proprietary data lake with three models that forecast, customise and allocate energy. EnergyAI operates as the continuous reinforcement learning loop that powers the entire system.
- Data lake: A continuously growing, multi-layered and proprietary store of consumption, generation, market and product data that feeds every model. As EnergyOS makes allocation decisions, the actual outcomes are fed back in, so that the model's predictions are continually verified against reality.
- Forecasting model: Built in three layers. The consumption layer uses client consumption data to simulate possible future consumption pathways, first for each client and then across the full client book. The generation layer uses granular solar and wind data to model hourly probability distributions by technology and simulate long-term generation pathways, so that the likelihood of different generation outcomes can be understood and managed. The market price layer is a bottom-up demand and supply model, built from first principles using actuarial and economic best practice. This allows Discovery Green to forecast future market prices.
- Customisation model: Most energy traders aggregate renewable generation but still pass the risk straight through to the client. Discovery Green draws on more than 30 years of actuarial expertise to customise the risk itself, helping each business decide which risks it keeps and which Discovery Green carries. Risk is actively priced, managed and shared, rather than simply transferred to the customer.
- Allocation model: Overlays hundreds of thousands of potential generation pathways with hundreds of thousands of consumption pathways, and runs millions of potential allocation scenarios for each combination. It narrows these down to the scenarios that optimise client outcomes and meet contractual commitments, and selects the one that offers the best outcome for all clients. The model adjusts dynamically each month, taking prior experience into account.
- EnergyAI: The actuarial intelligence layer running through EnergyOS creates a continuous reinforcement learning loop. As actual generation, consumption, pricing and allocation outcomes are observed, they are fed back into the models to improve forecast accuracy, pricing precision and allocation decisions. EnergyOS becomes more intelligent with every cycle.
Precision in energy modelling ensures that each business receives a generation mix suited to its specific consumption profile. Discovery Green uses an actuarial energy modelling analysis to determine the optimal solar and wind blend for different sectors. This mathematical approach analyses each business's consumption profile to construct a highly efficient supply structure. Table 2 shows the optimal blend for three example sectors.
Table 2: Optimal solar and wind blend by industry sector
| Industry sector | Optimal solar blend | Optimal wind blend |
|---|---|---|
| Commercial property | 39% | 61% |
| Chemical manufacturing | 23% | 77% |
| Metal processing | 8% | 92% |
This actuarial methodology forms the foundation of the platform's design. By applying this rigorous approach, Discovery Green absorbs wasted generation risk through a take-and-pay structure, whereas traditional traders use take-or-pay models that pass this risk to the buyer.
Discovery Green's structured framework supports a large client base drawn from a diverse range of industries. These clients benefit from a model that translates complex generation data into predictable commercial terms. This approach also assists businesses in managing their obligations under the Carbon Tax Act 15 of 2019, as higher renewable coverage directly reduces exposure to domestic carbon pricing. By relying on verified data and actuarial precision, Discovery Green offers the highest coverage in the market (90%) and therefore the highest emissions reduction.
The result is better outcomes for clients. EnergyOS helps businesses maximise their savings while minimising risk, through a renewable energy solution they can trust to remain robust as market conditions change. In practical terms, it is designed to maximise net present value (NPV), minimise NPV volatility and maximise renewable energy coverage, which in turn reduces emissions. This translates into 2x higher savings, 88% lower volatility and 90% renewable energy coverage.
Frequently asked questions
What is an energy aggregator in South Africa?
An energy aggregator is similar to an energy trader. A trader contracts to buy renewable solar and wind energy from independent power producers (IPPs) and sells this energy to businesses at a trading margin, passing the IPP contract terms and risks through to the business almost entirely. Each business is assigned a specific plant, or a portion of a specific plant. An aggregator works in a similar way, but absorbs marginally more risk and provides businesses with a packaged energy profile from a number of generation assets. In South Africa, both models operate within the Electricity Regulation Act 4 of 2006 (ERA 2006) framework and typically offer a take-or-pay structure with limits, so the business still carries much of the risk when generation does not match its consumption.
What is an energy aggregator in South Africa?
An energy aggregator is similar to an energy trader. A trader contracts to buy renewable solar and wind energy from independent power producers (IPPs) and sells this energy to businesses at a trading margin, passing the IPP contract terms and risks through to the business almost entirely. Each business is assigned a specific plant, or a portion of a specific plant. An aggregator works in a similar way, but absorbs marginally more risk and provides businesses with a packaged energy profile from a number of generation assets. In South Africa, both models operate within the Electricity Regulation Act 4 of 2006 (ERA 2006) framework and typically offer a take-or-pay structure with limits, so the business still carries much of the risk when generation does not match its consumption.
What is the difference between an energy aggregator and a renewable energy platform?
A renewable energy platform absorbs wasted generation risk through a take-and-pay structure, whereas an energy aggregator typically uses a take-or-pay model that passes generation variability to the buyer. The platform model uses actuarial analysis to optimise the solar and wind blend for each business's consumption profile, delivering higher coverage before wastage occurs. By combining different consumption profiles and geographically separate generation sites, a platform smooths the overall supply curve. This structural difference means that businesses using a platform can achieve significantly higher renewable energy coverage without facing the exponential price increases associated with wasted generation in a standard aggregator model.
How does platform diversification increase renewable energy coverage?
Platform diversification increases renewable energy coverage by combining different generation sources and business consumption profiles to create a natural offset. Because solar generation peaks in summer and wind is stronger in winter, these sources complement each other. Similarly, different consumption profiles have varying peak usage times. When these diverse profiles are combined within a single platform, the aggregated demand matches the aggregated supply more closely, drastically reducing wasted generation. For example, an analysis included in Discovery Green's whitepaper found that combining the consumption profiles of five industries increased coverage before wastage from 49% to 78%.
How long does it take to get a proposal from Discovery Green?
A customised energy proposal from Discovery Green is typically completed within 10 business days of receiving a business's 12 months of interval consumption data. This allows businesses to quickly evaluate their options and understand the exact commercial implications of joining the platform. The proposal details the projected coverage levels and generation cost savings of a solution designed to meet the company's operational requirements without exposing them to wasted generation risk.
What is EnergyOS?
EnergyOS is Discovery Green's proprietary operating system. It combines a proprietary data lake with models that forecast consumption, generation and energy market prices, customise how risk is shared between each business and Discovery Green, and allocate energy across the platform to deliver the best outcome for all clients. EnergyAI, a continuous reinforcement learning loop, feeds actual outcomes back into the models so that forecasting, pricing and allocation improve over time. The aim is to help businesses maximise savings and renewable energy coverage while minimising risk.
Conclusion
The South African renewable energy market offers commercial and industrial businesses clear pathways to secure their long-term operational requirements. By moving beyond standard trader models to a diversified platform approach, businesses achieve greater coverage and cost certainty. Discovery Green's proprietary operating system, EnergyOS, and the platform's secured grid capacity provide a secure structure for this transition, absorbing generation risk and optimising the energy mix. Requesting a customised energy assessment is the practical next step to quantify these advantages and implement a resilient, cost-effective energy strategy.
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[1] Discovery Green, whitepaper (discoverygreenwhitepaper.pdf). Page and table references are given in the text.
[2] National Energy Regulator of South Africa (NERSA), nersa.org.za.
[3] Electricity Regulation Act 4 of 2006, Government Gazette.
[4] Discovery Green project data (RR-PR1 and STATS).
[5] South African Revenue Service (SARS), Carbon Tax Act 15 of 2019.
[6] Statistics South Africa, statssa.gov.za.
About the author
Andre Nepgen is the CEO of Discovery Green, leading the development of Discovery Green's renewable energy platform for South African businesses. With extensive experience in energy markets and commercial strategy, he focuses on delivering cost certainty and portfolio diversification to large commercial and industrial energy users. His work ensures that corporate energy procurement aligns with long-term financial and operational objectives.
Contact: support.discoverygreen@discovery.co.za | +27 11 529 2888 | www.discoverygreen.co.za