Turning sunlight into smarter energy with AI

Client:

Emvelo

Services provided:

AI Clean Energy Data Engineering Machine Learning Optimisation Algorithms R&D

We worked with Emvelo to explore how artificial intelligence could unlock new efficiencies at the 100MW Ilanga CSP-1 solar plant in South Africa, increasing clean power for 100,000 homes and paving the way for a net-zero grid by 2050.

At a glance…

100MW solar power plant serving more than 100,000 households

340,000 tonnes of CO₂ displaced annually

£3m+ potential revenue uplift through AI optimisation

1,000+ sensors modelled into an AI-driven digital twin

The challenge

Emvelo had already achieved something remarkable with Ilanga CSP-1: a 100MW solar power plant capable of powering more than 100,000 homes. But their ambition didn’t stop there. To make the biggest possible impact – both financially and environmentally, the plant needed to deliver maximum output during the evening, when South Africa’s grid is under the greatest demand.

Achieving that goal, however, was far from simple. Running a concentrated solar power plant is a delicate balancing act, with operators constantly making complex decisions in real time. They needed a smarter way to manage the trade-offs between energy storage, generation, and unpredictable weather.

The main challenges came down to three critical questions:

When to use energy instantly and when to store it in molten salt tanks (Thermal Energy Storage) for after sunset.
How to forecast solar input accurately enough to make confident operating decisions.
How to meet peak evening demand, when grid exports are most valuable but the sun is no longer shining.

Our Approach

We began by tackling the plant’s vast data challenge. Every day, Ilanga CSP-1 generates high-resolution readings from more than a thousand sensors spread across the site. This information was originally stored in a proprietary format, making it difficult to query and analyse. Our first step was to transform this raw data into a streamlined, cloud-based data lake on Amazon S3 – making the information accessible, performant, and ready for AI modelling.

With the data re-engineered, we set about creating a digital twin of the plant. Using machine learning, we trained a statistical model that could accurately mirror the behaviour of Ilanga CSP-1. This allowed us to run safe experiments, testing different operating strategies and seeing how changes in control decisions would play out in the real world.

The final stage was to put optimisation techniques to the test. From simple brute-force searches to advanced genetic algorithms, we explored a range of approaches to discover the most effective way of balancing turbine generation with molten salt storage. Early results were promising, showing that AI-driven control could significantly increase evening energy output – exactly when the grid needs it most.

Results & Impact

The research phase showed that AI has significant potential to transform the way concentrated solar power plants are operated. By experimenting with digital twin modelling and optimisation techniques, we demonstrated how smarter control strategies could increase evening output, boosting both revenue opportunities and environmental impact. The findings provide a strong indication of what could be achieved with further development.

Alongside these broader outcomes, the research uncovered promising indications of what AI could achieve in this context:

£3m+ potential annual uplift suggested by early optimisation models
Increased CO₂ displacement potential, if evening generation can be improved
A validated digital twin, providing a reliable foundation for future experimentation

The research phase was only the beginning. With the potential of AI now proven, Emvelo’s focus has shifted to turning these insights into everyday operational tools. Together with Emvelo, we are developing a bespoke web application that will put optimisation directly into the hands of plant operators, enabling them to make faster, smarter decisions with confidence.

This next stage ensures that the impact of the project is not just theoretical but transformative, driving long-term value for Emvelo, their customers, and the climate. It also demonstrates how technology can play a critical role in accelerating South Africa’s journey towards a clean grid by 2050.

This collaboration has shown how AI can give clean energy operators the confidence to get more from every ray of sunshine.

Emvelo Team

See how he have helped