Guiding the renewable energy transition with AI
From strategic advice to building AI solutions, ML6 empowers the energy industry to leverage the transformative potential of AI to drive innovation, efficiency, and sustainability.
Challenges facing the energy sector
The climate crisis is one of the defining challenges of our time, calling for a global energy transition from fossil fuels towards renewable energy sources. This transition requires a shift to decentralised energy production, electrification, and flexible consumption. Success will depend on smart grids and the digitalization of all involved players.
ML6 is here to help along each step of the way.
Predictive maintenance
Whether you are an energy producer, network operator, or industrial prosumer, preventing a breakdown of your infrastructure is crucial. Predictive maintenance helps you minimise costs by planning downtime at times of low energy prices for producers, low load for network operators, or high energy prices for consumers.
Flexible consumption
Consumers need to transition to flexible consumption if they want to limit their current and future energy costs. The future of energy is intermittent, and the spread between low and high energy prices will only rise. To stay competitive or even gain an edge, consumers need to start leveraging flexibility now. We can help assess your flexibility, monetize it, and decide where to invest towards the future.
Congestion management
The introduction and growth of distributed renewable energy combined with the lagging transition to flexible consumption is putting stress on our electricity transmission and distribution networks. AI can help with the optimization of both design and operation of these grids.
Data & AI readiness
A successful energy transition depends on smart grids and the digitalization of all involved players. Unfortunately, data is often locked in different source systems, while the management of AI models is inconsistent and lacking across the organisation. We guide our clients in their transformation towards a data-driven and AI-ready organisation.
Specific AI solutions for the energy sector
At ML6, we understand the unique challenges faced by the energy sector. Our extensive knowledge and AI expertise enable us to develop practical solutions tailored to your business needs. Here's how we help energy sector players tackle their specific challenges:
Forecasting
Renewable energy depends on environmental factors like the weather, leading to intermittency which requires flexible consumption. The better we can forecast the weather, energy production and consumption, and market prices, the better we can coordinate our actions in a distributed market.
Examples
Electricity demand forecasting
Price forecasting
Renewable energy integration forecasting
Simulation
Digital twins enable us to simulate physical systems with a virtual model. Through these simulations, we can explore various scenarios, identify constraints and bottlenecks, and understand system sensitivities or vulnerabilities. Knowing this allows us to make informed decisions about investments and operations.
Examples
Energy storage optimisation
Grid staibility analysis
Demand response planning
Optimisation
Based on the information obtained through forecasting and simulation, both the design and the operation of systems can be optimised. In the design phase, optimization can be applied to network topology, wind farm layout, and EMS configuration. During operation, optimization can improve congestion management, wind turbine steering, and EMS control.
Examples
Congestion management
Wind turbine steering optimisation
Energy management systems (EMS) configuration
Automation
The energy markets are continuously shifting towards shorter timeframes, requiring faster decision-taking by all parties. Through automation, we can enable real-time demand response management, trading and bidding, and asset steering.
Examples
Real-time demand response management
Asset steering and control
Trading and bidding automation
Success Stories
Turbine underperformance analysis to reduce power loss
ML6 helped Otary to reduce power losses from their wind turbines. Through modelling of the turbines, we identified both underperformance and its root causes.
ML6 built an intelligent controlling unit which operates on the bike and continuously calculates the most optimal engine settings. This results in adjustments in power output, torque adaptations, and a new eco-mode for maximum range.
Digital modelling of a hydrogen plant
ML6 developed a simulation engine for a green hydrogen plant for a party active in the development, financing, construction and operation of sustainable energy sources.
The construction of a green hydrogen plant requires a large capital investment, while the value depends on the availability of renewable energy and the supply chain towards consumers. Our simulation engine provided integral insights to support the investment decision.
We helped a provider of hydrogen storage technologies to increase the ROI of their storage solution. We developed a smart energy system to decide when to charge and discharge based on forecasting of production and consumption.
Cooling capacity forecasting
Our client, a global chemical manufacturer, wanted to forecast the cooling water temperature of their cooling tower to know exactly how much heat could be absorbed to optimally plan their production. Our algorithm allowed for a 2-8% increase of production during summer depending on the production line.
Why clients choose ML6
Years of experience in AI & Machine learning
AI & ML use cases
Leading international clients across industries
Knowledgeable data, AI & ML engineers
Of engineer time dedicated to research
Open source downloads per month
Blog posts and insights
Read our case studies and blog posts to learn more about our energy expertise.
