Data intelligence for carbon neutrality
Digitization, decentralization, and decarbonization are driving the global transformation of energy systems.
Data intelligence provides essential resources to accelerate the transition to a carbon-neutral economy by reducing energy consumption, putting renewables at the heart of the grid, and getting more out of renewable generation assets. Digital energy is at the interface of digitization and sustainable energy, and builds on our expertise in solar photovoltaics, building energy management, ultra-low-power computing and secure IoT systems. We understand the needs of the power and energy industries in terms of reliability, security, scalability, and observability. We deliver solutions grounded in solid science, following best practices for software development.
Our solutions will help you transform your digital energy capabilities. Here are some examples:
- Fault identification and predictive maintenance: increase uptime and reduce maintenance and spare parts cost for renewable energy assets
- Estimation and activation of flexibility: manage local grid congestions
- Forecasting: high temporal and spatial resolutions support local energy management, networks, and market operations
- Processing of time series: pre-processing, storage, analytics, and forecasting
- Graph machine learning: reconstruct faulty data of PV production and forecast future generation values
- Data-driven models: technical systems, such as complete buildings or wind turbines, including linear state-space models with non-linear regressors and architectures based on recurrent neural networks, such as long short-term memory (LSTM) cells, encoder-decoder architectures, and transformers
- Data collection architectures: based on a mixture of commercial solutions and custom developments, such as the highly available instrumentation of tens of radiator valves in operational buildings for state estimation and optimal control
- Customized numerical algorithms: improve the applicability, scalability, and robustness of demanding computations. Applications include the training of data-driven models and the resolution of optimization problems, such as our patent-pending solution for optimal control of PV inverters or the aggregation and dispatch of flexibility provided by buildings.
Want to get involved?
We can help grid operators and energy providers create new services, improve asset management, and create value from the data they collect by exploiting cutting-edge data science. Effective data-driven solutions also help customers better benefit from the services supplied by system integrators and providers.
Get in touch to find out how you can get on board with digital energy today.
Meet our happy customers
Head of Engineering
CSEM is always a very good partner and this project is particularly important for us—and for all industrial settings—because it aims to change thinking as well as help produce more energy from renewable sources and use less energy overall.
We can now make the best use of data and predictive diagnostics to increase the energy production capabilities of wind farms. Given our experience with CSEM, we would like go further, and apply the same approch.