Artificial intelligence for the energy industry
Discover innovative next-generation AI solutions for the energy industry!
Be a pioneer in the energy industry and shape a sustainable, efficient and customer-oriented energy future with the help of artificial intelligence! With our experienced team of data scientists, we at scieneers are happy to make our contribution to digitalization in the energy sector and support you with our experience from numerous innovative data projects.
Transformer models, such as the Temporal Fusion Transformer (TFT), can increase the accuracy of your forecasts required for efficient plant operation and also provide significant added value in the context of predictive maintenance and anomaly detection. In doing so, TFTs offer the highest interpretability and enable the generation of high-quality forecasts even for plants with comparatively short data histories (“cross-plant” learning) via so-called data fusion.
Complex processes, such as the grid connection process in the power grid, can be significantly accelerated through digitization – completely in the cloud if required – and using AI (e.g. for reading out documents, generating customer responses). AI can also be used for early detection of damages in your assets – novel transformer models such as Temporal Fusion Transformer (TFT) can add significant value here through increased accuracy and improved interpretability.
Benefit from more precise energy price forecasts and the fast inference of new transformer models such as the Temporal Fusion Transformer (TFT) – unlike many classic models, its inference is in the range of seconds and thus enables participation in intraday trading in 15-minute intervals. The schedules of your own power generation plants, which depend, for example, on load forecasts to be generated in real time, can also be optimized for intraday trading in this way.
Speech models can support your sales and customer service, for example through personalized e-mail campaigns and telephone customer approaches (text-to-speech technologies). The use of vector databases enables speech models to access company-specific information in the process. ChatGPT is not an option for privacy reasons? Open source models such as Llama 2 can be retrained (“fine-tuned”) for your specific use case and operated locally.
Have you already identified a concrete use case for your company that you would like to implement with us? Or is it still a vague idea that we want to substantiate together?
No matter where you are at the moment, it is not difficult to get started with AI in your company. We will be happy to take you on a joint journey to unfold the individual advantages of AI.
Data Fusion makes it possible to combine different data sources for model training. This helps to mitigate the “cold-start” problem (i.e. short data history for new assets). Instead of having to wait for a full season, data from existing assets can be used for new assets. Successes through initial reliable model results are achieved at an early stage.
Transformers are not black box models. On the contrary, they offer a very high degree of interpretability, giving decision makers insights into the underlying processes and crucial factors. This is how AI delivers comprehensible results.
The transformer architecture enables optimized pattern recognition. Adaptive learning often allows energy demands, peak loads and renewable energy generation to be predicted more accurately compared to classical models. High model quality opens up numerous application possibilities.
Our Director of Data Science
Dr. Lars Perchalla
will be happy to advise you in a non-binding initial consultation.
Real-world use cases and knowledge from the AI-driven energy industry.