The Industry Challenge

Bring your own use case

Current Industry Challenge

Ready to make waste-to-energy operations smarter, more data-driven, and greener?

The Case

This is exactly what our industry partner, Wasteer, aims for. In 2026, efficient waste incineration is more than just burning waste.

To bring this vision to life, hessian. AI & Developer Student Club Darmstadt are proud to present a 24+ hour hackathon featuring challenges from Wasteer.

During this hackathon, teams will work with real industrial data to optimise the storage, mixing, and preparation of waste for incineration. Participants will tackle one of the most critical aspects of modern waste-to-energy systems: intelligent waste bunker management to maintain stable operations, maximise energy yield, and comply with regulations.

What to expect

50 selected participants working in teams
Hands-on experience with real-world industrial data
A unique opportunity to combine creativity, data science, and industrial expertise
An exciting challenges with attractive prizes

Prior Industry Challenges

Industry Challenge with TransnetBW

AI Serving Grid Stability

Anomaly Detection in the European Transmission Grid for Electricity

transnet-bw-logo

Reliable access to electricity at all times forms the backbone of our regional, national, and European infrastructure. To ensure this stability, control centers operated by grid operators continuously monitor the energy system.

The industry challenge “AI Serving Grid Stability”, organized by hessian.AI, TransnetBW, Fraunhofer IEE, and the House of Energy, demonstrated how AI can support this process. The participating teams developed models capable of detecting anomalies at an earlier stage, potentially reducing the need for costly countermeasures.

A compelling example of how AI can create real value in the energy sector.

The Case

Europeans are used to constant electricity supply and rarely experience blackouts. TransnetBW’s control room is one of the places where people are working 24/7 to maintain this seemingly inexhaustible flow. The company is one of four transmission system operators in Germany and industry partner of our Challenge 2023. Transmission system operators ensure that the electricity grid is stable. To do this, the same amount of electricity must be fed into the grid as is taken out at any point in time to maintain a frequency of 50 Hertz. To ensure this, TransnetBW uses automated control signals to instruct power plant operators to ramp up or down their infeed. In this challenge we look at the secondary reserve (a primary and a tertiary version also exists) that must be active after a maximum of 5 minutes.

Until recently, every European state used power plants in their own country to maintain the system balance. This has regularly led to the following situations: In Germany, for example, a power plant is ramped up and a few kilometers further across the border another power plant is ramped down. The costs that are incurred by this inefficient use of reserves are ultimately paid by all electricity customers. Since 2022, TransnetBW operates the PICASSO platform that coordinates the deployment of secondary reserve in real time, ensuring an optimal usage of reserves in a European domestic balancing market. This leads to macroeconomic savings of several hundred million euros per year and contributes to the decarbonization of the balancing market

The Challenge

The
Challenge

From its control room, TransnetBW operates the PICASSO platform and thus the world’s largest system for real time optimization of electricity flows. To ensure the correct functionality of the platform, information on imbalances, reserves, transmission capacities and many other time series are constantly monitored. These monitored features sometimes behave strangely, indicating to the control room engineers that it might be necessary to take action. Algorithms that recognize anomalies early and precisely may be of great help here. That’s why TransnetBW, in cooperation with Fraunhofer IEE, provides a previously unpublished data set consisting of various PICASSO platform time series to participants. An (AI) algorithm should be tuned to detect anomalies in platform operation. If this is successful, AI based solutions could support TransnetBW and other transmission system operators in better recognizing deviations from regular operation and in acting accordingly. The challenge aims at evaluating different solution methodologies in a short period of time and establishing personal contacts between industry and AI developers.

The Format

You could participate as an individual or as part of a team. Teams could be formed during the kickoff event, but team changes or new team formations were possible during the entire challenge duration.

The data set was available via the Kaggle platform. You could use your unrestricted toolbox of techniques and modules to solve the challenge. You could resubmit your result anytime until the deadline.

For discussions and requests, prior, during and after the challenge, we opened up a dedicated Discord server to check on the participants.

This challenge was not simply about working your magic with data, but also about fostering an exchange between the participants. This is why we planned events as well as working periods.