PAW Industry Expert Round 5: Smart Energy


Tuesday, June 15, 2021


4:00 pm



1. Using Machine Learning to Optimize Power Plant Operations at Uniper (Tobias Mathur)

This session shows how Uniper used machine learning to increase the efficiency of a waste-to-energy power plant resulting in lower emissions and higher revenues in terms of heat, power, and gate fees. The presentation will focus on experiences and results from the field. We will furthermore discuss the relevance of this technology and how it can disrupt the power generation industry in the era of sustainability, energy transition, increasing competition, and ongoing global health crisis.

2. Predictive Maintenance by using Digital Twin in the Hydropower Plant of tomorrow for Verbund Hydro Power (Teresa Alberts)
The hydropower plant of the future will be a transparent power plant. What that means is that comprehensive, detailed information about the current and expected state of the plant will be available on a continuous basis, ideally precise to the second. With this, Verbund Hydro Power can identify the sweet spot in operation between performance and availability, balancing revenue and maintenance cost. Verbund Hydro Power GmbH – one of the major European hydropower companies – aims to achieve this goal using digital twins and virtual sensors. The implementation of digital twins is shown based on the turbine of a hydroelectric power plant at the example of the Austrian hydropower plant in Rabenstein. A technical set-up as well as lessons-learned and challenges during the implementation will be discussed.

3. Predictive Modelling of the Aerocondensor Performance of the Luminus CCGT Power Plant (Wout van Alphen)
In order to produce electricity and fulfill its grid stability services to the grid operator, Luminus needs to make accurate forecasts of the maximum production capacity of its CCGT power plant in Gent. Predicting the performance of the plant is a challenging problem, as it depends on a multitude of internal and external (e.g. weather) conditions. In this talk, we will briefly illustrate the AI solution that was implemented, and highlight the challenges and key takeaways of the solution process.

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