PREDICTIVE ANALYTICS BECOMES STATE-OF-THE-ART IN HYDROPOWER PLANTS’ MAINTENANCE

Together with the German AI specialist LexaTexer, Salzburg AG has tested the use of predictive maintenance at the hydroelectric power plant in Wald im Pinzgau. Based on the existing sensor technology and the application of artificial intelligence, a powerful model was created from a data pool that can not only predict the wear of the turbine runner. Among other things, digital tools were created as by-products with which anomalies in operation can be detected at an early stage. The findings from the pioneering project are so outstanding that the application has been rolled out to other power plants and further projects are being planned.

PREDICTIVE MAINTENANCE UNDER THE MAGNIFIER

At the power plant in Wald im Pinzgau, located a few 100 m below the world-famous Krimmler waterfalls, Salzburg AG tested the concept of predictive maintenance for the first time. The facility, which was commissioned in 1988, uses the difference in altitude of around 200m, between Krimml and Wald, to generate electricity. In summer, the plant can be operated as a run-of-the-river power plant, due to the high volume of in-flowing water. During the periods of lower water levels, in the autumn and winter months, the power plant is used to generate peak energy, with the aid of a daytime storage facility. "The Wald power plant was selected as a 'proof-of-concept' project, in order to test the practicality and economic viability of predictive maintenance. As opposed to condition-based maintenance, which is relatively easy to implement for easily accessible components, predictive maintenance focuses mainly on those components that cannot be monitored continuously, such as turbine impellers," Jörg Hinterberger, Innovation Manager at Salzburg AG, explains. The German company LexaTexer (LXTXR), which has made a name for itself as a specialist in Enterprise AI, i.e. the integration of artificial intelligence and data-driven solutions into industrial and production processes, was brought on board as a project partner. "Our customers mainly include manufacturers from the TIER 1 sector, i.e. automotive industry suppliers or the automotive industry itself, for example, Mercedes in Stuttgart. Salzburg AG was the first partner that gave us the opportunity to use our technology in the energy sector," says Günther Hoffmann, CEO of LexaTexer.

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We offer predictive analytics automation to help companies make direct decisions by integrating and analyzing unstructured, structured and alternative data with machine learning technology.

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