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DrehPunkt and Turbit provide deep software integration to the global wind operation market

Updated: Feb 1, 2023

The market leader for technical operations software rotorsoft and the AI technology leader in wind operations Turbit cooperate. rotorsoft enables the acceleration, optimization, and automation of complex workflows in operations management and monitoring renewable energy plants. Turbit has been developing AI monitoring technology for wind turbines for five years to bring predictive maintenance and AI-powered performance monitoring to technical operation teams that suit their day-to-day workflows.

DrehPunkt, founded 19 years ago, has been developing rotorsoft, an OEM-independent operations management software for international markets, monitoring more than 50 GW of renewable energy assets globally. Managing Director Stephan Thiemann explains, "In addition to analyzing SCADA data with standard monitoring algorithms, the deployment of self-learning systems becomes necessary to cope with the growing volume of plants under management and to increase detection reliability of fuzzy and early faults."

Turbit utilizes historical wind turbine SCADA data to learn the expected behavior of wind turbines per site using neural networks. Turbit permanently simulates normal behavior and compares it with actual sensor data. In addition to main components, the most complex conditions at the site due to wildlife regulations can be monitored using AI. Once deviations are detected, Turbit sends automatic alerts and in-depth analysis automatically into rotorsoft.

The AI cores of Turbit are deep neural networks continuously improving through semi-automatic feedback loops. These neural networks predict the root causes of abnormal machinery behavior. This process requires efficient workflows between Turbit, operations management, and service. "In the last five years, we have invested heavily in automated alerting, AI infrastructure, and work processes between operations management and the service teams, developing best practices. At the same time, there is still a lot to do," states Michael Tegtmeier.

Christian Fontius adds: "Our customers want to integrate Turbit alarms into their operations management software. So they can harness the added value from Turbit alarms efficiently. We are therefore very excited about the cooperation with DrehPunkt and the deep software integration of Turbit and rotorsoft."

"We at DrehPunkt have a lot of ambitions for the next years and are pleased, especially after consultation with our customers, to have found a strong AI partner in the wind sector that fits our needs," portrays Stephan Thiemann. As a first move, DrehPunkt and Turbit are pursuing a deep data integration. This integration will make it easy and more efficient for joint customers to use both products in rotorsoft.

Predictive maintenance and intelligent monitoring are rapidly gaining importance in the global wind sector. "With the deeper integration of rotorsoft and Turbit, we offer operators and managers a compelling solution and consolidate our leading position in analytics automation, monitoring, and optimization of renewable energy plants," adds Tino Korth.

About DrehPunkt GmbH

DrehPunkt GmbH, with offices in Rostock (headquarters) and Stralsund, develops rotorsoft, a software for mapping all processes of the operator and the manager necessary for monitoring wind turbines. So from data acquisition, monitoring, alerting, and other essential processes, such as Redispatch 2.0, to the generation of reports and the tracking of operations, the software covers all aspects of operations management. About 190 customers worldwide use rotorsoft for the optimal monitoring of more than 50 GW of installed capacity in the wind energy sector.

About Turbit GmbH

Turbit Systems GmbH, headquartered in Berlin, is an AI monitoring infrastructure for wind turbines and monitors more than 1500 wind turbines in Europe. Turbit develops and implements real-time AI monitoring for wind farms, enabling operations and asset management to act early on unnoticed underperformance or potential failures of main components to increase AEP. Semi-automated user feedback is constantly improving detection accuracy and increasing the relevance of automated predictions and analysis from Turbit AI.


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