The Board of Trustees of the VGB-FORSCHUNGSSTIFTUNG awarded the VGB Innovation Award 2019 to
- Dr Marcel Richter (30) for the dynamic modelling of a coal-fired power plant for evaluation of flexibility measures (award category: future-oriented).
- Dr Meik Schlechtingen (35) for developing a model-based approach for wind turbine fault detection using SCADA data (award category: application-oriented).
The award, endowed with a total of 10,000€, was handed over by the VGB chairman on the occasion of the VGB Congress Power Plants 2019 in Salzburg, Austria.
Marcel Richter and Meik Schlechtingen were awarded with the VGB Innovation Award 2019 (from left to right: Dr Hans Bünting, Chairman of the VGB Board of Directors, Dr Marcel Richter, Dr Meik Schlechtingen, and Dr Oliver Then, VGB Executive Manager)
Marcel Richter studied mechanical engineering and management at the University of Duisburg-Essen and examined on Dynamic power plant simulation and techno-economic evaluation of flexibility measures.
He built-up a detailed dynamic model of a coal-fired power plant (Voerde, Unit A) using the Modelica library ClaRa in the simulation environment Dymola. Simulated and measured values showed good accordance in stationary load points and during transient load changes. On this basis, he identified an innovative integration concept of a thermal energy storage into the power plant process. A steam accumulator (Ruths storage) was integrated into the high-pressure preheating line operating on short-term intraday and primary control reserve markets.
Evaluation of flexibility measures with the dynamic power plant model contributes significantly to the current research topic of flexible power plant operation. Steag is thanked for supporting this work.
Meik Schlechtingen studied wind energy engineering at the Technical University Denmark DTU and examined on condition monitoring in wind turbines.
He described and applied a model-based approach for wind turbine fault detection using SCADA data. The approach is combined with vibration analysis to arrive at a global condition monitoring system. His work is referenced by many researchers. By using this method, EnBW AG has gained a very deep insight to turbine behaviour and early fault detection, with annual savings of several million €. The work turned out to be very relevant to operators in challenge of low CoE bids.
Latest publications showed the practical relevance and presented the very good experience with the methods and gave practical examples, which is important for operators and researchers to continue the work. Hence the work did not only show the theoretical potential, it also proved its value in practise.