Main topics
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Development of a Condition and Risk Assessment Method for Assets of the Transmission Grid
Many electricity grid operators are under increased cost pressure due to changed competitive environment. In addition, the increasing energy flows in the course of the integration of renewable energies and their sector-linked usage require an expansion of the electricity grids, while at the same time a considerable number of assets must be renewed. In contrast, the digitalisation of electric grids, the development of new condition diagnosis procedures and the application of asset management offer potential to meet these challenges.
The research objective is to link existing reliability analysis procedures (FTA, FMEA, etc.) and modelling possibilities (e.g., Weibull distribution) with online and offline measurement and diagnostic procedures of high-voltage technology (e.g., partial discharge or tanδ measurement) in order to assess the risk of transmission grid assets and to derive recommendations for measures.
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Usage of Machine Learning for the Condition Assessment for Assets of the Transmission Grid
Many electricity grid operators are under increased cost pressure due to changed competitive environment. In addition, the increasing energy flows in the course of the integration of renewable energies and their sector-linked usage require an expansion of the electricity grids, while at the same time a considerable number of assets must be renewed. In contrast, the digitalisation of electric grids, the development of new condition diagnosis procedures and the application of asset management offer potential to meet these challenges.
The research objective is the automated evaluation of data from online and offline measurement and diagnostic procedures in high-voltage technology (e.g., DGA, resistance measurement, etc.) with the help of algorithms from the field of machine learning (neural networks, dimension reduction, etc.) in order to be able to derive statements about the condition of the asset. The programming is done in Python, although it is possible to learn the language first in this context.
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Investigations on Insulations for use in the E-Mobility Sector
The aim is to limit the global rise of temperature in a short period to below 2 °C – if possible below 1,5 °C. In order to achieve this objective, measures to reduce greenhouse gas emissions need to be implemented in all sectors. Consequently, these measures also affect the energy and power sector. In particular, the importance of energy efficiency measures and energy conservation becomes a major focus.
In research and development one focus is currently on the use of electric motors, because their demand will steadily increase in connection with the change towards electrification and mobilization. The expected increasing demand and higher requirements on electric motors require the development and implementation of manufacturing and quality testing processes. This development affects the quality and the life cycle, but also the reduction of material and production costs. There is a need for action, especially at the quality of the insulation. In contrast to the production of internal combustion engines, the production of electric motors is a stochastic process with fluctuations in quality level and high reject rates. A failure of a motor causes high costs not only in later operation, but also in production.
Thus, investigations of existing test and diagnostic possibilities and their derivative are necessary, as well as aging and material tests for new developed insulations.
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Development of an online monitoring sensor to determine the acid and water content in the paper insulation of power transformers
The energy transition poses a major challenge in terms of investment and security of supply. Transformers are a central element in the generation and distribution of electrical energy. The transformers installed in Germany are mostly older than the intended design life. One of the main causes of failure is the oil-paper-insulating of the windings. With increasing age, the acid content in the insulating oil is also increasing. Above all, the ageing of the insulation is accelerated by temperature and the type of acid. The acids change the dielectric properties of the oil and accelerate the breakdown of paper cellulose. In addition to high molecular weight acids, low molecular weight acids are also formed. It is mainly the low-molecular acids that are responsible for paper aging in combination with hydrolytic processes. It is therefore of great importance to be able to determine the aging condition of insulating paper at an early stage using suitable methods for condition monitoring.
Current methods for determining the acid content in insulating oil cannot provide accurate information on the paper condition, since the different types of acid remain in different concentrations in insulating oil and insulating paper. In addition, the current measurement methods only provide an integral view of the acid concentrations as "total acid number" or "neutralization number." With the new method, both the acid and the water are to be determined directly in the insulating paper according to concentration and type, which should enable a more accurate estimation of the condition of the paper, so that any measures to improve the condition of the insulation can be initiated in good time.
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