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Title: | Condition monitoring of squirrel cage induction generators in wind turbines | Authors: | Kuiler, Ian Radcliffe | Keywords: | Wind power plants;Wind energy conversion systems;Renewable energy sources;Squirrel cage motors | Issue Date: | 2017 | Publisher: | Cape Peninsula University of Technology | Abstract: | Globally governments are faced with challenges in the energy sector which are exacerbated by uncertain financial markets and resource limitations. The over utilization of fossil fuels for electricity generation has had a profound impact on the climatic conditions on earth. Coal power stations release carbon dioxide (CO2) during the combustion process and studies show that concentrations have sharply risen in the atmosphere. Adverse environmental conditions like global warming exist as a result of high greenhouse gas (GHG) emissions in particular CO2. In 2015 Eskom constructed Sere Wind farm with a supply capability of 100 MW. Due to the lack of technical expertise and skills with regard to the new technology within Eskom, Siemens was offered a 5 year maintenance contract. Siemens also provides training on basic operation and maintenance (O&M) of the wind farm to Eskom staff. This excludes specialised training on Siemens Turbine Condition Monitoring (TCM) systems which is a critical part to develop optimum maintenance strategies. This shortage of specialised skills in the application of condition monitoring techniques within Eskom is a major concern. If the most cost effective maintenance strategies during the contract period are implemented, the long term plant health and design life of Sere wind farm will be reduced. There is a need to develop new condition monitoring techniques to complement or address the shortcomings of the existing systems. Developing these skills will increase the understanding of the technology and improve the operating and maintenance of Sere wind farm. | Description: | Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2017. | URI: | http://hdl.handle.net/20.500.11838/2530 |
Appears in Collections: | Electrical, Electronic and Computer Engineering - Master's Degree |
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File | Description | Size | Format | |
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197069789-Kuiler-Ian Radcliffe-M.Eng-Electrical-Engineering-Eng-2017.pdf | Thesis | 2.31 MB | Adobe PDF | View/Open |
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