Title :
Diagnostic technologies for embedded intelligence in high voltage power equipment
Author_Institution :
Delft Univ. of Technol., Delft, Netherlands
Abstract :
In the future power grid, equipment will need to work with distributed generation, deregulation, and accelerating ageing factors. For smart operation without degrading the reliability of the system, there is a need to make a turn with diagnostics towards condition monitoring systems, which assess the actual performance of individual equipment. However, the emerging technologies for sensors specifically for high voltage equipment performance, interpretation tools and aging models needed for such smart grids are still in a premature stage. A few emerging monitor systems have achieved robustness to some extent. In this paper, the expectations and experiences for power equipment monitoring will be discussed. In addition a model-based framework to optimize usage of power equipment is proposed using a predictive health model.
Keywords :
condition monitoring; distributed power generation; electricity supply industry deregulation; high-voltage engineering; power apparatus; power generation reliability; smart power grids; accelerating ageing factors; condition monitoring systems; diagnostic technology; distributed power generation; embedded intelligence; high voltage power equipment; power deregulation; power system reliability; predictive health model; smart power grids; Aging; Loading; Monitoring; Optimization; Predictive models; Sensors; Stress; condition monitoring; decision making; diagnostic interpretation; diagnostics; high voltage; power grid intelligence; predictive health model; sensoring;
Conference_Titel :
Power and Energy Society General Meeting, 2011 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4577-1000-1
Electronic_ISBN :
1944-9925
DOI :
10.1109/PES.2011.6039612