An Adaptive Framework for Power Components Dynamic Loadability

An Adaptive Framework for Power Components Dynamic Loadability

Antonio Piccolo (University of Salerno, Italy), Pierluigi Siano (University of Salerno, Italy) and Gerasimos Rigatos (Unit of Industrial Automation, Industrial Systems Institute, Greece)
DOI: 10.4018/978-1-61520-849-4.ch012
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In electrical competitive markets, where deregulation and privatisation have determined changes in the organizational structures of the electricity supply industry as well as in the operation of power systems, utilities necessitate to change dynamically the loadability rating of power components without penalizing their serviceability. When assessing network load capability, the prediction of the Hot Spot Temperature (HST) of power components represents the most critical factor since it is essential to assess the thermal stress of the components, the loss of insulation life and the consequent risks of both technical and economical nature. In this chapter a general adaptive framework for power components dynamic loadability is proposed. In order to estimate the effectiveness of the adaptive framework, based on grey-box modelling, a specific case study, concerning the problem of forecasting the HST of a mineral-oil-immersed transformer, is presented.
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System abnormalities, loading, switching and ambient condition normally contribute towards accelerated aging and sudden failure of power components. In the absence of critical components monitoring, the failure risk is always high. For early fault detection and real time condition assessment, online monitoring system would be an important tool. On-line monitoring of power components can also provide a clear indication of their status and ageing behavior. Analysis of the collected data allows prudent asset management, foresighted investment budgeting as well as operation closer to or, for certain time periods, even above limits.

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