Abstract
Leakage current and temperature are common features of zinc oxide (ZnO) arrester degradation in power systems; however, for substation engineers, these key features often bring difficulties in grasping the operating conditions of ZnO arresters because of insufficient maintenance references. Therefore, in this study, the aim is to propose a systematic method to facilitate the realization of predictive maintenance of ZnO arresters in energy systems. The method begins with the feature extraction of ZnO arresters by using on-line resistive current monitoring and infrared radiation (IR) image inspection. A regression model based on the temperature difference, the total leakage current, and the resistive leakage current is then formulated to assist in the insulation diagnosis. This approach is useful to observe the insulation condition, thereby benefiting the predictive maintenance of ZnO arresters. In order to validate the effectiveness of the method, it has been applied to inspect several ZnO arresters installed in a 345kV substation in Taiwan. Results show that this proposed method performs more effectively than published techniques.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International Journal of Electrical Power & Energy Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.