Description
A Master of Science thesis in Electrical Engineering by Abdelrahman Khaled entitled, "ESDD Prediction of Outdoor Polymer Insulators," submitted in June 2015. Thesis advisor is Dr. Ayman Hassan El-Hag and thesis co-advisor is Dr. Khaled Assaleh. Soft and hard copy available.
Abstract
Reliable power transmission is a main factor in designing transmission and distribution lines. Contaminated environments significantly reduce the performance of outdoor insulators in which the accumulation of contamination eventually leads to a complete flashover. The main factors that lead to contamination flashover include, operating voltage, humidity level and temperature. Contamination flashover happens when soluble or non-soluble deposits cover the surface of the insulator, which results in a reduction of the surface resistance. The flashover event is the main problem that affects the life-time of the insulators reducing the security and reliability of the power transmission system. Controlling the risk of flashover is practically done by cleaning and replacing heavily polluted insulators. However, there is no standard technique for scheduling cleaning or maintenance of outdoor insulators, which in some cases can extend for hundreds of kilometers. To make this process as efficient as possible, many researchers are trying to develop techniques for flashover prediction. In the past, some researchers used the leakage current to predict the contamination level on the surface of ceramic and porcelain outdoor insulators. This can help as a mean to warn transmission power operators about the advent of contamination flashover. However, there have been few researches to predict the contamination levels on the surface of non-composite or polymer insulators. This work aims to develop a practical technique to monitor and evaluate the surface condition of non-composite by predicting the soluble contamination level. In this research, the leakage current was used to predict the soluble salt deposit on the surface of polymer insulators. Based on this prediction the surface condition of the insulator was evaluated.