ZnO lightning arresters are the best device for protecting electrical power systems from transient overvoltages generated by lightning discharges and switching operations. However, ZnO lightning arresters deteriorate by repetitive use, absorption of environmental moisture, and manufacturing defects.
The deteriorated lightning arrester can cause to accidents such as a line-to-ground fault or an explosion that may occur even at the normal operating voltage. Therefore, it is necessary to perform online monitoring of lightning arresters, especially for GIS lightning arrester facilities, and promptly replace the deteriorated lightning arrester to ensure the reliability of the power supply.
Various diagnostic methods for ZnO arresters have been proposed mainly based on measurements of the leakage current, and those have been found to be difficult in the measurement of leakage current because of the power system voltage harmonics and the electromagnetic interferences. I have experimentally studied the leakage current vs. the surface temperature of an arrester and the ambient temperature vs. the leakage current of one to propose high reliable diagnostic techniques for lightning arresters.
Leakage currents are also influenced by the magnitude of the system voltage and its harmonic components, so these influences have been analyzed to improve the reliability of arrester diagnosis.
The resistive component of the leakage current flowing through arresters is an important indicator of deterioration, but the total leakage current and its harmonic analysis are widely used in diagnosing the soundness of arresters because of difficulties in measuring resistive leakage current.
In this dissertation, a new method of measuring resistive leakage current is proposed, which is quite different from conventional methods such as self-canceling and the synchronous rectification methods. To confirm the effectiveness of the resistive current detection algorithm, a leakage current detector and analysis program have been designed and fabricated. From the experimental results, it has been confirmed that the proposed algorithm does not need a complex circuitry and is easy to complete.
A conventional surge counter set in a grounding conductor of a lightning arrester can perform a measurement only when a surge occurs and does not provide sufficient data on surge current. Information on surge current is important in evaluating arrester condition, and many parameters, like the amplitude, the polarity, and the time of surge current occurrence.
An intelligent surge counter that can record the date and time, polarity, and the amplitude of surge currents has been designed and fabricated utilizing microprocessor technology.
From the theoretical and experimental results, an expert system has been designed and implemented to monitor and diagnose lightning arresters in GIS substations. The expert system consists of a data acquisition module(DAM) based on microprocessor and diagnostic algorithms.
The DAM measures and analyzes several parameters necessary for the arrester diagnosis such as system voltages, leakage currents, surge currents and temperatures. All acquired data are transmitted to a remote computer by a low-rate wireless network specified in IEEE 802.15.4 to avoid electromagnetic interferences under high voltage and large current environments.
The decision-making of the arrester diagnosis is completed with a Java Expert System Shell(JESS), which is composed of a knowledge base, an inference engine and a graphic user interface(GUI).
In conclusion, it was verified that the proposed expert system could be very effective in monitoring and diagnosing lightning arresters in GIS substations.