Insulator is an essential part of overhead line. In recent years, the news about the insulator flashover is increasing. The main reason of insulator flashover is insulator surface contamination. Insulator flashover is a serious threat to the safe and stable of transmission lines operation. With the development of China's comprehensive national strength, power companies and power users demand on grids stability is highly increased. Currently usual methods of insulator monitoring are ESDD (equivalent salt deposit density), experiment and on-line detecting of leakage current [. But they can't fully meet our requirements. Now this paper will present a new method, which is made correlation analysis by harmonic analysis based on two ends of the existing lines to the data acquisition apparatus of voltage and current signals. Without additional hardware devices online monitoring of insulator surface contamination can be achieved.
This paper does aging test about zinc oxide varistor and collects the waveform data from the arrester before and after aging, then uses numerical calculation and FFT to analyze the waveform data. Through comparing the changes of characteristic parameters before and after aging such as power loss of varistor, leakage current and every harmonic current, this paper can get the relationship between varistor aging and leakage current, especially the changes of resistive fundamental and harmonic current after aging. Based on analysis and study of aging characteristic parameters of the arresters, it can provide the basis of the judgment for putting forward a new online monitoring method and contributes to the application and development of MOA monitoring technology.
Metal oxide surge arresters (MOA) is a power system overvoltage protection device, and the online monitoring of the MOA is an important means to ensure the safe operation of the power system. This paper presents a new MOA insulation defects monitoring method. This method is based on the relative change in capacitance to MOA insulation defects as characteristic parameter, the aging classified as a kind of local defects, the system disturbance contains higher harmonic of transient voltage and current as the signal source, dynamically generated MOA partial insulation discriminant function of the defects in the diagnosis. The maximum value of the discriminant function corresponds to the local insulation defects. The proposed method contributes to the MOA monitoring methods and the development of technology.
Abstract. Now, there are many influencing factors of partial discharge(PD) for switchgear cabinet, but very few methods used for switchgear cabinet monitoring. In this paper, Partial discharge of switchgear cabinet is identified based on Least Square SVM (LSSVM) used for comprehensive evaluation of switchgear cabinet. Partial discharge ultrasonic signal of time and frequency domain are gave to get two stable characteristic bands in MATLAB tool. It provides a theoretical basis for partial discharge monitoring to ensure proper and efficient operation of the switchgear cabinet.
Transformer is the primary equipment of power system. The normal operation of transformers has great significance of the security and stability of a power system. Once partial discharge happened in the winds of a transformer, it will accelerate the aging of the insulation, and may damage the windings. This paper analyzes the effect of partial discharge to transformer windings, and founding a model of non-even distribution parameters. Separate the even distribution parameters model into three parts and partial discharge happens in the second one. The partial discharge leads to changing of the model parameters. And port voltage changes with it. Partial discharge detection achieved according to the changing of port voltage.
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