Methodology Study Of On-line Partial Discharge Monitoring And Analysis For Large Generator

Large generators, as the main power source, are the key equipment in the power system, so the safety of their operation has always been the highest priority. One of the main threats of generator's safe and reliable operation is from insulation system. The partial discharge (PD) activity is an important symptom of stator insulation deterioration. Therefore, the on-line PD monitoring has been used as an effective method for a long time to detect and diagnose insulation deterioration of generator, which is an important content of generator condition monitoring and also a hot and difficult study. Based on summarizing the existing methods and researches on PD monitoring technique, this dissertation is focused on research the generator on-line monitoring and analysis method, the research is combined with the needs of Gezhouba Hydro Power Plant and the specific parameters of its generators. The methodology and technique are comprehensively investigated on integration of theory with practice.In order to meet the needs of Gezhouba Hydro Power Plant, a PD on-line monitoring system mounted at neutral for large electric generators is designed, which uses the wideband measurement technique to obtain PD signal in the generator's neutral point. To provide a PD integrated monitoring and remote diagnostics platform, the system adopts the framework of hierarchical network structure. Then the effectiveness to obtain high-frequency signals of the PD sensor is demonstrated. And the comparison between the method of PD sensor mounted at neutral and the PDA method which is popular is carried out, it is found that the method of PD sensor mounted at neutral has the advantage in the equipment cost, reliability, comprehensive monitoring results and sensitivity of detecting PD occurred at the medium voltage windings. The high-speed data collection and analysis techniques are used to enhance the response capability to the stator insulation transient failure. Aiming at enhancing the sensitivity of the monitoring, the automatic amplification switching method is designed. Particularly, considering the influence of the operating states of the generator on PD, a variety of storage mechanisms for data storage is proposed to capture all PD features in different operating states with less data redundancy, and the operating conditions, load, signal mutation, signal strength and so on are all took into account in data storage.Employing the specific parameters of generator in Gezhouba Hydro Power Plant, the reliability issues of the PD sensor was systematically analyzed, including the reliability of the PD sensor body and the the reliability of the installation of PD sensor. The reliability of PD sensor body during normal operation of generator is explained firstly. By using the steady-state computational method, the magnitude of the neutral steady-state voltage was investigated when there was an asymmetry short fault at the generator expert bus, and then the high reliability of PD sensor when the generator in asymmetry short fault is verified. Subsequently, the impact of the PD sensor installation on the generator's single-phase grounding fault including zero sequence voltage protection, third harmonic protection, grounding fault current and high-voltage system transmission overvoltage is investigated. Two simulation models, which are transient network analysis model and quasi-distributed parameter model, are separately adopted to investigate the impact of the PD sensor installation on the overvoltage of non-fault phase and the neutral when the single phase grounding fault occurs at export bus and internal stator windings of the generator.The time domain energy distribution character of the background noise is studied in theory, and the sliding energy window method which could determine pulses boundaries is designed. Based on the effective extraction of the single pulse waveform, two pulses identification methods (a) adaptive clustering algorithm and three-dimensional distribution (b) synthetic features extraction in time and frequency domain are proposed. Some effective schemes are proposed to solve out the problem of the adaptive clustering algorithm when used in practical application. Wavelet energy distribution and spectra space energy distribution are extracted as the pulses frequency domain features. To overcome the three problems in wavelet analysis, which are difficult to determine the decomposition level, difficult to select the mother wavelet and difficult to choose the denoising threshold, solutions, including adopting the lowest identification frequency of pulses to determine the decomposition level, applying the correlation coefficient method to select the mother wavelet and adopting the 3a threshold method, are put forward respectively. The statistical parameters of two-dimensional diagram were applied for pulses identification. The basic principles of both pulse identification methods are introduced and the comparison between both methods has been undertaken. Finally, method (b) was determined as the best option for field application.The pulses comprehensive analyzed method is designed to decrease the information waste for on-line PD monitoring, which implements corresponding special analysis to different excitation pulses, diagnoses the state of the excitation source, and finally achieves the monitoring and diagnosis of the generator comprehensive operation condition. Methods to analyze PD pulses, arc pulses and pulses generated by excitation system have been respectively set up. Traditional monitoring system only analyzes PD in isolation, which is unreasonable. Based on investigating the influence factors of PD, the PD integrated analysis method is employed to ensure a more accurate result, which combines with the operation state information of the generator to implement PD synthetical analysis.Nowadays, the PD on-line monitoring system mounted at neutral for large electric generators has been put into on-line operation in Gezhouba Hydro Power Plant, which has got plenty of pulses signal and basically established the knowledge database for filed pulses, it'smonitoring and analysis results can describe the stator insulation state well. All the achievements are meaningful for carrying out condition-based maintenance and improving PD on-line monitoring research for generator.