Abstract：As a key electrical equipment, the operational continuity and reliability of pumped storage units are of great significance to the construction of new power systems. In view of the multiple factors such as unbalanced electromagnetic force, thermal stress, and external mechanical stress, the inter-turn insulation of the excitation winding is susceptible to deterioration during the operation. How to quickly and accurately extract the early weak fault characteristics of inter-turn short circuit(ITSC) and organise timely condition maintenance is of great significance. To address the problem that the condition monitoring of ITSC faults in the excitation winding is susceptible to dynamic/static eccentricity and armature response, and early fault characteristics are difficult to identify effectively, this study proposes a fault diagnosis method based on time-frequency map of circulating current(TFMCC). Firstly, this study derives the equations for the same phase multi-branch circulating current in the dynamic/static eccentricity and static eccentricity composite ITSC states, and obtains the characteristic harmonics of circulating current in each state. Secondly, a two-dimensional finite element simulation model of 334 MVA is constructed, and the magnitude of the same phase branch circulating current under each state are calculated. Comparative experiments have verified that TFMCC can effectively distinguish between eccentricity, armature reaction disturbance and ITSC faults. Finally, based on the salient synchronous generator simulation platform, the operating conditions of ITSC with different fault levels are simulated. Simulation results show that changes in the degree of dynamic/static eccentricity cause time domain amplitude of circulating current changes, and that armature response and dynamic eccentricity also cause the appearance of characteristic fractional harmonics, so that ITSC fault diagnosis by a single time domain analysis or spectrum analysis can easily lead to fault misclassification. The TFMCC allows the fault to be clearly located at the moment of occurrence, and the signal intensity at the characteristic frequencies (5.5 Hz, 11 Hz, 22 Hz, 28 Hz, 39 Hz, 44.5 Hz) is significantly enhanced compared to the normal state, while a comparison with the dynamic/static eccentricity shows that the signal intensity of the dynamic eccentricity is mainly concentrated at 55.5 Hz and the static eccentricity is mainly concentrated at 50 Hz. The signal intensity distribution is clearly differentiated from that of ITSC faults. Further calculations of the signal intensity difference energy ratio(SIDER) show the results are 7.13%, 13.96% for the no-load ITSC condition and 6.66%, 13.44% for the load ITSC condition, both of which are much greater than zero, which can effectively identify the ITSC faults. The experiments on salient synchronous generator show that: the TFMCC of static eccentric compound ITSC 2.5%, 5% and 7.5% under no-load condition, the signal intensity at the intersection of time and characteristic frequency has changed significantly, and the signal intensity differences at 25 Hz before and after the fault are 13.05 dB, 21.06 dB and 29.86 dB, respectively. Further calculate the SIDER are 4.16%, 5.23% and 11.11%, respectively. Meanwhile the static eccentricity compound ITSC of 1%, 2.5% and 4.9% under load condition, the signal intensity differences at 25 Hz before and after the fault are 29.64 dB, 38.56 dB and 71.81 dB, respectively. Further calculate the SIDER are 2.28%, 3.13% and 15.68% respectively, which shows that the method can effectively detect weak ITSC faults and locate the time of fault occurrence. The experimental results demonstrate that the method is effective in eliminating static eccentricity and armature response disturbances, and visualises the operating conditions of the unit with a three-dimensional map containing operating time, characteristic frequency and signal intensity. At the same time, in order to effectively identify weak ITSC faults, this study also calculates the SIDER of time-frequency matrix can further quantify the magnitude of the fault and prevent fault false alarms, which can provide guidance for field operation and inspection personnel to carry out condition maintenance work.
齐鹏, 李永刚, 马明晗, 武玉才, 纪璇. 基于环流时频图谱的抽水蓄能机组励磁绕组匝间短路故障诊断研究[J]. 电工技术学报, 0, (): 63-63.
Qi Peng, Li Yonggang, Ma Minghan, Wu Yucai, Ji Xuan. Diagnosis of Inter-turn Short Circuit in Excitation Winding of Pumped Storage Units Based on Time-frequency Map of Circulating Current. Transactions of China Electrotechnical Society, 0, (): 63-63.
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