Early aging diagnosis of winding insulation is crucial for preventing insulation failures. However, early aging suffers from unclear mechanisms and weak changes of electrical parameters, which makes it difficult for mechanism and intelligent diagnosis approaches to achieve effective modeling. To address this issue, this article proposes a mechanism-guided intelligent enhancement method for early aging information based on the common-mode impedance spectrum. First, an effective mechanism knowledge focusing strategy is proposed, which can effectively alleviate coupling of aging mechanism features under different aging types, so as to provide the pure mechanism features for the dynamic knowledge matching. Then, a dynamic knowledge matching strategy is presented, by which aging mechanism features and early aging information are reliably matched, thereby supporting the strong generalization of the mechanism-guided reconstruction. Finally, a mechanism-guided reconstruction network is constructed to enhance the insulation early aging information, so as to achieve high accuracy and strong-generalization diagnosis modeling of insulation early aging. Notably, our method provides a promising solution for the diagnosis modeling of early aging. The experimental results on a 4-kW permanent magnet synchronous motor drive system demonstrate that our work outperforms the existing methods, which achieves the 60.74% reduction in the early aging diagnosis error of winding insulation.

The grid-connected photovoltaic (PV) power generation system which has multiple parallel DC modules is popularly applied in industry. In each DC-DC converter, the DC-link capacitor is the weak component which is subject to electrical property degradation. Most existing methods hardly achieve on-line capacitor diagnosis in economy and efficiency manners, considering the cost of measurement units and the effect of PV cables. In this paper, a high-efficiency diagnosis method for DC-link capacitors is proposed using two readily-available currents. The novelty lies in the linear relationship between the proposed current gain and the degradation degree at a certain characteristic frequency. The DC-link capacitor in each parallel branch can be diagnosed separately. Based on the built simulation model, the performance of the proposed DC-link capacitor diagnosis method is clarified with effectiveness and the effects of inherent harmonics and control strategies are investigated. The proposed current gain is not affected by voltage and current harmonics, as well as the varying load under the specified inverter control strategy. However, the proposed current gain is dependent on temperature and irradiance since the duty cycle of DC module is dynamically adjusted in the operation.

The reliability of underground power cables has become a critical issue in modern power systems. Due to the non-uniform operation stresses, segmental ageing will form in cable insulation, which will further result in insulation faults. Online detection of segmental ageing can lead to early and targeted maintenance, improving system reliability and save the operation cost, which is rarely studied in the existing researches. In this paper, a novel online segmental ageing detection method for underground power cables is proposed to fill the research gap. Instead of using conventional travelling wave signals, multi-frequency steady-state common-mode (CM) leakage current measurements are used to realize the online detection. The overall detection scheme is presented and the detection algorithm is also designed. Simulations and case studies prove the effectiveness of the proposed method. Accurate detection can be achieved with convenient algorithm implementation for cables of different lengths, structures and parameters.

Leakage current is an effective indicator for groundwall (GW) insulation condition of power transformers. The existing sensing technology based on magnetic shielding design and differential measurement principle enables on-line leakage current measurement from strong magnetic noises caused by load currents. The technology has been verified in the application of the traditional power system. In this paper, an improved method is proposed for harmonic leakage current measurement, with the goal of on-line GW insulation monitoring of converter-connected transformers in microgrids. First, the simulation model of modular multilevel converter system is built in MATLAB/ Simulink. The amplitude-frequency characteristics of the load current and the leakage current of the converter-connected transformer are analyzed. Second, the sensing performance of the improved method is investigated in converter harmonic frequency band, by considering the effect of the frequency-dependent core permeability. Third, the methodology is clarified to select the appropriate monitoring frequency with the highest sensitivity. Finally, a sensor unit with the dual-core structure is manufactured and its performance is verified by off-line and on-line experiments. On-line leakage current measurement is enabled with 1-mA sensitivity and 100-kHz bandwidth from strong noises caused by load currents up to 400-A.

The permanent magnet synchronous generator (PMSG) connected to pulse width modulation (PWM) rectifier is widely used in the renewable energy applications, such as direct–drive wind turbines and marine current turbines. The reliability of the PMSG is crucial due to the high maintenance cost of the turbines. The stator winding insulation is one of the main reasons for the PMSG failures. However, the current technologies can only detect the insulation failure when the short-circuit failure has already happened, which cannot avoid the corresponding downtime losses. Therefore, the online monitoring method for stator winding insulation is performed on the PMSG-PWM rectifier system in this paper for the first time. The factors affecting the voltage harmonics on the stator winding insulation are studied and their effects on the monitoring results are analyzed. Based on the flow path of the insulation leakage current and the phase-to-ground voltage, the insulation impedance can be measured online. The effects of the rotor position and the working condition are also analyzed. The effectiveness of the online condition monitoring method for PMSG-PWM rectifier system under various working conditions is verified using offline and online tests.