Mechen Liu

Bio: Mechen Liu is an academic researcher from North China Electric Power University. The author has contributed to research in topics: Partial discharge & DC bias. The author has an hindex of 1, co-authored 1 publications receiving 36 citations.

Growth and partial discharge characteristics of electrical tree in XLPE under AC-DC composite voltage

Abstract: The growth characteristics of electrical trees under DC and AC voltages are quite different. In order to investigate the influences of AC component in HVDC cable system on the electrical tree properties, the growth and discharge characteristics of electrical trees under AC-DC composite voltages were studied in this paper. The results showed that the AC component greatly accelerated the developing process of the electrical trees. The influences of the positive and negative DC bias voltages on the electrical tree growth properties were quite different. The growth rate under negative DC bias voltage was similar to that under pure AC voltage and pine-branch type electrical trees were more likely to form. In contrast, the growth rate of the electrical tree increased with the increase of the positive DC bias voltage and it was much faster than the negative DC biased one. More branch-like electrical trees would form under positive DC bias voltage. When the AC component decreased, the developing process of the electrical tree was fairly tough and it was easy to form bush-like electrical trees, which were the typical conducive electrical trees with fairly small discharges. Under the positive DC bias voltage, there was a fast re-growth process of electrical tree after the bush tree formed, and the positive DC bias voltage could promote the coming of the re-growth process. However, the detected partial discharge during this process was quite small. The test results indicated that it may pose a great threat to the safety of the cable insulation if there is a large AC component in the HVDC cable system.

Electrical tree degradation in high-voltage cable insulation: progress and challenges

Abstract: High-voltage direct current (HVDC) and high-voltage alternating current (HVAC) cables are the most important equipment for high-voltage, large-capacity and long-distance power transmission. Electrical tree is a pre-breakdown phenomenon leading to failure of insulation materials, and it is the major issue that threatens the safe and stable operation of HVDC and HVAC cable systems. This study summarises and analyses the achievements in the research of electrical tree for HVDC and HVAC cables. The initiation mechanisms of the electrical tree, including Maxwell electro-mechanical stress, charge injection–extraction, charge trapping and electroluminescence theories, are elaborated for fully understanding the electrical degradation process in insulation materials. Then, the influences of the high electric field, high temperature and mechanical stress on electrical tree behaviours are discussed, and the relationship between charge transport and the electrical tree is analysed and illustrated. The suppression methods of the electrical tree are put forward by introducing inorganic and organic additives into insulation materials, and the suppression mechanisms are presented from the viewpoints of the structure-property and microscale–macroscale relationships. Recently, the electrical tree research studies are focused on the high-precision of initiation models, high-dependence of multi-physical fields and high-efficiency of suppression methods. The achievements provide theoretical support for improving the electrical performance of insulation materials, while it is a practical problem to explore their application feasibility in HVDC and HVAC cable.

Trap Distribution and Dielectric Breakdown of Isotactic Polypropylene/Propylene Based Elastomer With Improved Flexibility for DC Cable Insulation

Abstract: In this paper, we report on electrical and mechanical properties of isotactic polypropylene (PP) blended with polyolefin elastomer (POE) and propylene-based elastomer (PBE). Carrier trap distribution of the samples was estimated by isothermal surface potential decay measurement, while dc breakdown strength was measured through a pair of semicircle electrodes. Elongation at break and tensile strength were obtained to examine the variation in mechanical property of PP caused by the addition of elastomers. Furthermore, scanning electron microscope (SEM), differential scanning calorimetry (DSC), and dynamic mechanical analysis (DMA) have been employed to assist the understanding of morphology of the blends, thermal properties, and mechanical properties. Obtained results have indicated that with the increase of the elastomer content from 0 to 30 wt%, the trap depth appeared to be shallower and the dc breakdown strength tended to be reduced for both PP/PBE and PP/POE samples. Compared with PP/POE blend, PP/PBE blend had deeper trap depth, which should be responsible for its higher dc breakdown strength. In addition, PP/PBE blend has presented a better performance in elongation at break and tensile strength measurement. With the growth of the elastomer content, the crystallinity of the blends appeared to decrease, whereas the melting and the crystallization temperatures did not change remarkably. The SEM inspections and DMA results revealed better compatibility between PP and PBE compared with that between PP and POE, which should be the reason for the better electrical and mechanical properties of PP/PBE blend. The blend of PBE with low content could result in remarkably improved flexibility of PP with acceptable electrical strength for dc cable insulation.

A Comprehensive Review of Signal Processing and Machine Learning Technologies for UHF PD Detection and Diagnosis (I): Preprocessing and Localization Approaches

Abstract: Partial discharge (PD) detection and diagnosis based on the ultra-high frequency (UHF) signals is one of the most widely adopted methods to evaluate the internal insulation status of high voltage equipment. Benefit from the rapid development of computing hardware and data processing algorithms, the intelligent PD fault diagnosis method based on the UHF data has made considerable progress in the past two decades. This two-part paper aims to give a comprehensive review about the application of signal processing and machine learning technologies in UHF PD detection and diagnosis. These technologies are divided into three categories according to their respective purpose, which are the preprocessing technology, source localization technology and pattern recognition technology. As the first one of the two-part review, we focus on the preprocessing and localization approaches in this paper. Specifically, for the preprocessing topic, the methods for signal denoising, multi-source separation, and pulse segmentation are included. While for the localization topic, the time difference of arrival (TDOA) method, direction of arrival (DOA) method, received signal strength indicator (RSSI) method, and other latest methods are reviewed. For each topic, the basic ideas, recent research progresses, advantages and limitations are discussed in detail. Before the conclusion, we also make a discussion about the application effects of the above technologies and prospect some future directions accordingly. In the second paper, the pattern recognition problems based on the UHF PD data will be concentrated, especially the application of deep learning algorithms.

Effect of Doping Microcapsules on Typical Electrical Performances of Self-Healing Polyethylene Insulating Composite

Abstract: Polyethylene cables, as important transmission equipment of modern power grid, would inevitably be slightly damaged, which seriously threatens the safety of the power supply. This paper has pioneered the preparation and typical performances of a self-healing polyethylene insulating composite. The self-healing performance to structural damage was verified by tests of electrical and mechanical damage. The effect mechanism of doping microcapsules on the electrical performance of polyethylene was emphatically analyzed. The results show that in appropriate conditions (such as 60 °C/30 min), the composite can not only repair the electrical tree and scratches, but also restore the insulation strength of damaged area. The effect of doping microcapsules on the electrical performances of polyethylene, such as breakdown strength, volumetric resistivity, dielectric properties, and space charge characteristics, are mainly related to impurity and the interface of microcapsule. Polarization and ionization of impurities can reduce the electrical performance of polyethylene. The interface not only improves the microstructure of polyethylene (such as how the heterogeneous nucleation effect increases the number of crystal regions, and the anchoring effect enhances the stability of amorphous regions), but also increases the charge traps. Moreover, the microstructure and charge trap can affect the characteristics of carrier transport, material polarization, and space charge accumulation, thus improving the electrical performance of polyethylene. In addition, the important electrical performance of the composite can meet the basic application requirements of polyethylene insulating material, which has good application prospects.

Effect of radical scavenger on electrical tree in cross‐linked polyethylene with large harmonic superimposed DC voltage

Abstract: In this study, three kinds of radical scavenger Chimassorb 944, Tinuvin 622, and Tinuvin 770 are used to suppress the growth of electrical trees in cross-linked polyethylene (XLPE) with transient superimposed voltage under the temperature gradient. The tree morphology, tree length, accumulated damage, and time to breakdown are used to investigate the effect of radical scavenger on the electrical treeing process. It is found that under the temperature gradient caused by the temperature rise on the high voltage side, only Tinuvin 622 can always suppress the electrical tree as the temperature gradient rises. Under the temperature gradient caused by the temperature rise on the ground side, the three radical scavengers can all suppress the electrical tree. The breakdown of electrical tree exhibits the strong DC polarity dependence. Meanwhile, energy levels of these three radical scavengers are calculated through quantum chemistry, and the results indicate that radical scavengers have greater electron affinity, smaller ionisation energy, and smaller energy gap than XLPE. According to the surface potential decay test results at 60°C, it is found that all three radical scavengers can introduce deep traps. The different performances of radical scavengers under different temperature gradients and voltages are determined by the trap distribution characteristics, the molecular structure and chemical reaction of the additives themselves. It is concluded that Tinuvin 622 has potential for use in high voltage direct current XLPE cable application.