Abstract:In November 2017, the first ±1100 kV high-voltage direct-current power transformer in the world, which was made by Siemens in Nurnberg, passed its type test. Meanwhile, in early 2017, a ±1000 kV ultra-high voltage (UHV) substation was officially put into operation in Tianjin, China. These examples illustrate that the era of UHV power transmission is coming. With the rapid increase in power transmission voltage, the performance requirements for the insulation of power transformers are getting higher and higher. The traditional mineral oils used inside power transformers as insulating and cooling agents are thus facing a serious challenge to meet these requirements. In this review, the basic properties of traditional mineral insulating oil are first introduced. Then, the variation of electrical properties such as breakdown strength, permittivity, and conductivity during transformer operation and aging is summarized. Next, the modification of mineral insulating oil is investigated with a focus on the influence of nanoparticles on the electrical properties of nano-modified insulating oil. Recent studies on the performance of mineral oil at molecular and atomic levels by molecular dynamics simulations are then described. Finally, future research hotspots and notable research topics are discussed.

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This paper focuses on the space charge behavior in oil-paper insulation systems used in power transformers. It begins with the importance of understanding the space charge behavior in oil-paper insulation systems, followed by the introduction of the pulsed electrostatic technique (PEA). After that, the research progress on the space charge behavior of oil-paper insulation during the recent twenty years is critically reviewed. Some important aspects such as the environmental conditions and the acoustic wave recovery need to be addressed to acquire more accurate space charge measurement results. Some breakthroughs on the space charge behavior of oil-paper insulation materials by the research team at the University of Southampton are presented. Finally, future work on space charge measurement of oil-paper insulation materials is proposed.

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In this study, molecular dynamics simulations were used to investigate the micro-scale effects of modification of nano-SiO 2 with commonly used silane coupling agents (KH550, KH560, KH570, and KH792) on the cellulose/nano-SiO 2 interface. The relative optimum silane coupling agent and grafting density for nano-SiO 2 modification to improve the cellulose/nano-SiO 2 interface were determined. The results showed that at the same grafting density, modification of nano-SiO 2 with KH792 yielded the highest interfacial binding energy and binding energy density, the largest number of hydrogen bonds at the cellulose/nano-SiO 2 interface, the strongest binding to the cellulose chains, and the largest overlapping area at the cellulose/nano-SiO 2 interface. We found that the non-bonding interaction energy played a decisive role in the energy of the model system and the interfacial interaction force mainly consisted of van der Waals forces and the hydrogen-bonding energy. When silane coupling agents with amino groups (KH550 and KH792) were used to modify nano-SiO 2 , the number of hydrogen bonds at the cellulose/nano-SiO 2 interface was larger than that for unmodified nano-SiO 2 . When silane coupling agents without amino groups (KH560 and KH570) were used to modify nano-SiO 2 , the number of hydrogen bonds at the cellulose/nano-SiO 2 interface was lower than the case for unmodified nano-SiO 2 . Nano-SiO 2 modification with various amounts of KH792 was investigated. The results showed that the interfacial bonding energy increased with grafting density. When the grafting density was 1.57 nm −2 , the interfacial bonding energy and number of hydrogen bonds formed at the cellulose/nano-SiO 2 interface was relatively stable, which indicates that the interface had reached a relatively stable state. Modification of nano-SiO 2 with KH792 achieved the greatest improvement of the cellulose/nano-SiO 2 interface; this interface reached a relatively stable state when the grafting density of KH792 was 1.57 nm −2 .

The water content in oil is closely related to the deterioration performance of an insulation system, and accurate prediction of water content in oil is important for the stability and security level of power systems. A novel method of measuring water content in transformer oil using multi frequency ultrasonic with a back propagation neural network that was optimized by principal component analysis and genetic algorithm (PCA-GA-BPNN), is reported in this paper. 160 oil samples of different water content were investigated using the multi frequency ultrasonic detection technology. Then the multi frequency ultrasonic data were preprocessed using principal component analysis (PCA), which was implemented to obtain main principal components containing 95% of original information. After that, a genetic algorithm (GA) was incorporated to optimize the parameters for a back propagation neural network (BPNN), including the weight and threshold. Finally, the BPNN model with the optimized parameters was trained with a random 150 sets of pretreatment data, and the generalization ability of the model was tested with the remaining 10 sets. The mean squared error of the test sets was 8.65 × 10−5, with a correlation coefficient of 0.98. Results show that the developed PCA-GA-BPNN model is robust and enables accurate prediction of a water content in transformer oil using multi frequency ultrasonic technology.