Zhenghai Liao

DC total electric field measurement under ultra-high voltage direct current (UHVDC) lines suffers from inherent challenges of electric field distortion caused by sensor grounding and interference from corona ions. To address these issues, this paper develops a ground-free differential-rotation dual-probe field mill. The sensor consists of two split-cylinder probes with identical structure coaxially mounted on a common motor shaft but operating at different rotational speeds, together with peripheral signal processing circuits. Each probe comprises multiple fan-shaped cylindrical metal mantles with uniform dimensions, a motor, a photodetector, and a slip ring. Four key innovations are incorporated: (1) corona discharge tips integrated on the mantle surface realize potential clamping through charge leakage; (2) multi-fan-shaped cylindrical metal mantles enhance electric field measurement sensitivity and resolution; (3) dual probes with differential signal processing suppress corona ion interference; (4) a dedicated hardware circuit performs weak signal conditioning, polarity discrimination, and signal output. The field mill was comprehensively validated using laboratory calibration test systems, reduced-scale conductor models, and field tests on the ±800 kV Zhalute-Guanggu UHVDC line. Laboratory results demonstrate excellent linear response in ion-containing electric fields, with relative deviations from simulated values within ±2.15% under corona conditions, matching the accuracy of conventional shutter-type field mills. Field measurements show consistent trends with traditional devices in both perpendicular and parallel cross-sections of the transmission line, confirming stable operation in engineering environments. These results verify that the proposed field mill effectively mitigates grounding-induced distortion and corona ion interference, meeting the requirements of engineering applications. The main limitation is slightly inferior measurement repeatability compared to shutter-type field mills, and future work will focus on optimizing probe rotation stability and signal processing algorithms to improve measurement consistency, thereby facilitating broader application in electromagnetic environment evaluation of UHVDC transmission projects.

Audible noise (AN) is a critical parameter in the economic and environmental design of extra-high voltage (EHV) AC transmission lines, especially in high-altitude regions. Although several altitude correction factors and AN prediction methods have been proposed based on corona cage tests and long-term observations, the accuracy remains uncertain owing to the limited measurement data from high-altitude transmission lines. This study addresses this gap through long-term observations of four EHV transmission lines on the Tibetan Plateau, combined with existing corona cage test results. The cumulative distribution of AN in rainy weather was obtained from various observation stations. By comparing measured values from stations at different altitudes and combining the experimental results from a movable corona cage, an altitude correction method for AN was developed. Subsequently, by comparing statistical data from four high-altitude observation stations with predicted results from different approaches, the predicted values were found to be overestimated. An improved prediction method for AN in rainy weather was proposed. Additionally, based on the statistical differences observed over one year at multiple long-term observation stations, a method for evaluating AN under varying weather conditions was investigated. A predictive model for AN under different rainfall conditions was developed based on correlation and multiple regression analyses, and its accuracy was validated. The findings of this study provide a crucial reference for the prediction and evaluation of AN from EHV AC transmission lines in high-altitude regions.

With the advancement of China’s ultra-high voltage (UHV) projects, the proximity of transmission lines to buildings has intensified grid-environment conflicts, increasing the risk of electric shock from induced electric fields on areas like balconies and building platforms. This study addresses the mitigation of DC total electric field (TEF) on flat-roofed building platforms near UHV direct current (UHVDC) lines by proposing a shielding method using a grounded metal mesh (GMM). A 3D finite-element model integrating buildings, GMMs, and UHVDC lines was developed to analyze the shielding effect on the TEF, which combines electrostatic and space charge excitation fields. The influence of GMM parameters and installation methods was investigated. The method was validated in the 1951 to 1952 section of the ± 800 kV Lingzhou-Shaoxing UHVDC project. Results show that installation parallel to the platform provides superior shielding compared to perpendicular installation, controlling TEF E₈₀ values at 3.95 kV/m and 7.70 kV/m with shielding efficiencies of 16.59 dB and 10.13 dB, respectively, both of which were much lower than the limit of 15 kV/m stipulated in GB 39220-2020 and 20 kV/m stipulated in IEEE Std C95.1-2019. This research offers practical guidance for building protection along DC lines, enabling controllable electric field environments, mitigating grid-residence conflicts, and promoting harmonious coexistence between power facilities and buildings.

Radio interference (RI) is a key environmental indicator of extra-high-voltage (EHV) AC transmission lines. In high-altitude regions, the harsh climate and thin air result in a more intense corona discharge of the conductors, making the effects of meteorological parameters on RI even more complex. In this study, we perform statistical analysis of RI data collected over 1–2 years from three EHV transmission line observation stations located at an altitude of 1854, 3320, and 3950 m to investigate the effects of meteorological parameters on the RI level of EHV AC transmission lines at high altitudes. The correlation coefficients between RI and meteorological parameters under different weather conditions were calculated, followed by an analysis of the effects of rainfall rate, relative humidity, temperature, dew point, and other meteorological factors on the RI level. The statistical values of RI under different seasons and weather conditions were then compared. The findings are of significant importance for the measurement, prediction, and control of RI in high-altitude AC transmission lines.

In recent years, the State Grid of China has placed significant emphasis on the monitoring of noise in substations, driven by growing environmental concerns. This paper presents a substation noise monitoring system designed based on an end-network-cloud architecture, aiming to acquire and analyze substation noise, and report anomalous noise levels that exceed national standards for substation operation and maintenance. To collect real-time noise data at substations, a self-developed noise acquisition device is developed, enabling precise analysis of acoustic characteristics. Moreover, to subtract the interfering environmental background noise (bird/insect chirping, human voice, etc.) and determine if noise exceedances are originating from substation equipment, an intelligent noise separation algorithm is proposed by leveraging the convolutional time-domain audio separation network (Conv-TasNet), dual-path recurrent neural network (DPRNN), and dual-path transformer network (DPTNet), respectively, and evaluated under various scenarios. Experimental results show that (1) deep-learning-based separation algorithms outperform the traditional spectral subtraction method, where the signal-to-distortion ratio improvement (SDRi) and the scale-invariant signal-to-noise ratio improvement (SI-SNRi) of Conv-TasNet, DPRNN, DPTNet and the traditional spectral subtraction are 12.6 and 11.8, 13.6 and 12.4, 14.2 and 12.9, and 4.6 and 4.1, respectively; (2) DPTNet and DPRNN exhibit superior performance in environment noise separation and substation equipment noise separation, respectively; and (3) 91% of post-separation data maintains sound pressure level deviations within 1 dB, showcasing the effectiveness of the proposed algorithm in separating interfering noises while preserving the accuracy of substation noise sound pressure levels.

The switching operation of gas insulated switchgear (GIS) disconnector will produce multiple random spark discharges between the gas gaps of the disconnector. Each spark discharge can be affected by various random factors, such as trapped charge on the load side, the initial operating phase, gap distance and operating speed of the disconnector, leading to dispersion characteristics. At present, some studies have mentioned this dispersion, but its impact is still unclear due to the lack of experimental data, resulting in a deviation between the simulation results and the measured results. In this study, thousands of switching operations were carried out based on the 1100 kV full‐scale GIS circuit in Wuhan ultra‐high voltage alternating current Test Base. The maximal information coefficient analysis, linear regression fitting and other statistical methods were used to discuss the dispersion characteristics of very fast transient overvoltage (VFTO) and transient enclosure voltage (TEV) from large‐scale experimental data. The results show that the dispersion of VFTO and TEV in amplitude aspects both increase gradually as the breakdown voltage increases, with the maximum difference of five times of TEV amplitude at normalised breakdown voltage. In terms of frequency characteristics, the dispersion of different frequency components in TEV is always greater than that of VFTO, especially for the high‐frequency components. Moreover, by comparing the frequency characteristics of TEV at different positions, we notice that the dispersion is almost independent of the spatial position but only determined by the randomness of spark discharges. These discoveries reveal the importance of the dispersion in switching transients and make up for the lack of theoretical understanding of the correlation among them.

Gas–oil separation by membrane stands for a promising technique in dissolved gas analysis (DGA). Since the accuracy of DGA relies on the results of gas–oil separation to a great extent, it is necessary to study the influence factor of membrane for better performance. Although plentiful studies have been conducted aiming at membrane modification to obtain better separation performance, it cannot be ignored that the conditions of oil also affect the performance of membrane much. In this work, a photoacoustic spectroscopy-based sensor for DGA, which employed membrane for gas–oil separation, was established first. By detecting the photoacoustic signal, the performance of membrane could be evaluated. Furthermore, the influences of feed velocity and pressure have on the performance of membrane were analyzed. Both simulation and experiment were employed in this work to evaluate the influences by collecting the equilibrium time of membrane under different conditions. As a result, the simulation and experiment agreed with each other well. Moreover, it was reasonable to draw the conclusion that the equilibrium time was evidently reduced with the raise of feed velocity but remained with a minimum change when pressure changed. The conclusion may serve as a reference for the application of membrane in optical sensor and DGA.

Accurate quantitative detection for trace gas has long been the center of failure diagnosis for gas-insulated equipment. An absorption spectroscopy-based detection system was developed for trace SF₆ decomposition SO₂ detection in this paper. In order to reduce interference from other decomposition, ultraviolet spectrum of SO₂ was selected for detection. Firstly, an excimer lamp was developed in this paper as the excitation of the absorption spectroscopy compared with regular light sources with electrodes, such as electrodeless lamps that are more suitable for long-term monitoring. Then, based on the developed excimer lamp, a detection system for trace SO₂ was established. Next, a proper absorption peak was selected by calculating spectral derivative for further analysis. Experimental results indicated that good linearity existed between the absorbance and concentration of SO₂ at the chosen absorption peak. Moreover, the detection limit of the proposed detection system could reach the level of 10⁻⁷. The results of this paper could serve as a guide for the application of excimer lamp in online monitoring for SF₆-insulated equipment.