The characteristics of negative corona discharge and radio interference at different altitudes based on coaxial wire-cylinder gap

The corona discharge from transmission lines in high-altitude areas is more severe than at lower altitudes. The radio interference caused thereby is a key factor to be considered when designing transmission lines. To study the influence of altitude on negative corona characteristics, an experimental platform comprising a movable small corona cage was established: experiments were conducted at four altitudes in the range of 1120-4320 m, and data on the corona current pulse and radio interference level of 0.8-mm diameter fine copper wire under different negative voltages were collected. The experimental results show that the average amplitude, repetition frequency and average current of the corona current pulse increase with increasing altitude. The dispersion of pulse amplitude increases with increase in altitude, while the randomness of the pulse interval decreases continuously. Taking the average current as an intermediate variable,the relationship between radio interference level and altitude is obtained. The result of this research has some significance for understanding the corona discharge characteristics of ultra-highvoltage lines.

RankXGB-Based Enterprise Credit Scoring by Electricity Consumption in Edge Computing Environment

With the rapid development of the internet of things(IoT),electricity consumption data can be captured and recorded in the IoT cloud center.This provides a credible data source for enterprise credit scoring,which is one of the most vital elements during the financial decision-making process.Accordingly,this paper proposes to use deep learning to train an enterprise credit scoring model by inputting the electricity consumption data.Instead of predicting the credit rating,our method can generate an absolute credit score by a novel deep ranking model–ranking extreme gradient boosting net(rankXGB).To boost the performance,the rankXGB model combines several weak ranking models into a strong model.Due to the high computational cost and the vast amounts of data,we design an edge computing framework to reduce the latency of enterprise credit evaluation.Specially,we design a two-stage deep learning task architecture,including a cloud-based weak credit ranking and an edge-based credit score calculation.In the first stage,we send the electricity consumption data of the evaluated enterprise to the computing cloud server,where multiple weak-ranking networks are executed in parallel to produce multiple weak-ranking results.In the second stage,the edge device fuses multiple ranking results generated in the cloud server to produce a more reliable ranking result,which is used to calculate an absolute credit score by score normalization.The experiments demonstrate that our method can achieve accurate enterprise credit evaluation quickly.

Humidity effects on the ground-level resultant electric field of positive DC conductors

The effects of humidity on the ground-level resultant electric field around positive DC conductors were studied both experimentally and numerically. Experiments were carried out in an artificial climate chamber, the results of which showed that the photon count and the groundlevel resultant electric field strength both increased with increasing relative humidity. Numerical calculations for different values of relative humidity were carried out, including solutions of the positive corona inception voltage and the ion-flow field, for which a photoionization model and the upstream finite element method were employed, respectively. In order to analyze the effects of humidity, three main factors were considered: the ionization coefficient, the attachment coefficient in the photoionization model and the modified ion mobility of the charged water particles. The results indicated that, with increasing relative humidity, increasing values of the effective ionization coefficient were responsible for a reduction in the inception voltage, and the reduction reinforced the ground-level resultant electric field. Moreover, due to the charged water particles and the lower ion mobility with increasing relative humidity, the space charge density distribution was enhanced, which also strengthened the ground-level resultant electric field.

A diagnostic method for distribution networks based on power supply safety standards

In order to overcome the shortages of diagnostic method for distribution networks considering the reliability assessment,this paper proposed a method based on power supply safety standards.It profoundly analyzed the security standard of supply for urban power networks,and established quantitative indicators of load groups based on different fault conditions.Then a method suitable for diagnostic evaluation of urban distribution networks in China was given.In the method,“N-1”calibration analysis of the distribution network was conducted.Then the results are compared with quantitative indicators of load groups on different conditions deriving the diagnostic conclusions and the standard revision is discussed.The feasibility and accuracy of the method is finally verified in the case study.

A Cloud-edge Cooperative Dispatching Method for Distribution Networks Considering Photovoltaic Generation Uncertainty

With the increasing penetration of renewable energy generation,uncertainty and randomness pose great challenges for optimal dispatching in distribution networks.We propose a cloud-edge cooperative dispatching(CECD)method to exploit the new opportunities offered by Internet of Things(IoT)technology.To alleviate the huge pressure on the modeling and computing of large-scale distribution system,the method deploys edge nodes in small-scale transformer areas in which robust optimization subproblem models are introduced to address the photovoltaic(PV)uncertainty.Considering the limited communication and computing capabilities of the edge nodes,the cloud center in the distribution automation system(DAS)establishes a utility grid master problem model that enforces the consistency between the solution at each edge node with the utility grid based on the alternating direction method of multipliers(ADMM).Furthermore,the voltage constraint derived from the linear power flow equations is adopted for enhancing the operation security of the distribution network.We perform a cloud-edge system simulation of the proposed CECD method and demonstrate a dispatching application.The case study is carried out on a modified 33-node system to verify the remarkable performance of the proposed model and method.

Experiments and Analysis of Corona Inception Voltage Under Combined AC-DC Voltages at Various Air Pressure and Humidity in Rod to Plane Electrodes

As the effect of climate plays a significant role in corona discharge under combined voltages,the variation of corona inception voltage with different air pressure and humidities is studied.An experimental platform,based on a rod-to-plane electrode,is constructed with adjustable air pressure from 0.06 MPa to 0.10 MPa and with a relative humidity(RH)from 20%to 90%.The variation of ultraviolet(UV)photon count and corona inception voltage is obtained at various climate conditions under different applied voltages:the single AC,single DC,and combined AC-DC.It turns out that all the corona inception voltages decline with the drop of air pressure and the rise of humidity under different applied voltages.The influence between different voltages primarily relies on space charge,as more AC components make it easier to accumulate positive ions.The existence of AC makes ions move forward and backward while the existence of DC dominates the polarity of corona and general drift directions.At last the fitting formula of hybrid corona inception voltage combining air pressure and relative humidity is given.