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.

Wide-Area Delay-Dependent Adaptive Supervisory Control of Multi-machine Power System Based on Improve Free Weighting Matrix Approach

The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission delays. The paper uses an LMI-based iterative nonlinear optimization algorithm to establish a method of designing state-feedback controllers for power systems with a time-varying delay. This method is based on the delay-dependent stabilization conditions obtained by the improved free weighting matrix (IFWM) approach. In the stabilization conditions, the upper bound of feedback signal’s transmission delays is taken into consideration. Combining theoriesof state feedback control and state observer, the ASC is designed and time-delay output feedback robust controller is realized for power system. The ASC uses the input information from Phase Measurement Units (PMUs) in the system and dispatches supplementary control signals to the available local controllers. The design of the ASC is explained in detail and its performance validated by time domain simulations on a New England test power system (NETPS).

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.

一种电力电缆的随机电热退化模型（英文）

In this paper a methodology is proposed to model the stochastic electro-thermal degradation accumulation in cables.The cable life and the reliability are predicted by estimating the accumulated electro-thermal degradation during seasonal load cycles.The degradation is considered,in a novel approach,as stochastic in nature due to variations in the manufacturing process of insulation raw material and in operational and environmental conditions.The methodology is based on estimation of life by using combined electro-thermal life model,simulation of degradation accumulation process under electro-thermal stress in each season of the year based on Miner’s cumulative damage theory and reliability prediction from a probabilistic point of view.A case study is demonstrated on 10 k V XLPE cables which are directly buried in the UK and China.Results show that,the electro-thermal life of the cable is 56 and 69 years in China and the UK,respectively at 50%failure probability,or the life of the cable in the UK would be 13 years longer than in China,when other stresses such as mechanical and environmental are also considered and assumed to be the same.

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.

Transceiver Optimization for Multi-Antenna Device-to-Device Communications

It has been shown that the deployment of device-to-device(D2D) communication in cellular systems can provide better support for local services. However, improper design of the hybrid system may cause severe interference between cellular and D2D links. In this paper, we consider transceiver design for the system employing multiple antennas to mitigate the interference. The precoder and decoder matrices are optimized in terms of sum mean squared error(MSE) and capacity, respectively. For the MSE minimization problem, we present an alternative transceiver optimization algorithm. While for the non-convex capacity maximization problem, we decompose the primal problem into a sequence of standard convex quadratic programs for efficient optimization. The evaluation of our proposed algorithms for performance enhancement of the entire D2D integrated cellular system is carried out through simulations.

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 multi-input and multi-output design on automotive engine management system

Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotive engine management system(EMS).Usually,an ECU has a structure of multi-input and single-output(MISO).Therefore,if there are multiple objectives proposed in EMS,there would be corresponding numbers of ECUs that need to be designed.In this situation,huge efforts and time were spent on calibration.In this work,a multi-input and multi-out(MIMO) approach based on model predictive control(MPC) was presented for the automatic cruise system of automotive engine.The results show that the tracking of engine speed command and the regulation of air/fuel ratio(AFR) can be achieved simultaneously under the new scheme.The mean absolute error(MAE) for engine speed control is 0.037,and the MAE for air fuel ratio is 0.069.

Optimal proportion of wind and PV capacity in provincial power systems based on bilevel optimization algorithm under low-carbon economy

In order to boost contributions of power systems to a low-carbon economy,the installed capacity of renewable power generation,such as wind and photovoltaic(PV)power generation should be well planned.A bilevel formulation is presented to optimize the proportion of wind and PV capacity in provincial power systems,in which,carbon emissions of generator units and features of renewable resources are taken into account.In the lowerlevel formulation,a time-sequence production simulation(TSPS)model that is suitable for actual power system has been adopted.In order to maximize benefits of energy conservation and emissions reduction resulting from renewable power generation,the commercial software called General Algebraic Modeling System(GAMS)is employed to optimize the annual operation of the power system.In the upper-level formulation,the optimal pattern search(OPS)algorithm is utilized to optimize the proportion of wind and PV capacity.The objective of the upper-level formulation is to maximize benefits of energy conservation and carbon emissions reductions optimized in the lowerlevel problem.Simulation results in practical provincial power systems validate the proposed model and corresponding solving algorithms.The optimization results can provide support to policy makers to make the polices related to renewable energy.

Multi-Objective Optimization of EV Charging and Discharging for Different Stakeholders

As a dynamic energy storage system,electric vehicles(EV)play important roles in future power grids.In this paper,a model for EV aggregator participation in the electricity market has been built with a focus on the feasibility issue of the model arising from economic interest inconsistencies between different stakeholders:EV owners and aggregator.In the model,the EV aggregator attends day-ahead energy and reserve markets for profit maximization by scheduling charging and discharging behaviors of EVs.This issue exists since different stakeholders have different interests which are not necessarily consistent,e.g.profit maximization leads to increasing EV owners'charging fee.To investigate the economic relationship between the two stakeholders,two multi-objective optimization methods(weighted sum and$\varepsilon$-constraint methods)are proposed to take the aggregator profit and EV owners'charging fee into account in the model.A sensitivity analysis is applied to examine the aggregator profit under different price scenarios,which reveals the internal relationship between EV owners'charging fees and aggregator profit.The proposed EV charging and discharging strategy in this paper could be used to determine the settlement price between the aggregator and owners to ensure the feasibility of participation from both EV owners and stakeholders in electricity markets.

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.