Multi-Equipment Detection Method for Distribution Lines Based on Improved YOLOx-s

The YOLOx-s network does not sufficiently meet the accuracy demand of equipment detection in the autonomous inspection of distribution lines by Unmanned Aerial Vehicle(UAV)due to the complex background of distribution lines,variable morphology of equipment,and large differences in equipment sizes.Therefore,aiming at the difficult detection of power equipment in UAV inspection images,we propose a multi-equipment detection method for inspection of distribution lines based on the YOLOx-s.Based on the YOLOx-s network,we make the following improvements:1)The Receptive Field Block(RFB)module is added after the shallow feature layer of the backbone network to expand the receptive field of the network.2)The Coordinate Attention(CA)module is added to obtain the spatial direction information of the targets and improve the accuracy of target localization.3)After the first fusion of features in the Path Aggregation Network(PANet),the Adaptively Spatial Feature Fusion(ASFF)module is added to achieve efficient re-fusion of multi-scale deep and shallow feature maps by assigning adaptive weight parameters to features at different scales.4)The loss function Binary Cross Entropy(BCE)Loss in YOLOx-s is replaced by Focal Loss to alleviate the difficulty of network convergence caused by the imbalance between positive and negative samples of small-sized targets.The experiments take a private dataset consisting of four types of power equipment:Transformers,Isolators,Drop Fuses,and Lightning Arrestors.On average,the mean Average Precision(mAP)of the proposed method can reach 93.64%,an increase of 3.27%.The experimental results show that the proposed method can better identify multiple types of power equipment of different scales at the same time,which helps to improve the intelligence of UAV autonomous inspection in distribution lines.

A novel approach to the dynamic response analysis of Euler-Bernoulli beams resting on a Winkler soil model and subjected to impact loads

This work presents a novel approach to the dynamic response analysis of a Euler-Bernoulli beam resting on a Winkler soil model and subjected to an impact loading.The approach considers that damping has much less importance in controlling the maximum response to impulsive loadings because the maximum response is reached in a very short time,before the damping forces can dissipate a significant portion of the energy input into the system.The development of two sine series solutions,relating to different types of impulsive loadings,one involving a single concentrated force and the other a distributed line load,are presented.This study revealed that when a simply supported Euler-Bernoulli beam,resting on a Winkler soil model,is subject to an impact load,the resulting vertical displacements,bending moments and shear forces produced along the span of the beam are considerably affected.In particular,the quantification of this effect is best observed,relative to the corresponding static solution,via an amplification factor.The computed impact amplification factors,for the sub-grade moduli used in this study,were in magnitude greater than 2,thus confirming the multiple-degree-of-freedom nature of the problem.

考虑工时不确定性的混流U型装配线平衡的分布鲁棒优化方法

在以人工装配为主的流水线生产中,工时的不确定性是影响生产节拍的重要因素。考虑到随机优化要求精确的概率分布信息和较高的鲁棒优化保守性,本文针对工时不确定条件下混流U型装配线平衡问题,采用以经验分布为中心、Wasserstein距离为半径的模糊集对工时的不确定性进行描述,并以最小化生产节拍为优化目标,建立装配线平衡问题的分布鲁棒优化模型。为了降低模型的复杂性,利用强对偶理论将模型转换为易于求解的形式;为保证解的鲁棒性,设计了一种鲁棒性指标并将其作为模型的约束条件。针对上述模型,通过设计一种基于区间数的解码方式,并引入自适应交叉和变异概率,给出了一种改进的遗传算法。最后通过标准算例和断路器抽架生产实例进行了数值仿真实验,结果表明相较于随机优化和鲁棒优化方法,所建立模型在降低结果保守性的同时保持较高的鲁棒性,并且针对问题所提出的改进遗传算法具有良好的寻优能力。

Stability Analysis of Multi-paralleled Grid-connected Inverters Including Distribution Parameter Characteristics of Transmission Lines

The sparse distribution characteristics of renewable energy resources can lead to there being tens of kilometers of transmission lines between a grid-connected inverter and the actual grid.Accurate analysis of the stability of such gridconnected inverter systems currently involves using a complex hyperbolic function to shaped model of the transmission line circuit.This has proved to be problematic,so,drawing upon the distribution parameter characteristics of transmission lines,this paper looks at how to use impedance-based stability criteria to assess the stability of multi-paralleled grid-connected inverters.First,the topology of multi-paralleled inverters connected to the grid via transmission lines is established,using each transmission line terminal as a grid connection point.Each grid-connected system is taken to be equivalent to a small-signal circuit model of the“current source-grid”.Euler’s formula and the Nyquist stability criterion are combined to assess the stability of the associated grid-connected current transfer functions and evaluate the stability of the grid-connected current.Finally,a simulation analysis circuit is constructed to verify whether power line intervention will cause stability problems in the grid-connected system.Overall,it is found that long-distance transmission lines are more likely to cause unstable output of the grid-connected current.It is also found that the number of grid-connected inverters,the short-circuit ratio(SCR),the distorted grid and the inverter parameters can all have a significant impact on the stability of the grid-connected current.

Impedance-based Stability Criterion for the Stable Evaluation of Grid-connected Inverter Systems with Distributed Parameter Lines

For a multi-inverter grid-connected system,the stability of the point of common coupling(PCC)voltage is evaluated considering the distribution parameters of the transmission lines.First,the systems on both sides of the PCC are equalized,a smallsignal equivalent circuit similar to the“current source-grid”is established,and a mathematical model for the voltage of the PCC is derived.Then,using Euler’s formula and Nyquist stability criterion,the PCC voltage stability of the grid-connected system is evaluated by the impedance analysis method under the premise that the single-side excitation is stable.In addition,the gridconnected conditions causing PCC voltage instability are studied.A phase compensation method based on an impedance phase compensation control strategy is introduced.The stability of the grid-connected system is improved by compensating the phase margin at the equivalent impedance crossover-section frequency on both sides of the grid-connected system PCC.Finally,a simulation circuit is built to simulate and analyze the proposed model and phase compensation method.The simulation results verify the accuracy and effectiveness of the theoretical analysis.

计及气网管存效应的综合能源系统分布鲁棒优化调度

可再生能源接入的综合能源系统具有不确定性特征,然而随机规划与鲁棒优化等求解方法存在鲁棒性不足或过于保守等问题。气网管存是综合能源系统中重要的灵活性资源,可以有效平抑不确定性的影响。鉴于此,提出计及气网管存效应的综合能源系统分布鲁棒优化调度方法,通过充分利用系统中的灵活性资源,促进可再生能源消纳,实现系统安全稳定运行。在分析天然气管道中气体流动特性和管存效应的基础上,以系统综合成本最低为目标,建立计及气网管存效应的综合能源系统优化调度模型。针对风电出力和电负荷不确定性特征的差异性,分别采用概率分布集和梯形模糊函数对风电出力和电负荷不确定性进行刻画。在此基础上,建立综合能源系统分布鲁棒优化调度模型,并采用列约束生成算法进行求解。最后,通过算例分析验证了所提方法的准确性与有效性,并且结果表明所提方法在应对不确定场景时具有较强的调节能力和良好的经济性。

Fault Location in Distribution System Using Convolutional Neural Network Based on Domain Transformation

Distribution lines are integral parts of the modern power system,which can affect the security and stability of power supply directly.An effective power system protection scheme should be able to detect all occurring faults as soon as possible.There are two tasks in fault diagnosis.One is the fault classification,where high accuracy rates have already achieved.Thus,this paper focuses on the other task,i.e.fault location.Enlightened by Fourier transform,this paper proposes an online data-driven method,which transforms signals from time domain to image domain through signal-to-image(SIG)algorithm and then process the transformed images with framework based on convolutional neural network(CNN).On the one hand,we can extract more crucial characteristic and information from image domain.On the other hand,the CNN-based structure is much smaller than others.It needs less memory space and would be easier to be transplanted to hardware platform.Moreover,the proposed algorithm does not require synchronous devices.The numerical comparison shows that the proposed SIG-CNN fault location model achieves robust and accurate results compared with other data-driven algorithms.

Robust N−k Security-constrained Optimal Power Flow Incorporating Preventive and Corrective Generation Dispatch to Improve Power System Reliability

As extreme weather events have become more frequent in recent years,improving the resilience and reliability of power systems has become an important area of concern.In this paper,a robust preventive-corrective security-constrained optimal power flow(RO-PCSCOPF)model is proposed to improve power system reliability under N−k outages.Both the short-term emergency limit(STL)and the long-term operating limit(LTL)of the post-contingency power flow on the branch are considered.Compared with the existing robust corrective SCOPF model that only considers STL or LTL,the proposed ROPCSCOPF model can achieve a more reliable generation dispatch solution.In addition,this paper also summarizes and compares the solution methods for solving the N−k SCOPF problem.The computational efficiency of the classical Benders decomposition(BD)method,robust optimization(RO)method,and line outage distribution factor(LODF)method are investigated on the IEEE 24-bus Reliability Test System and 118-bus system.Simulation results show that the BD method has the worst computation performance.The RO method and the LODF method have comparable performance.However,the LODF method can only be used for the preventive SCOPF and not for the corrective SCOPF.The RO method can be used for both.

Single-ended Time Domain Fault Location Based on Transient Signal Measurements of Transmission Lines

Precise fault location plays an important role in the reliability of modern power systems.With the in-creasing penetration of renewable energy sources,the power system experiences a decrease in system inertia and alterations in steady-state characteristics following a fault occurrence.Most existing single-ended phasor domain methods assume a certain impedance of the remote-end system or consistent current phases at both ends.These problems present challenges to the applicability of con-ventional phasor-domain location methods.This paper presents a novel single-ended time domain fault location method for single-phase-to-ground faults,one which fully considers the distributed parameters of the line model.The fitting of transient signals in the time domain is real-ized to extract the instantaneous amplitude and phase.Then,to eliminate the error caused by assumptions of lumped series resistance in the Bergeron model,an im-proved numerical derivation is presented for the distrib-uted parameter line model.The instantaneous symmet-rical components are extracted for decoupling and inverse transformation of three-phase recording data.Based on the above,the equation of instantaneous phase constraint is established to effectively identify the fault location.The proposed location method reduces the negative effects of fault resistance and the uncertainty of remote end pa-rameters when relying on one-terminal data for localiza-tion.Additionally,the proposed fault analysis methods have the ability to adapt to transient processes in power systems.Through comparisons with existing methods in three different systems,the fault position is correctly identified within an error of 1%.Also,the results are not affected by sampling rates,data windows,fault inception angles,and load conditions. Index Terms—Fault location,distributed parameter line model,transient signal,renewable energy,instantaneous phase.