基于主动探测技术的输电线路驱鸟策略研究

为解决鸟害引起的输配电线路故障,通过总结鸟害故障机理,分析鸟害事故较严重的华北地区鸟害的时间规律,提出了基于光电探测技术、激光立体扫描和能源优化设计的驱鸟策略。研究表明,鸟害故障一般发生在春秋两季,且06:00～08:00时间段故障率较高;光电探测技术可探测与探测平面成60°范围内的飞鸟;激光器可实现上下左右10°范围内立体式驱鸟,覆盖范围广;驱鸟策略采用定扫模式和巡航模式,系统综合功耗优化至38AH,鸟害故障率降低了60%。研究结果为输配电线路鸟害故障治理提供了参考。     

架空输电线路鸟害防治措施研究现状及展望

鸟害是威胁架空输电线路安全稳定运行的重要因素之一。全面分析和评价应用于国内外输电线路的鸟害故障防治措施,提出了应重视鸟害防治工作、借鉴其他学科研究成果、建立引鸟、驱鸟、防鸟三位一体的鸟害防治体系,绘制鸟害等级区划图等建议,以期为提高电网的安全可靠性、防治鸟害故障提供参考。     

架空电力线路鸟害分析与预防

针对鸟类的频繁活动极易造成电力架空线路故障甚至事故,从鸟害的形成机理上进行分析和归类,并提出了相应的防治措施。     

输电线路鸟粪故障分析与工程治理

为有效降低鸟粪故障跳闸发生的频次,通过分析研究其共性特点,找出鸟类体积尺寸和地理环境系数关键技术指标并进行了量化,建立了统一鸟害系数与防鸟害措施的一一对应关系,给出了体系建设过程中鸟类体积尺寸确定、防鸟技术分类、现场调查、防鸟害评估等具体方法和范例,由此建立了鸟害区段图绘制的理论基础,提出了混合型防鸟害技术思路和干字型塔中相吊串防鸟害新技术。实例应用表明,该治理技术效果明显。     

110 kV线路接地故障与终端站保护配合案例分析

针对110 kV中性点直接接地系统中,主网终端且带地区电源的变电站在始端送电线路发生单相接地故障时,线路接地保护与终端变电站内相关保护的配合、整定问题,以华北电网发生的一起110 kV线路单相接地故障为例,阐述了线路接地保护及终端带地区电源变电站主变压器零序电压保护的动作过程,分析了导致零序电压保护动作与变电站全站停电的原因、110 kV主变零序电压保护的配置和110 kV线路接地保护、地区电源联络线保护、重合闸与备用电源自投装置等配合问题,并对保护配置和整定提出了改进建议。     

一起多点接地导致自闭/贯通线路故障跳闸案例分析

自闭贯通线路多是采用电缆架空混架的形式,线路中存在大量电缆和架空箱变,一旦线路线路发生故障跳闸,多是采用翻牌式故障指示器进行故障区间的确认,无法实现线路的精确定位。同时,基于现阶段自闭贯通线路的结构,在进行故障处理式,需要通过大量的人力进行巡线,对于自闭/贯通线路的故障处理极不友善。本文基于行波法故障测距理论,分析了现阶段自闭/贯通线路故障测距所面临的难题,同时对已安装了行波法故障监测装置的线路进行故障定位,成功定位了一起多点故障导致的自闭/贯通线路故障,从而排除了自闭/贯通线路故障。相比传统翻牌式故障指示器,行波故障监测装置大大提升了故障处理效率,从而大大提升了自闭/贯通线路自动化运维水平。     

基于正序阻抗的微电网线路故障定位策略的研究

微电网线路结构的复杂性,造成了对线路的故障判断和定位困难。文章提出了一种基于等效正序阻抗的线路故障定位方法。通过对线路两端的电压、电流、有功功率以及无功功率进行3次测量,计算出每条线路两端的等效正序阻抗。通过对故障前后线路等效正序阻抗的对比分析,对出现故障的线路做出判断。在确定故障线路的前提下,比较短路点到线路端点的阻抗与故障前线路阻抗的大小,确定出线路短路点的具体位置。实验数据以及仿真波形与理论分析完全吻合,验证了所提出的故障定位方法是完全正确和有效的。     

基于多视图稀疏特征选择的架空输电线路故障原因判别

日渐增加的多源异构数据为输电线路故障原因判别带来了信息融合的机遇和挑战。为解决故障录波和多源关联信息的特征融合问题,引入多视图学习概念,提出了基于多视图稀疏特征选择的架空输电线路故障原因判别方法。根据故障录波和关联信息区分并提取双视图故障特征,随后基于稀疏表示提出了层次多视图特征选择算法（HMVFS）。该算法引入ε-dragging扩大分类类别的标签间距,并通过Frobenius范数和l2,1范数的正则化项分别从故障视图和故障特征的高低维度实现特征选择。最后采用某地区输电线路故障数据进行对比实验,结果验证了该方法在输电线路故障原因判别的有效性和优越性。     

基于多代理系统的含DG辐射状配电网故障定位

分布式电源（DG）的高渗透接入使配电网结构发生了改变,导致传统的配电网故障定位算法失效。基于含多DG辐射状配电网拓扑结构的特点,构建多代理系统的配电网故障定位框架,该系统主代理根据子代理上传的电源端故障量测量建立RBF神经网络故障测距模型,估计各电源端到故障点的故障距离,考虑上传量测量误差对相邻线路分界点故障定位的影响,应用相邻线路故障信息修正故障线路定位信息;子代理根据主代理下传的故障线路定位结果,利用并行线路首端过流信息校验故障线路。基于MATLAB/ SIMULINK搭建32节点配电系统仿真模型,分析不同故障距离、不同故障位置（包含相邻线路分界点附近、分支线路）的故障测距结果和故障定位结果的正确性,结果表明,RBF模型的测距精度高,基于多代理的故障定位方法能够精确定位故障位置,且定位结果不受量测量误差与分支线路的影响。     

极端冰雪灾害等天气下输电线路运行的可靠性分析

在利用气象模型,考虑风速、降雨率、线路潮流、线路的隐性故障率等多种因素的基础上,提出了一种复杂的输电线路运行可靠性分析模型,并利用经典的蒙特卡罗分析方法进行了模拟,对系统的长期规划、短期运行调度都有着积极意义。给出了基于中国某地区的实际电网的算例分析,仿真结果表明,天气状况和隐性故障对输电线路的可靠性有着不可忽视的影响。     

Thermo-fluid dynamics of Loop Heat Pipe operation

The paper presents a thermo-fluid dynamic model for the transient operations of a Loop Heat Pipe. The Fourier heat conduction equation in a hollow cylinder is solved to determine the temperature distribution of the compensation chamber and the cavity. A one-dimensional transient model is also derived for the vapor temperature in the condenser section of the Loop Heat Pipe. The thermo-fluid dynamic characteristic of a Stainless Steel/Ammonia Loop Heat Pipe is analyzed.     

江西电网涉鸟故障分析及防范

为分析江西电网涉鸟故障原因及规律,通过统计2009~2016年涉鸟故障,发现涉鸟故障主要发生在农田或邻近水源低海拔地区,4~7月为涉鸟故障发生的高峰期,且鸟巢类故障主要发生在凌晨和早晨,而鸟粪类故障主要发生在夜间至凌晨。同时,涉鸟故障发生的概率还与杆塔的电压等级、杆塔结构型式、排列方式、相别和天气有关。为更好地防范涉鸟故障的发生,综合考虑鸟类分布、人类干扰度、地理环境和运行经验等要素,提出了涉鸟故障差异化防治措施。研究成果对于降低涉鸟故障率,保障电网安全运行有重要意义。     

民用大涵道比涡扇发动机吸鸟过程动态性能仿真研究

为验证民用大涵道比涡扇发动机对《航空发动机适航规定》CCAR33.76吸鸟适航条款的适用性,针对吸鸟条款中的中鸟附加完整性子条款开展数值仿真研究。基于风扇叶片鸟撞过程动力学仿真结果及鸟撞前后风扇特性数值计算结果,以某型发动机为例建立吸鸟过程动态性能仿真模型,完成了发动机从吸鸟开始到最终稳定的动态过程仿真,获得了吸鸟过程及最终稳定后的性能变化情况。结果表明:吸鸟后发动机性能急剧变化的主要因素是风扇叶片的塑性形变,通过起飞状态发动机吸鸟前后稳态节流特性对比,起飞推力下降约8%,满足持续的功率或推力损失不超过25%的条款要求;随着转速下降,风扇外涵喘振的风险极高,需改进设计保证吸鸟后风扇外涵仍具有足够的裕度;吸鸟前后,涡轮进口温度及发动机排气温度均下降,不存在超温风险。     

基于鸟鸣功率谱密度的输电线路涉鸟故障相关鸟种智能识别

鸟类活动对架空输电线路的运行影响较大,不同鸟种引起的线路故障差异明显,为了提高渉鸟故障防治的针对性,需分类识别输电线路相关鸟种。以鸟粪类、鸟巢类、鸟体短接类、鸟啄类四种渉鸟故障对应的8种代表性鸟种为例,通过分帧加窗、端点检测等预处理,采用离散傅里叶变换和Welch算法获取不同鸟鸣信号的功率谱密度(PSD)图,从中提取129个频率点的PSD特征,并基于随机森林建立分类识别模型,以PSD特征作为输入量,开展模型训练和不同鸟种分类测试,8种鸟类的识别准确率为83.3%~100.0%,提高了渉鸟故障防治措施的精准性。     

Five-leg converter topology for wind energy conversion system with doubly fed induction generator

In this paper, application of a five-leg converter in Doubly Fed Induction Generator (DFIG) for Wind Energy Conversion Systems (WECS) is investigated. The five-leg structure and its PWM control are studied and performances are compared with the classical six-leg topology. The main drawback of five-leg converter with respect to the six-leg back-to-back converter is the need to increase the dc-link voltage for the same operation point, i.e. the same powers in case of WECS. So, different methods for the reduction of the required dc-link voltage in the five-leg case are studied. The five-leg converter is used to replace the conventional six-leg one, with the same ability. For the performance evaluation of this structure and its fully digital controller in a more realistic and experimental manner, Hardware in the Loop experiments is carried out. It is shown that efficient control of active and reactive powers and dc-link voltage is performed. Hardware in the Loop results demonstrate the high performance of the proposed fully digital control which is implemented on an Altera FPGA target.     

Deep learning–based automatic bird identification system for offshore wind farms

Practical deterrent methods are needed to prevent collisions between birds and wind turbine blades for offshore wind farms. It is improbable that a single deterrent method would work for all bird species in a given area. An automatic bird identification system is required in order to develop bird species–level deterrent methods. This system is the first and necessary part of the entirety that is eventually able to automatically monitor bird movements, identify bird species, and launch deterrent measures. A prototype system has been built on Finnish west coast. In the proposed system, a separate radar system detects birds and provides WGS84 coordinates to a steering system of a camera. The steering system consists of a motorized video head and our software to control it. The steering system tracks flying birds in order to capture series of images by a digital single‐lens reflex camera. Classification is based on these images, and it is implemented by convolutional neural network trained with a deep learning algorithm. We applied to the images our data augmentation method in which images are rotated and converted into different color temperatures. The results indicate that the proposed system has good performance to identify bird species in the test area. Aiming accuracy for the video head was 88.91 %. Image classification performance as true positive rate was 0.8688.     

基于迁移学习的光伏组件鸟粪覆盖检测

该文基于无人机光伏组件可见光图像采集,提出一种基于迁移学习的光伏组件鸟粪检测方法.方法首先基于掩膜区域卷积神经网络(Mask-RCNN)对光伏组件边界进行框选,再利用迁移学习策略,构建光伏组件鸟粪缺陷检测模型,实现鸟粪智能检测.利用上述方法,实现光伏组件鸟粪覆盖检测准确率为96.75％.     

Experimental Studies on Heat Transfer Characteristics In Inverted Evaporator of Micaro／Miniature Capillary Pumped Loop

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Experimental optimization of capillary structures for loop heat pipes and heat switches

Loop Heat Pipes (LHP) and Heat Pipes (HP) are used in the thermal management of electronic devices with high-density heat dissipation. In these two-phase thermal devices, the key component is the capillary structure (CS) that pumps the working fluid using the capillary forces generated by the meniscus, which is formed due to evaporation. The performance of the LHP and the HP depends greatly on the internal structure and external configurations of the CS. However, there is not enough experimental and theoretical data on the optimization of the capillary structures of evaporators. The “inverted meniscus” scheme is the usual configuration for Loop Heat Pipes (LHP) but not for Heat Pipes (HP), which use the “classical” scheme. This paper presents the results of extensive experimental investigations on the optimization of the physical and geometrical parameters of the flat CS including thickness, configuration and size of vapor grooves, for different CS materials and working fluids. Additionally, the paper presents a comparative study between the “classical” and the “inverted meniscus” schemes of vaporization. Based on the obtained results, two examples of evaporators have been designed and evaluated.