When a single-phase grounding fault occurs in the low-current grounding system,the fault characteristic of the zero-sequence current is weak and highly complex,therefore the reliability of the traditional line selection method is badly in need of improvement.To address this issue,a fault line selection method for distribution networks based on variational mode decomposition(VMD)and dilated convolutional neural network is proposed in this paper.Firstly,the electrical characteristics of healthy lines and faulty lines are analyzed,and zero-sequence current is used as fault characteristic signal to provide theoretical basis for the input of the line selection model.Secondly,the zero-sequence current sequence is decomposed into different frequency intrinsic mode functions(IMF)using the VMD technique to enhance the stability and distinctiveness of the fault signal features.Secondly,dilated convolutional neural network is used as line selection network to improve the adaptive classification ability of the model by enlarging the receptive field of convolutional operation.Finally,a 10 kV distribution network is constructed in MATLAB/Simulink for the case study analysis.The results suggest that the proposed method yields favorable conductor selection outcomes across various fault scenarios,thus verifying the robustness and accuracy of the proposed approach.
Although some results have been obtained in the analysis of factors affecting commutation failure,but the influence of fault clearance time(fault division angle)on commutation failure still needs to be studied further.Firstly,based on the commutation failure process,the effect of zero-crossing offset angle on the turn-off angle is analyzed.Secondly,based on the time area of commutation voltage,the influence of different initial fault angles on the first commutation failure of the inverter is analyzed,and the influence of fault division angle and zero-crossing offset angle on subsequent commutation failure is further analyzed.It is found that the risk of subsequent commutation failure is greatest when the fault is cleared in commutation.Finally,taking single-phase grounding fault as an example,simulation test results of different initial fault angles and fault division angle based on PSCAD/EMTDC and CIGRE HVDC models verify the correctness of the theoretical analysis.
In order to ensure the stability of the transmission voltage and effectively control the operation of the DC transmission system in the event of three-phase short circuit fault, this paper proposes a DC transmission system operation control method based on multilevel converter module (MMC). The multilevel converter module is designed by using the anti parallel diode and parallel capacitor to obtain the AC equivalent inductance, ensure that the AC/DC flow of the converter station is the same as the active power, and clarify the power situation in the converter station; The module is combined with the feedforward decoupling compensation term, and the PI is used to obtain the input value of the current inner loop operation controller to realize current decoupling, increase the stability control of DC voltage, and improve the anti-interference of the transmission system; The corresponding reference value is obtained through the correction and control link, and the optimal operation control result is obtained. The experiment proves that the designed module can ensure the smooth operation of the power transmission system under normal working conditions, control the impact in a safe range when a fault occurs, and ensure the stability of the power transmission system.
With the increasing penetration of distributed renewable energy and flexible loads in the distribution network, the traditional distribution network is gradually transitioning to an active distribution network. Due to the vigorous development of new power system, the economic dispatch of active distribution network faces great challenges. Therefore, this paper introduces V2G technology while considering the carbon emission of the system, establishes an orderly charging and discharging model for electric vehicles and then builds demand response modeling based on transferable load and interruptible load, and then conducts second-order cone relaxation on the branch power flow constraints of the distribution network. Finally, With the goal of minimizing the dispatch cost for active distribution network, this paper proposes a low-carbon economic dispatch model for active distribution network considering V2G and demand response. The Case studies of IEEE 33-node power distribution system verifies that the proposed model can effectively reduce the dispatch cost, enhance the security of system operation and reduce carbon emission.
Since Age of Information (AoI) has been proposed as a metric that quantifies the freshness of information updates in a communication system, there has been a constant effort in understanding and optimizing different statistics of the AoI process for classical queueing systems. In addition to classical queuing systems, more recently, systems with no queue or a unit capacity queue storing the latest packet have been gaining importance as storing and transmitting older packets do not reduce AoI at the receiver. Following this line of research, we study the distribution of AoI for the GI/GI/1/1 and GI/GI/1/2* systems, under non-preemptive scheduling. For any single-source-single-server queueing system, we derive, using sample path analysis, a fundamental result that characterizes the AoI violation probability, and use it to obtain closed-form expressions for D/GI/1/1, M/GI/1/1 as well as systems that use zero-wait policy. Further, when exact results are not tractable, we present a simple methodology for obtaining upper bounds for the violation probability for both GI/GI/1/1 and GI/GI/1/2* systems. An interesting feature of the proposed upper bounds is that, if the departure rate is given, they overestimate the violation probability by at most a value that decreases with the arrival rate. Thus, given the departure rate and for a fixed average service, the bounds are tighter at higher utilization.
大量研究和实发事件表明,柔性直流输电技术的应用会在系统中引入潜在的振荡风险.以往对于柔直振荡的研究往往集中于交流侧,而对于直流电网侧的振荡问题研究较少.该文针对柔直换流器与直流电网之间的振荡问题展开研究,首先通过电磁暂态仿真分析复现出柔直系统中高频振荡现象,其次建立系统直流阻抗网络模型,然后采用对数导数法定量分析系统振荡模式,最后分析了振荡的影响因素,总结了多端柔直电网中高频振荡特性.
On the basis of the method of moments, the resistive coupling effect between the newly built grounding network. When the horizontal distance between two grounding networks of a substation changes, this original grounding network of a certain substation is analyzed. And establish corresponding soil models based on actual engineering soil resistivity data. Use the grounding grid analysis function of CDEGS software and Powerstation software simulation software to simulate and calculate some parameters of the new and old grounding grids. The analysis parameters mainly include the grounding resistance, step voltage, and contact voltage of the grounding grid system. And the obtained parameter indicators are compared and analyzed with safety limits to determine the safety performance of the newly built grounding grid system in the substation. And the impact on the grounding performance of the original grounding network of the substation. Provide certain theoretical data support for the actual promotion of substation grounding network engineering.
云团运动的不确定性使得光伏系统输出功率较难准确估计,从而影响新能源并网的可靠性和经济性.为了有效利用卫星的云观测数据,提出了基于云图特征的超短期光伏发电功率预测模型.利用卷积神经网络对卫星云图进行特征提取,且和通过相关性分析后的 4 种气象特征进行融合,作为光伏发电功率预测模型输入.在此基础上,通过卷积神经网络解析这些特征之间的空间联系,并使用长短期记忆网络实现对光伏输出功率的时间序列预测.此外,考虑到一个自然日中不同时段数据对预测影响不同,引入多头注意力机制来确定关键时间点与关键特征,由此进一步提高所提模型精度.使用光伏电站实际数据以及对应的卫星云图和天气数据,对所提模型的预测效果进行验证.算例分析结果表明,该模型预测精度高且时效性好,特别对于正午辐照较大以及云团运动波动剧烈的时段,模型仍能保证较高的预测精度.
电缆接头线芯温度计算是实现电缆载流量预测重要环节.该文通过三芯电缆接头结构分析其散热路径,进一步考虑了电缆接头的轴向散热,提出了改进的热路模型.以10 kV三芯电缆中间接头为例开展有限元温度场计算,并根据温度-热源的响应实现稳态热路模型的参数辨识.同时,分析了不同电缆电流以及环境散热条件下稳态热路模型的等效性,与有限元仿真结果吻合良好.该模型可以有效提高电缆接头热点计算的效率.
为解决目前电力设备故障识别系统识别敏感度低的问题,提出基于云计算关联分析的电力设备故障识别模型.利用关联分析法、Model-1 故障特征提取法、Copula函数的故障特征分类法,对电力设备故障特征进行提取和分类,将分类后的特征数据随机组成训练集X,并在此基础上获得故障特征优化的二维数据,将Copula函数的输出结果导入优化ID3的井漏类型分类算法中以完成对故障特征的优化,得到电力设备故障特征分类矩阵;利用非对称性卷积层的CNN模型,实现对电力设备多种故障类型的快速识别.实验结果表明:在进行故障准确性检测时,所提方法的故障识别率平均高达87.2%、识别精准率平均高达 71.06%;在不同负荷对系统灵敏性影响的测试中,所提方法在任意负荷状态下的故障识别数据计数不低于 40 次,优于对比方法;在对电力设备匝间短路故障位点的识别性能测试中,所提方法在任意匝间短路故障位点的故障识别数据计数均高于 140 次,优于对比方法.所提方法的故障识别精确度高、故障位置识别敏感性高,可促进电网安全运行和发展.
电网中大量新能源替代常规同步发电机机组导致系统惯性时间常数降低,调频能力不足,频率波动增大.基于光伏机组高度可控特性,提出一种考虑变工况的光伏下垂控制与二级电容响应的调频策略.模拟传统调频过程,策略同时考虑惯性响应和下垂控制响应,由直流电容和光伏减载备用分别承担两项调频功率,最大化利用调频资源.所提策略通过运用改进频率变化率测量法,优化惯性响应;通过光照参数估算确定实际最大功率值,以适应变化运行工况;自适应下垂系数能适应光伏实际出力,在可用功率范围内向上/向下调整系统频率.PSCAD仿真验证表明,所提策略能够最大化利用光伏现有调频资源,对于变化工况的适应性良好,能够在不超光伏运行极限基础上有效改善系统频率响应.
为保证风电场集电线路输送潮流时的稳定性,在高比例柔性负荷接入下提出了风电场集电线路入廊规划方法.调度接入工业高载能负荷与柔性负荷 2 种高比例柔性负荷,并将其作为风电场集电线路入廊规划方法的目标函数;构建风电场集电线路潮流约束,限制线路输送潮流,设计高比例柔性负荷约束,结合潮流约束与高比例柔性负荷约束构建线路入廊规划方法,并使用蚁群算法获取全局最优解,得到最佳规划线路.经实验验证:该方法接入高比例柔性负荷后,具备明显的削峰填谷能力.
为提升风光水火蓄多源互补运行的经济性,计及不同类型电源的调峰特性,提出一种基于改进免疫蚁群算法的风光水火蓄多源互补优化调度策略.以火电机组的煤耗成本和启停成本、水电机组的发电成本、抽水蓄能的运行成本以及弃风弃光惩罚成本最低为优化目标,构建了风光水火蓄多源互补优化调度模型;提出改进的免疫蚁群算法对调度模型进行求解,改善了人工蚁群算法易陷入局部最优解的缺陷;通过夏、冬季典型日不同装机容量的抽水蓄能的算例仿真,表明所提模型可以充分利用抽水蓄能机组的"削峰填谷"以及能源之间的互补性,实现降低火电机组煤耗、新能源全额消纳、利用柔性电源调节的目的.
水电是可再生能源的重要组成部分,精确预测水电站的发电量对电力系统的运行和调度至关重要.针对传统预测方法在处理水电站之间复杂的拓扑结构时存在限制的问题,提出了一种基于图迁移学习的方法,旨在通过水电站的拓扑连接特征提升发电预测的准确性和泛化能力.利用水电站的拓扑结构构建图表示各水电站之间的关联关系,以捕捉水电站的上下游关联特征,采用预训练源水电站数据集并通过图迁移学习来适应目标水电站的发电预测模型.实验结果表明,图迁移学习有助于更好地捕捉水电站间的拓扑特征,提高发电预测精度,减少所需训练样本数量.
为了解决直流系统中工况变动及负载变更条件下造成的故障电弧识别准确率低的问题,提出了一种基于自适应噪声的完全集合经验模态分解-希尔伯特(complete ensemble empirical mode decomposition with adaptive noise-Hilbert transform,CEEMDAN-HT)包络谱和堆叠自编码器(stacking automatic encoder,SAE)的直流串联故障电弧诊断方法.首先参考雄安高铁站区直流系统典型负载搭建含混合负载的直流串联故障电弧实验平台,采集多工况下的电流信号并建立故障电弧数据库.其次采用CEEMDAN对原始信号进行分解得到多个固有模态函数(intrinsic mode function,IMF),然后进行HT变换Hilbert transform)分析包络谱,组成首尾相接的高维特征样本,最后将样本输入SAE模型中学习特征,实现变负载下的直流故障电弧识别.实验结果表明:该方法能够很好地发挥CEEMDAN-HT从原始信号中提取故障电弧特征和SAE无监督学习的能力,不需要人工设置阈值即可准确识别故障电弧并进行负载分类,平均准确率可达98.9%.
电力线通信检测装置是低碳楼宇能源互联网的核心设备,其采用的电力线载波通信(power line communication,PLC)的传输速度虽快,但路径搜索信令的通信可靠性较低,严重制约了中继对通信性能的提升效果;双向工频自动通信系统(two way automatic communication system,TWACS)的可靠性虽然很高,但路径搜索速度较慢,严重影响了通信时效性.为提高电力线通信检测装置在能源互联网信息感知中的性能,提出一种基于PLC与TWACS的多模式融合通信路径搜索算法.为保证电力线通信的覆盖范围,在改进算法中由PLC负责主要数据信息的传输;而下行通信搜索信令则由鲁棒性较强的TWACS替代,以保证广播信息与路径中继指令传输的可靠性.仿真结果表明,所提算法能够有效提高能源互联网的通信质量和通信效率,更好地满足低碳楼宇电力线通信检测装置的性能需求.
针对光伏的不确定性、波动性与反调峰性对配电网稳定运行造成巨大冲击,而大幅增加配网调峰压力的问题,提出了光伏-氢储能辅助调峰的双层优化配置模型.基于光伏波动量对配网的影响,将原始光伏出力曲线分解为调峰分量与平抑波动分量;结合氢储能运行特性,配置用于调峰与平抑波动的储能容量,构建计及氢储能工作特性的储能系统运行策略;以系统运维成本、碳排放成本、弃光惩罚为优化目标,建立光伏-氢储能辅助调峰的配电网氢储能优化配置模型,并进行算例分析.结果表明,所提出的优化配置方案可有效降低光伏波动对配网的影响,缩减配网的运行成本,提升其运行经济性与稳定性.
提出冲击性负荷接入下风能并网暂态电能扰动的控制方法,对风能并网暂态电能扰动进行有效控制.运用小波变换来分解采集到的风能并网暂态电压信号,确定信号出现扰动的时间,完成风能并网暂态电能扰动的检测;构建DSTATCOM数学模型,完成风能并网暂态电能扰动时有功与无功电流的单独控制,实现无功补偿;将电力系统稳定器(dianli xitong wendingqipower system stabilizer,PSS)装配在并网中同步发电机(synchronous generator,SG)的自动电压调节器(automatic voltage regulator,AVR)内,改善风能并网的阻尼,提升风能并网的稳定性.实验结果表明:在不同信噪比条件下,该方法PI控制器的跟踪误差都较小,未超过 0.5,具有较好的跟踪性能与抗扰性;在 6 000 MV·A和 7 000 MV·A的 2 种冲击性负荷下,实现不同冲击性负荷状态下风能并网暂态电能扰动的有效控制,较好地改善了电能质量.
目前的储能建模研究大都关注其电磁仿真模型,难以用于大规模储能接入对系统稳定性的影响研究.该文提出了集中式储能电站的机电暂态建模方法,在电力系统分析综合程序PSASP的用户自定义(UD)模块中搭建了考虑限幅和附加功率控制的储能机电暂态仿真模型.在此基础上,提出了储能电站的自适应附加功率控制方法,并搭建了相应控制模块.不同工况下的仿真结果证明,所提模型能够准确模拟储能对电力系统的暂态支撑,所提自适应附加功率控制方案进一步提升了储能电站对系统的暂态支撑能力.
为了避免逆变器在运行过程中出现桥臂直通问题,器件的驱动时序中需要插入必要的死区时间.然而,死区会带来逆变器基波电压损失与畸变等问题.尤其当采用SiC MOSFET作为开关器件时,较高的开关频率使得波形畸变更严重,这使得传统应用于Si IGBT逆变器的死区补偿策略已经无法适用.为此,在传统死区消除策略的基础上,提出一种分段调制死区补偿策略.该策略通过建立的预测模型得到过零点处的电流纹波值,并以此划分电流过零区域和非过零区域.当输出电流处于非过零区域时,每相桥臂仅对有效器件进行开关动作,互补器件处于关断状态,以提高基波电压幅值;当处于过零区域时,针对死区时间、寄生电容等因素产生的误差,计算出等效脉冲补偿时间用于补偿误差电压,减少波形畸变.最后,仿真与实验结果证明了该补偿策略相较于传统的死区消除策略可减少低次谐波含量,改善输出波形质量,输出电压的THD可减少 1.63%.
