Power Line Monitoring Data Transmission Using Wireless Sensor Network

The WSN used in power line monitoring is long chain structure, and the bottleneck near the Sink node is more obvious. In view of this, A Sink nodes’ cooperation mechanism is presented. The Sink nodes from different WSNs are adjacently deployed. Adopting multimode and spatial multiplexing network technology, the network is constructed into multi-mode-level to achieve different levels of data streaming. The network loads are shunted and the network resources are rationally utilized. Through the multi-sink nodes cooperation, the bottlenecks at the Sink node and its near several jump nodes are solved and process the competition of communication between nodes by channel adjustment. Finally, the paper analyzed the method and provided simulation experiment results. Simulation results show that the method can solve the funnel effect of the sink node, and get a good QoS.

NEW PRINCIPLE FOR DIRECTIONAL COMPARISON CARRIER PROTECTION OF EHV TRANSMISSION LINES

The increasing scale and complexity of power systems require high performance and high reliability of power system protection.Protective relaying based on directional comparison with power line carrier or microwave channels is the most suitable protection scheme for long distance EHV transmission lines and is widely used in power systems.The key element of such protection is a directional relay used to discriminate the fault direction.In order to overcome the disadvantages of conventional directional relays,the authors of this paper put forward the directional comparison carrier protection based on the artificial neural network(ANN).The protection is extensively tested using electromagnetic transient program (EMTP) under various electric power system operating and fault conditions.It is proved that the directional comparison carrier protection based on ANN,which can recognize various fault patterns of the protected transmission line(such as fault direction,fault phases etc.)correctly in any kind of operating and fault conditions and the whole process,is satisfactory for EHV transmission line protection.

Power Line Communications Networking Method Based on Hybrid Ant Colony and Genetic Algorithm

When solving the routing problem with traditional ant colony algorithm, there is scarce in initialize pheromone and a slow convergence and stagnation for the complex network topology and the time-varying characteristics of channel in power line carrier communication of low voltage distribution grid. The algorithm is easy to fall into premature and local optimization. Proposed an automatic network algorithm based on improved transmission delay and the load factor as the evaluation factors. With the requirements of QoS, a logical topology of power line communication network is established. By the experiment of MATLAB simulation, verify that the improved Dynamic hybrid ant colony genetic algorithm (DH_ACGA) algorithm has improved the communication performance, which solved the QoS routing problems of power communication to some extent.

A Data Driven Security Correction Method for Power Systems with UPFC

The access of unified power flow controllers(UPFC)has changed the structure and operation mode of power grids all across the world,and it has brought severe challenges to the traditional real-time calculation of security correction based on traditionalmodels.Considering the limitation of computational efficiency regarding complex,physical models,a data-driven power system security correction method with UPFC is,in this paper,proposed.Based on the complex mapping relationship between the operation state data and the security correction strategy,a two-stage deep neural network(DNN)learning framework is proposed,which divides the offline training task of security correction into two stages:in the first stage,the stacked auto-encoder(SAE)classification model is established,and the node correction state(0/1)output based on the fault information;in the second stage,the DNN learningmodel is established,and the correction amount of each action node is obtained based on the action nodes output in the previous stage.In this paper,the UPFC demonstration project of NanjingWest Ring Network is taken as a case study to validate the proposed method.The results show that the proposed method can fully meet the real-time security correction time requirements of power grids,and avoid the inherent defects of the traditional model method without an iterative solution and can also provide reasonable security correction strategies for N-1 and N-2 faults.

基于随机森林优化RL的电力工程造价预测

针对现阶段电力工程造价数据预测准确度较低的问题,提出了一种基于随机森林优化RL的相关预测算法。通过分析影响电力工程造价的因素,将其按照影响程度的大小进行分级,利用随机森林算法加以筛选,并采用筛选后的影响因素特征向量作为预测模型的训练和测试数据。同时,将电力工程造价预测问题转化为输电线路规划问题,再使用强化学习优化蚁群算法的参数来构建电力工程造价预测模型。经过实验对照,综合两种栅格尺寸结果,所提方案比两种对照组算法的电子工程造价分别降低了2.97%、3.78%。

我国数据空间建设:核心要件、发展路径与推进策略

数字经济时代,算力和数据成为新质生产力和新型生产要素。构建国家数据空间,高效统筹利用算力和数据等战略资源,是加快推进网络强国、数字中国建设的战略举措。本文立足我国数字化发展实际,借鉴国外数据空间建设经验,提出了网络传输体系、算力调度体系、数据应用体系、安全保障体系“四位一体”的数据空间总体架构,明确了起步验证、打造样板、创新驱动的“三步走”发展路径,并从统筹推进机制、示范工程建设、关键技术创新、标准规范建立、算力与数据基础设施化、国际交流合作等方面提出了具体举措,以期为我国加快数据空间建设提供参考借鉴。

偏远油气田现场的通信新技术应用及效果分析

针对偏远油气田现场没有电信网络覆盖,导致现场数据无法采集回传,作业现场管理存在盲区,依赖移动通信网络进行的过程控制系统PCS(Process Control System)巡检作业无法使用等问题,提出了不同生产场景下利用通信新技术解决偏远油气田现场数据传输的方法,包括电力线载波、无线微波、NB-IOT、LORA、北斗卫星、高通量卫星等传输方式,结合生产现场实际情况,对每种技术的适用场景、成本效益以及可能的局限性进行了综合评估,得出了在不同应用场景下最适合的通信技术方案。结果表明,采用通信新技术可以快速解决不同偏远生产现场的传输难题,降低传输成本,为企业数字化发展助力。

基于小波神经网络的特高压直流输电线路故障测距方法

传统特高压直流输电线路故障测距方法直接对故障区段进行识别,未对故障电压信号空间状态模型进行构建,这导致了传统方法测距的精度存在较大误差。针对这一问题,文章提出了基于小波神经网络的特高压直流输电线路故障测距方法。通过构建故障电压信号空间状态模型进行故障区段识别,最后基于小波神经网络实现故障测距。对比实验结果表明,本文研究方法测距精度误差较小,具有重要的实际应用价值。

基于联合功率量/载波调制的DC-DC变换器功率/数据复合传输方法

DC-DC变换器可以同时进行功率变换和数据传输。针对较低通信速率限制功率/数据复合传输(power/data multiplexing transmission,PDMT)应用的难题,提出一种联合功率量/载波调制(joint power/carrier modulation,JPCM)的新方案。与传统二进制PDMT方案不同,JPCM同时对功率量/载波进行2FSK调制,实现两种数据并行传输,可以看作一种四进制FSK,有效提高通信速率。相较于传统四进制PDMT方案,JPCM方案解调环节所需带通滤波器数目可减少一半,且软件开销更低。首先,证明PDMT在理论上的可行性;然后,根据4种不同电压纹波频率配置不同码元,并设计了包含高低数据位调制的JPCM和基于滑动傅里叶变换的数据解调方案;此外,重点分析输出参考电压突变对通信的影响,动态调整阈值可有效抑制误码;最后,搭建一个由2个Buck变换器并联的实验装置,实验结果表明在稳态、负载突变和输出参考电压突变的工况下,JPCM方案均能实现20 kb/s的通信速率,验证了该方案的有效性。

基于动态平衡布局的输电网潮流图自动生成方法

为解决输电网潮流图自动生成中厂站布局与线路布线问题,提出基于动态平衡布局的输电网潮流图自动生成方法。针对厂站布局,首先,在力导向算法的基础上引入基于图纸中心点的惩罚函数,以解决力导向算法布局不均匀的问题,提高布局的均布度;然后,利用厂站分布率参数控制算法平衡次数,引导厂站向图纸边界运动,解决布局自动适应给定图幅大小的问题;最后,通过位置映射变换将围绕图纸中心点的椭圆分布转换为矩形分布,解决引入惩罚函数布局均匀但不符合传统输电网潮流图绘制习惯的问题。针对线路布线提出以构建通道树为中心的布线方法,有效降低布线交点个数,提升布线效果。所提布局与布线算法在实际工程应用中取得了良好的效果,通过案例验证了输电网潮流图自动生成的正确性和有效性。

基于区块链数据安全机制的输变电工程建设动态计算技术研究

针对现今输变电工程施工过程中不确定性因素较多、造价计算偏向静态等问题,文章建立了基于区块链数据安全机制的输变电工程造价实时动态计算模型,实现了造价实时动态计算技术与计算结果的精准高效。文章以区块链可信数据交换技术为底层模型,利用区块链去中心化信任体系、链上数据不可篡改等特性,构建输变电工程的数据上传、交互、储存与计算的架构体系;使用粒子群算法优化径向基神经网络参数,构造输变电工程造价数据预测计算模型;采用杰卡德距离对计算结果进行校正,且在反馈误差的同时进一步优化计算模型。利用仿真算例验证了模型的先进性与可行性。

基于注意力机制和LSTM-LightGBM的特高压直流输电线路可听噪声无效数据清洗方法

特高压直流输电线路可听噪声试验过程中,外界环境的突发性干扰会使实验数据中掺杂较多的无效数据,严重影响后续的数据分析。提出了一种基于注意力机制(attention mechanism,AM)和长短时记忆网络-轻量级梯度提升机(long short-term memory network-light gradient boosting machine,LSTM-LightGBM)的输电线路可听噪声无效数据清洗方法。首先,针对可听噪声数据的非线性、高维时序冗余特征等特点,以LSTM神经网络为基础进行特征提取;同时,引入特征维度注意力机制,自适应地分配权重来刻画关键特征信息的表达能力;进而,利用LightGBM对提取到的特征进行分类,检测出无效数据;然后,以某特高压直流输电线路实测可听噪声数据试验分析,结果表明该方法的检测精准率为95.55%,召回率为97.73%,F1分数为0.9663,均优于对比实验模型;最后,将无效数据删除并使用均值插补法填补,无效数据清洗后数据的50%值和95%值基本不变,仅降低无效数据的最大值和5%值。该算法对提高输电线路可听噪声数据的可靠性具有一定参考意义。

结合ECC算法的电力监控网络智能接入协议

为了进一步降低电力监控网络遭受攻击的风险,基于ECC公钥加密算法,提出了具有较高安全性能的智能接入协议。通过研究电力监控网络的基本架构和安全体系,总结了电力监控终端所面临的多种攻击方式。并在此基础上,利用ECC公钥加密算法,深度改进适用于电力监控网络的智能接入协议,进而优化协议的加密耗时、解密耗时及安全强度等多项参数。仿真结果表明,与基于RSA算法的协议相比,基于ECC算法的智能接入协议具备更高的安全强度。

Detection and Classification of Transmission Line Transient Faults Based on Graph Convolutional Neural Network

We present a novel transient fault detection and classification approach in power transmission lines based on graph convolutional neural network.Compared with the existing techniques,the proposed approach considers explicit spatial information in sampling sequences as prior knowledge and it has stronger feature extraction ability.On this basis,a framework for transient fault detection and classification is created.Graph structure is generated to provide topology information to the task.Our approach takes the adjacency matrix of topology graph and the bus voltage signals during a sampling period after transient faults as inputs,and outputs the predicted classification results rapidly.Furthermore,the proposed approach is tested in various situations and its generalization ability is verified by experimental results.The results show that the proposed approach can detect and classify transient faults more effectively than the existing techniques,and it is practical for online transmission line protection for its rapidness,high robustness and generalization ability.

基于多源异构气象数据融合的线路状态识别算法

针对传统输电线路状态判断方法存在费时费力且准确率偏低的问题,文中在多源异构气象数据融合分析的基础上提出了一种输电线路状态判别算法。该算法由气象数据分析模块和输电线路故障判断模块组成,对于LSTM网络中存在超参数选择困难的问题,利用WOA算法进行自动优化,以实现对气象数据的特征提取。而输电线路故障判断模块使用航拍线路图像作为训练集,通过引入GAN网络完成训练,并采用AE网络进行改进,从而提升原网络的性能。在实验测试中,所提算法在数据处理层面的MAE仅为0.1159,其余多个测试指标也均优于对比算法,同时还可根据训练得到的多源数据特征来对当前线路状态进行准确预测,表明了该算法具有良好的综合性能与工程实践能力。

Energy-efficient performance of cooperative relay network with joint sensing-transmission time duration and power allocation

A joint optimal sensing-transmission time duration and power allocation scheme has been proposed to maximize the energy efficiency for cooperative relay network. In particular, observing that the spectrum sensing and data transmission time duration lies within a strict interval, the joint optimal solutions of our proposed scheme are achieved by sequential optimization method. Numerical evaluation results reveal that the relay-assisted transmission using our proposed scheme significantly outperforms the non-relay transmission in terms of the network energy-efficiency.

基于改进CS算法的移动网络海量数据低能耗传输方法

移动网络数据传输过程未考虑数据间相关性,导致数据传输能耗大,对此文章提出了基于改进CS算法的移动网络海量数据低能耗传输方法。文章分析移动网络海量数据传输能耗,引入混沌扰动系数改进CS算法。在此基础上选取改进CS的双簇头,解决传统方法数据传输路径长的问题,设计静态、动态传输队列低能耗传输模式。由实验结果可知,该方法数据传输完整,不同工作模式下,使用基于改进CS算法最高耗能为2 J,耗能较低,该方法将指导移动网络在工业应用中的实现。

交流电力与信息数据双向同传的低压交流输电系统分析

随着电力电子技术与通讯技术的不断发展,采用同一电力电缆或信号电缆进行电力与信号同时传输也是构建新型电力系统的一个重要部分。本文提出了一种交流电力与信息数据双向同传的低压交流输电系统,一端负责调制数据信号作用在逆变器,另一端负责调制解调数据信号,这是一种与数据线供电和电力线载波通讯不同的信电同传方式。在分析该系统结构和工作原理的基础上,进行了仿真分析验证,结果表明该系统能够支持交流电力与信息数据的双向同传,适合较低功率低压交流功率传输的应用场合。

基于多导体传输线理论的配电网电力电缆载波模型降阶分析

为降低配电网电力电缆载波模型复杂程度,首先,根据配电网常用三芯XLPE绝缘电力电缆结构,结合电力电缆三相金属护套相互接触的实际,以三相金属护套为整体进行分析,将电力电缆7阶多导体传输线载波模型降为5阶。接着,根据配电网终端电力电缆金属护套、铠装直连接地的特点,将其进行等效处理,并分析了等效单位长度参数矩阵各元素与实际参数的关系,再次将配电网电力电缆5阶载波模型降为4阶。仿真试验验证了降阶分析的正确性,电力电缆载波模型的两次降阶,显著降低载波模型复杂程度,降低运算量提升分析速度,为载波通信在电力电缆传输中的进一步分析提供参考。

数据驱动的低压配电台区拓扑辨识技术综述

低压配网拓扑结构是新型配电网系统分析所关注的重点领域,高级量测体系建设为低压配网积累大量数据,数据驱动类方法备受关注。根据数据源类型不同,本文将低压配电台区拓扑识别方法分为两类:第1类基于电气量测量数据的机器学习与数据分析方法,包括相关性分析、聚类分析、数学规划和深度学习;第2类基于通信信号数据,利用电力线载波通信,采用调制信号、信号强度检测方法进行拓扑识别。最后,基于对现有方法的对比分析,对今后工作进行了展望,旨在为科研人员和工程技术人员提供参考。