Descriptive IoT Based Design and Implementation of a 3-Input Automatic Transfer Switch with Data Logging Features

Electricity is crucial for critical sectors such as banking, healthcare, education, and business. However, in developing nations like Cameroon, persistent power fluctuations and outages present significant challenges, leading to communication disruptions, food spoilage, water supply interruptions, and financial losses. This study proposes a novel solution: a three-input automatic transfer switch integrated with Internet of Things (IoT) and data logging capabilities. The system automatically switches between three independent power sources based on priority and availability, employing electromechanical contactors, relays, and timers for seamless switching. It incorporates ATMEGA328P microcontrollers, a GSM module for communication, and an SD card module for efficient data logging. Safety measures, such as miniature circuit breakers, voltage monitoring relays, and proper grounding, ensure user protection and system integrity. A user-friendly mobile application enables remote manual switching and real-time system information requests, while SMS notifications inform consumers about power source changes. The system has a power rating of 4.752 kW, accommodating a maximum continuous load of the same value. Voltage dividers provide a reliable 3.37 VDC output from a 12 VDC input, and data logging operates effectively by storing system data onto an SD card every 1.5 seconds. Comprehensive testing validates the system’s performance, with an average percentage error of 2.31% compared to actual values, falling within an acceptable range. This solution distinguishes itself by incorporating modern technologies like data logging and IoT, addressing the limitations of existing alternatives.

基于Attention-LSTM的电力负荷自动预测方法

电力负荷预测方法异常数据筛选能力较差,导致预测精度较低,为此,基于Attention-LSTM研究一种新的电力负荷自动预测方法,构建ZigBee组网协议下的数据采集信息组网,采集电力负荷原始数据,建立自动预测模型,将电力负荷数据输入到数据处理模块中,构建模态序列,将各个子序列中的模态分量结果重组叠加,得到电力负荷功率的预测结果。实验结果表明,该方法能够筛选出绝大部分异常数据,异常数据筛选率在90%以上,预测精度在99%以上,预测时间低于15 s。

Automatic Modeling of Fault Tree for NuIEEE Transactions on Power Electronics,Clear Power Safety I&C Configuration

The automatic modeling of fault tree for nuclear power safety I&C configuration is designed to meet the requirements of reducing the workload and improving the traceability during the nuclear power safety I&C system reliability assessment work. To complete the fault tree automatic modeling, the Visio Automation software technology is used to analyze the topology of the nuclear power safety I&C system hardware device and software function. The good result in practical implementations shows that the nuclear power safety I&C system fault tree modeling work is successfully simplified.

An Automatic Synchronization Method for Distributed Power Electronics System

Currently, the high-speed serial fiber-optic ring net communication is a main method for performing the distributed control network topology and control mode. Because of a network transmission delay inherent in the topology, synchronization between nodes has become a critical issue which needs to be studied. The existing synchronization methods largely depend on the complex communication protocol. Therefore, this paper has proposed a method of automatic measurement and compensation of synchronization delay, and analyzed its operating principle and implementation procedure in detail. The results obtained from the experiments prove the proposed method to be correct, effective and practicable.

The Application of Principle of Automatic Control in the site Management of Electric Power Construction Enterprise

It is need to establish site project department during the construction of electric power project.The head office should design and build the main structure,continually improve structure of project department,meantime,positively apply principle of automatic control to improve the site management of electric power construction.In this article,the application strategy of principle of automatic control is analyzed focusing on the site work of electric power construction.

基于KL-散度的电力用电数据自动脱敏算法研究

电力数据中包含一些隐私数据,一旦泄漏,就会对个人隐私安全造成隐患。为保证电力数据的安全性,提出了基于KL-散度设计电力用电数据自动脱敏算法。基于KL-散度算法建立敏感数据过滤模型,计算不同变量数据的KL距离,得到其相似性指标,对用户项目评分进行平滑处理,将具备相似性的敏感数据分成不同的批次。敏感数据去身份化处理,将数据匿名转换,计算用户真实路径被泄露的概率。设计数据自动脱敏算法,分别计算概念化数据、元组信息以及信息流的损失程度,以此判定脱敏后的数据是否可用。检验脱敏前后数据一致性,三类电力用电数据的变化率分别为0.43%、0.14%和0.11%,远远小于标准值。且算法在运行过程中单位时间处理数据量和平均延迟时间也较为理想,可见该脱敏算法具备实用性。

基于风电-负荷匹配度的风电消纳能力自动评估方法

风力发电是一种绿色清洁发电技术,风能分布不均,存在着弃风问题,基于此,研究基于风电-负荷匹配度的风电消纳能力自动评估方法。创建风电-负荷场景,获取真实风电-负荷数据,计算风电-负荷匹配度,选取风电消纳能力自动评估指标,构建风电消纳能力自动评估模型,明确构建模型的约束条件,基于粒子群优化算法获取评估数值,根据评估规则确定风电消纳能力,实现风电消纳能力的自动评估。实验数据显示:应用提出方法获得的风电消纳能力自动评估时延最小值为11.4 s,评估结果误差最小值为2%,风电消纳能力评估效果更佳。

Design and Realization of Automatic Warehouse Based on S7-1500PLC

In order to improve the efficiency of automatic warehouse control system,the experimental platform of stereoscopic warehouse with s7-1500plc is designed.The manipulator is driven by stepper motor and servo motor to realize x,y and Z three-axis space motion.The material transmission system is built by general-purpose G120 inverter.HMI KTP700 realizes control and status monitoring.The materials are identified and classified by RFID sensor and other sensors.TIAV15 software build PROFINET com­munication and PROFIBUS communication network.Using the GRAPH language programming can improve the visualization degree of application and solve the complex problems of program design and debugging of the warehouse control system.Through the design of hardware and software,a set of complete control system design scheme is formed,which has high practical value and provides an excellent teaching and experiment platform for the intelligent storage system.

A 155 Mbps laser diode driver with automatic power and extinction ratio control

An integrated laser diode driver(LDD) driving an edge-emitting laser diode was designed and fabricated by 0.35 μm BiCMOS technology. This paper proposes a scheme which combines the automatic power control loop and temperature com-pensation for modulation current in order to maintain constant extinction ratio and average optical power. To implement tem-perature compensation for modulation current,a novel circuit which generates a PTAT current by using the injecting base current of a bipolar transistor in saturation region,and alternates the amplifier feedback loop(closed or not) to control the state of the current path is presented. Simulation results showed that programmed by choice of external resistors,the IC can provide modu-lation current from 5 mA to 85 mA with temperature compensation adjustments and independent bias current from 4 mA to 100 mA. Optical test results showed that clear eye-diagrams can be obtained at 155 Mbps,with the output optical power being nearly constant,and the variation of extinction ratio being lower than 0.7 dB.

基于T-S模糊神经网络的光伏发电机组自动控制

光照情况变化会使光伏发电机组功率呈现不稳定性,加大光伏发电机组控制难度,为此,设计了基于T-S模糊神经网络的光伏发电机组自动控制方法。构建光伏阵列数学模型,分析在均匀和不均匀2种光照情况下光伏发电机组特性曲线。以分析结果为依据,采用T-S模糊神经网络构建光伏发电机组自动控制模型。为保证良好的控制效果,引入定比因子优化隶属度函数,输出最佳跟踪结果,结合最佳跟踪结果和自动控制模型实现光伏发电机组自动控制。测试结果显示,该方法能够完成光伏阵列特性分析,控制效果好。

基于负荷预测的飞轮-火电系统自动发电控制响应性能优化

随着新能源发电占比的不断增加,电网频率的稳定性受到严峻挑战,传统火电机组参与电网调频的作用愈发突出,然而部分火电机组的调节速率和精度难以满足电网负荷变动需求。为此,提出一种基于负荷预测的飞轮-火电系统自动发电控制响应性能优化策略。首先对负荷进行预测,采用基于树的管道优化工具TPOT库自动机器学习搭配并训练负荷回归预测模型,在训练数据中引入自动发电控制日前计划值以减少预测误差;然后根据负荷预测值以及飞轮系统的当前荷电状态,以火电机组调节速率最小化为优化目标,在负荷分配中优先动作飞轮储能系统,并调整飞轮荷电状态;最后基于湖北某火电厂实际运行数据进行仿真实验,实验结果证明了所提方法能够有效改善火电机组的调频性能。

A novel technique for automatic seismic data processing using both integral and local feature of seismograms

A novel technique for automatic seismic data processing using both integral and local feature of seismograms was presented in this paper. Here, the term integral feature of seismograms refers to feature which may depict the shape of the whole seismograms. However, unlike some previous efforts which completely abandon the DIAL approach, i.e., signal detection, phase identifi- cation, association, and event localization, and seek to use envelope cross-correlation to detect seismic events directly, our technique keeps following the DIAL approach, but in addition to detect signals corresponding to individual seismic phases, it also detects continuous wave-trains and explores their feature for phase-type identification and signal association. More concrete ideas about how to define wave-trains and combine them with various detections, as well as how to measure and utilize their feature in the seismic data processing were expatiated in the paper. This approach has been applied to the routine data processing by us for years, and test results for a 16 days＇ period using data from the Xinjiang seismic station network were presented. The automatic processing results have fairly low false and missed event rate simultaneously, showing that the new technique has good application prospects for improvement of the automatic seismic data processing.

Multi-train modeling and simulation integrated with traction power supply solver using simplified Newton–Raphson method

Multi-train modeling and simulation plays a vital role in railway electrification during operation and planning phase. Study of peak power demand and energy consumed by each traction substation needs to be deter- mined to verify that electrical energy flowing in its railway power feeding system is appropriate or not. Gauss-Seidel, conventional Newton-Raphson, and current injection methods are well-known and widely accepted as a tool for electrical power network solver in DC railway power supply study. In this paper, a simplified Newton-Raphson method has been proposed. The proposed method employs a set of current-balance equations at each electrical node instead of the conventional power-balance equation used in the conventional Newton-Raphson method. This concept can remarkably reduce execution time and computing complexity for multi-train simulation. To evaluate its use, Sukhumvit line of Bangkok transit system （BTS） of Thai- land with 21.6-km line length and 22 passenger stopping stations is set as a test system. The multi-train simulation integrated with the proposed power network solver is developed to simulate 1-h operation service of selected 5-min headway. From the obtained results, the proposed method is more efficient with approximately 18 % faster than the conventional Newton-Raphson method and just over 6 % faster than the current injection method.

660 MW超超临界机组CO-O_(2)控制技术的应用

利用火力发电厂烟气排放连续监测系统(CEMS),实现锅炉烟气中一氧化碳(CO)、氧气(O_(2))的测量,设计完善风量氧量串级控制系统,实现CO-O_(2)联合控制。实际应用结果表明:该系统投入后可以有效监控CO含量,减少锅炉燃烧中产生的CO,为锅炉燃烧调整提供数据支持,提高锅炉效率,减少水冷壁高温腐蚀,进而提高锅炉运行的安全性、经济性。

Key Problems of Cold Power Spinning of Ti-15-3 Alloy

The key problems of cold power spinning of Ti-15-3 alloy are studied. Reasonable billet preparation methods are presented to improve crystal structure and avoid crack of billet. Influences of original wall thickness, reduction rate and feed rate on expanding in diameter are analyzed and some methods to prevent expanding in diameter are given.

基于YOLOv5与改进VGG-CTC的数字仪表自动读数方法

随着数字电网的发展,数字仪表在电网中的应用越来越广泛。为进一步提高数字仪表自动读数算法的准确率和识别效率,推动数字电网建设,文中提出一种基于YOLOv5和改进VGG-CTC模型的数字仪表自动读数方法。该方法包括数字区域定位和仪表字符识别两部分。首先,采用YOLOv5模型检测输入图像的仪表数字区域,输出预测的数字区域边界框;然后,对VGG网络的卷积层和全连接层参数进行改进,提出一种改进VGG网络,将预测的数字区域输入该网络,即可提取数字区域图像特征,通过长卷积层输出字符概率分布信息;最后,经过CTC转录模块将概率分布序列映射为预测的数字仪表示数。实验结果表明,所提自动读数方法的准确率为89.63%,识别时间为439 ms,相比其他读数方法具有较好的读数准确率和识别速度,能够提高智能电网对设备状态监测的准确性和高效性,对推进能源物联网和数字化电网的建设具有重要意义。

基于LM-CNN的输变电工程造价自动计算模型

输变电工程造价计算作为造价管控技术的核心环节,其计算模型的好坏直接影响输变电工程造价管控效能。然而现有模型往往不能兼顾计算速度、精确性与稳定性。为解决上述问题,首先,针对输变电工程造价中的实际需求确定模型的输入与输出,构建卷积神经网络模型;然后,将历史造价数据作为样本输入网络模型,得到网络输出;最后,针对期望输出与实际输出相差较大的问题,利用列文伯格-马夸尔特算法对卷积神经网络的权重参数进行优化,完成模型训练。该模型结合列文伯格-马夸尔特算法与卷积神经网络模型的优点,相比于反向传播(BP)神经网络与梯度下降法-卷积神经网络(GD-CNN)具有更高的预测精度与稳定性,提高了输变电工程造价的计算效果。

Hybrid Loader Automatic Shift Strategy Based on Neural Network

Hybrid loader 's comprehensive performance mainly depends on the performance of hydraulic torque converter during its driving and working. Hybrid loader and hydraulic torque converter are taken for the research objects. The primary characteristic curve of hydraulic torque converter and the traction curve of hybrid loader are acquired by analyzing the characteristic parameters of hydraulic torque converter, the characteristic parameters of engine, the characteristic parameters of battery pack and geometric parameters of hybrid loader. The gear shift curves based on the best energy saving performance and the best power performance are acquired respectively with the opening of throttle,the speed of pump wheel and the speed of turbine as parameters. Then the two curves are combined to get the comprehensive gear shift curve. Radical basis function( RBF) neural network is applied to building the gear shift strategy to keep hybrid loader with the best power performance and energy saving performance. The experimental bench is set up for experimental verification. It proves that both of the power performance and energy saving performance of hybrid loader are improved effectively by using the automatic shift strategy.

Investigation on some key problems of large power AC-DC-AC converter

China is an important country in iron and steel industry.Power electronics converters are widely used.For the cold rolling mills of high speed,AC-DC-AC converters should be used.In the paper,the design and the control system of the large power three-level AC - DC - AC converter with IGCTs is investigated,and a back-to-back large power three-level AC - DC - AC converter with IGCTs has been got. With a series experiments,the performance of the converter is examined.The experiment result indicates the converter reaches the design requirement and it shows excellent performance.The converter system has been put into use safely.It is estimated that the AC - DC - AC converter system will be used in the drive systems for rolling mills in the near future.