This paper introduces the research on the key technology of bending control of strain clamp for transmission line. Through the development of special measurement tools, the introduction of intelligent measurement and data analysis functions, and the improvement of design to meet the needs of high-altitude operation, the problem of bending of strain clamp in the process of crimping is solved, and the quality control ability and detection efficiency and accuracy of crimping process are improved to ensure the operation reliability and safety of transmission line. Through the research and implementation of this scheme, it can not only reduce the transmission line fault caused by crimping quality defects, but also significantly reduce the labor intensity of construction personnel, improve the working environment, and promote the mechanization and intelligent development of transmission line construction technology.
This paper briefly introduces the basic principles and types of vehicle grounding,and conducts in-depth investigation and analysis on the distribution of ground current,the principle of drift current,and the path of drift current.Combined with practical tests,the vehicle electrical system under a new 2.0 architecture platform simulates the environment of ground closing and breaking,and accurately monitors the current through IPE equipment,and furthermore,a method for determining the safety of wire harnesses is proposed.Based on analyzing drift current path,it is found that the harness with risks meets the design requirements.The potential risks caused by the drift current are optimized and rectified by means of changing and disassembling the ground point,and thickening the drift current ground wire.Post-rectification re-simulation on the grounding disconnection environment shows that the rectification achieves stable and safe grounding,and effectively ensures the functional operation of the 2.0 architecture platform.
In response to the gradual exhaustion of fossil energy and the worsening of the climate environment,global new energy power generation has developed rapidly.However,large-scale grid integration of new energy generation has not on-ly brought a great impact on the conventional energy market to maintain a balance of supply and demand,but also brought certain uncontrollable factors to the electricity market.In order to achieve full potential of the incentive role of electricity prices to mobilize the enthusiasm of both supply and demand,and to improve the level of consumption of new energy,a virtual power plant bidding strategy based on continuous bidirectional auctions is proposed.The applicable conditions,transaction methods,and transaction rules of electricity market transactions based on continuous bidirectional auctions are analyzed to establish a quotation function that conforms to the transaction psychology of buyers and sellers,and to per-form user cost calculation and error processing.Through multiple simulation tests,it is compared under the hidden bid auction.The new energy consumption efficiency and social welfare have verified that the proposed continuous bidirectional auction-based bidding strategy for virtual power plants is conducive to the full consumption of new energy and the healthy development of the electricity market.
This paper presents a prediction-based method to generate load transfer strategy for intelligent distribution net-work.The method obtains section data of system operation from power distribution monitoring system.According to the primary model information and equipment operation status of the system,the topology structure of the system operation is calculated through the topology service to provide a basis for load transfer.System prediction results are obtained from the prediction system,topology and prediction results are input into the load transfer expert system,and the transfer strategy is calculated and generated according to the weight configuration of the transfer.The transfer strategy is stored in the da-tabase or displayed on the interface to provide decision-making basis for operators.
The voltage gain range in the over-resonant region of CLLLC resonant converter under pulse frequency modulation (PFM) at light load is insufficient. Phase shift modulation (PSM) can only realize the buck function, and the load switching perturbation has a large impact on the output voltage. In response to the above problem this paper proposes a variable frequency and phase-shift control method that can freely switch the control mode according to the input voltage range to achieve a wide voltage range soft switching and output voltage stability. The system model is acquired by the extended descriptive function method and reduced to the second order. The second-order linear active disturbance rejection control (LADRC) strategy is introduced to reduce the impact of the load casting perturbation on the output voltage and improve the dynamic performance of the system. Finally, the correctness of the theoretical analysis and the effectiveness of the control strategy are verified by PLECS simulation.
为提高电网安全运行的稳定性,减小风光等新能源发电不稳定性带来的波动对电网影响,增强电网抗事故的能力,对作为调峰调频扮演重要角色的火力发电机组提出了越来越严格的要求.为更好适应新时代电网发展的要求,对火力发电机组进行 AGC负荷快调和机组综合调频进行了改造.
In order to improve the correct judgment rate of fault diagnosis of oil -immersed power transformers, this paper proposes a fault diagnosis method using the combination of the relief feature weight method, HPO-SVM model, and dissolved gas analysis in oil (DGA). First, the method introduces the feature weight algorithm to filter and reduce the dimensionality of the input quantity; second, the probabilistic neural network model is optimized using the predator optimization algorithm, and the SVM model is used to process the DGA ratio set to finally obtain the fault diagnosis results of the transformer. The experiments show that the model with dimensionality reduction using the reliefF feature weight algorithm has higher diagnostic accuracy. The average fault judgment accuracy of HPO-SVM, GWO-SVM, WOA-SVM, and PSO-SVM is 94%, 91.33%, 90%, and 83.33%, respectively, and the average number of iterations is 6.5, 8.9, 12.5, and 15.1, respectively, and the simulation results show that the preferred hybrid feature model has higher correct diagnosis rate and faster convergence seeking speed The simulation results show that the superiority of this scheme is confirmed.
近几年新能源技术不断发展,光伏发电因具有绿色清洁、持续长久等优点得到了广泛应用,但同时其输出功率存在间歇性、随机性和突变性等特点,会对电网的稳定性带来负面影响,因此准确的功率预测对电网的稳定运行至关重要.随着人工智能的兴起,将深度学习网络技术与功率预测相结合,可得到高精度的预测结果.为此提出一种基于长短期记忆网络的深度学习方法,建立分时长短期记忆网络模型,从而实现了光伏发电功率的预测.该预测方法的推广应用为电网的稳定运行提供了可靠保证,有效提高了功率预测精度,具有很好的应用前景和现实的应用价值.
为了解决端子箱凝露问题,研制出一种能在低温自启动的微纳米驱潮装置.该装置以环氧树脂玻璃纤维为载体,高导电水性碳纳米电热涂料为发热主体,形成远红外线,模拟太阳光的自然辐射过程加热物体,持续提升端子箱内温度,使箱壁成为"隔热体",且辐射不断在箱内发生反射,有效防止发霉,彻底解决凝露问题.
面对大规模新能源并网带来的电力系统频率安全挑战,储能技术的发展为解决频率安全问题提供了解决方案.混合储能系统辅助火电机组参与调频可以有效改善电网调频性能,因此提出一种基于线性分解的混合储能调频控制策略,将频率偏差分解后得到高低频分量,飞轮储能和锂电池的功率指令由自适应虚拟下垂控制产生.仿真结果验证了所提策略的有效性,混合储能系统的参与在改善电力系统调频效果的同时可减缓火电机组的出力波动.
介绍一种适用于火电厂电气设备状态诊断的谐波诊断技术,主要包括电气设备状态信号采集和预处理、谐波故障诊断系统设计两部分内容.其中,电气设备状态信号采集和预处理主要采用改进小波预制信号去噪方法,可有效提高信号采集和预处理效果;谐波故障诊断系统则基于电气设备状态信号采集和预处理,合理介绍系统基本组成结构,并重点说明高次谐波诊断数据样本、劣化诊断判定算法、设备异常及劣化判定标准三部分系统内容.为检验谐波诊断系统在火电厂电气设备状态诊断中的应用成效,将该系统应用于工程实践,最终确认该系统具有较高的诊断精准性.
基于三菱FX5U PLC和 RS-485 通信的 2 条流水线联合控制系统,其设计包括 PLC输入/输出端口分配、电气控制线路设计、RS-485 通信参数设置以及基于软元件链接和链接时间延迟的主从站程序设计等.经仿真调试和联机运行,该系统能够实现 2 条流水线启停和产品自动计数的联合控制,各流水线还可独立工作,系统功能完善、抗干扰性好、容错性好、RS-485 通信简便稳定.该系统不仅能够用于工业企业多条流水线控制优化和提高生产效率,还可作为典型案例用于本专科大学生和社会相关专业技术人员学习FX5U PLC的应用.
为解决大规模风电并网带来的频率不稳定问题,提出风储联合调频的控制策略.双馈风力发电机组的调频能力受风速的影响较大,无法满足调频需求.利用储能响应速度快、可控性高等特点弥补风电机组自身调频的不足.当系统出现频率波动时,通过优化虚拟惯性控制来调节风电机组的输出功率.在 MATLAB/Simulink仿真平台上开展的风电不调频、风电调频和风储联合调频下电力系统频率特性的对比分析表明,风储联合能显著提高电力系统频率的稳定性.
高压开关柜手车开关操作需要使用摇把,传统的手动摇把操作费时费力,容易拖落和缠绕绝缘手套,并且具有专用性.设计一种电动摇把,由电机带动转接头,稳定性较好,可实现通用性.通过设置转动圈数,该电动摇把还能实现手车开关到位自锁.
风电机组状态监测数据具有量大、多源、异构、复杂、增长迅速的特点,但当前处理大数据的过程中所使用的诊断方法和预警方法存在一定缺点,难以保证其精度.为了确保处理数据时能够及时了解风电机组的具体情况,分析了风电机组运行状态评估和故障诊断中的分析技术,相关实验表明,这一故障诊断以及预测方法优势显著,且具有一定的可行性.
超级电容器是一类新型的电化学能量存储器,具有功率密度高、充放电速度快和寿命长等优势.探究碳基锂离子超级电容器负极预嵌锂方法,通过对以炭为主要原料的负极材料实施一系列处理工艺,可得到预嵌锂炭材料.通过对预嵌锂炭材料的物理性能、电化学性能以及电容性能的测试,证明了该预嵌锂方法可显著提高超级电容器的能量密度、功率密度和循环稳定性.此外,还探讨了该预嵌锂方法的机理,并对其可能的应用前景进行了展望,对碳基锂离子超级电容器的开发和应用具有重要的理论和实际意义.
为提高智能小区风光储充一体化电站投资收益,进而促进电站社会效益和经济效益的最大化,开展智能小区风光储充一体化电站容量优化方法研究.根据智能小区实际充电负荷和风电、光伏波动数据,估算智能小区风光储充一体化电站储能需求电量.将电站年运行成本最小化作为目标,建立风光储充一体化电站容量配置优化目标函数.结合改进后的差分进化入侵杂草算法,实现电站容量优化配置.依托某智能小区项目,通过实例验证优化方法应用后,电站投资收益显著提升,对于实现电站综合效益最大化具有极大帮助.
针对现有技术中新能源电网评估不足和能源调配不合理问题,通过设计"主干网"和"局域网",将主干网或者微网设计成分布式能源互联网网络架构,使分布式能源以开放对等的形式构成信息能源一体化系统.研究还实现了分布式能源互联网双向按需传输和动态平衡使用,从而能够将不同形式的新能源有序接入、转换和应用;设计了配电数据信息融合算法模型,提高了配电网资产运行效率;通过基于灰色 GM(1,1)模型的电网高弹性分析方法,实现了多种不同能源互联网架构的数据分析与计算.试验表明,所提方法数据融合能力强,评估误差率低.
近年居民、工商业用户的非介入负荷识别技术和工程应用场景呈井喷式发展态势,而针对负荷辨识设备的检测技术研究却鲜有关注.针对智能物联电表的非介入负荷识别模组批量化测试场景进行测试平台的研究设计.首先介绍了基于COMTRADE文件的典型用电工况的数字描述方法,并针对多通道输出波形同步性难题,提出了基于同步激励控制方法的数字波形同步回放技术;然后重点进行了测试平台的设计,在整体框架设计基础之上,详细设计了下位机硬件测试单元和上位机测试软件的功能,并进行了完整的测试平台软件的控制流程设计;最后通过实验测试验证了该测试平台的性能,数字波形输出具有较高的稳定度,通道偏差小于(100±10)μs/p(包),数字波形的输出错包率小于 0.01‰,保证了数据输出的稳定性,可加载多种模式的负荷数字波形满足多场景检测需求,极大地提高了负荷识别模组的检测效率.
