Three-Phase Unbalance Prediction of Electric Power Based on Hierarchical Temporal Memory

The difference in electricity and power usage time leads to an unbalanced current among the three phases in the power grid.The three-phase unbalanced is closely related to power planning and load distribution.When the unbalance occurs,the safe operation of the electrical equipment will be seriously jeopardized.This paper proposes a Hierarchical Temporal Memory(HTM)-based three-phase unbalance prediction model consisted by the encoder for binary coding,the spatial pooler for frequency pattern learning,the temporal pooler for pattern sequence learning,and the sparse distributed representations classifier for unbalance prediction.Following the feasibility of spatial-temporal streaming data analysis,we adopted this brain-liked neural network to a real-time prediction for power load.We applied the model in five cities(Tangshan,Langfang,Qinhuangdao,Chengde,Zhangjiakou)of north China.We experimented with the proposed model and Long Short-term Memory(LSTM)model and analyzed the predict results and real currents.The results show that the predictions conform to the reality;compared to LSTM,the HTM-based prediction model shows enhanced accuracy and stability.The prediction model could serve for the overload warning and the load planning to provide high-quality power grid operation.

Research of Three-Phase Unbalanced Treatment in Low-Voltage Distribution Network Based on New Commutation Switch

Low-voltage distribution systems in our country are mostly used in agricultural loads and household loads. The value and using time of these kinds of loads are uncontrollable, which lead to the three-phase imbalance in low-voltage distribution system, and seriously affect the quality of power supply. A new type of the commutation system and an improved quantum genetic algorithm (IQGA) are proposed in the paper. At last, the rationality and the efficiency of the method are verified by a practical example.

Influence of Unbalance on Classification Accuracy of Tyre Pressure Monitoring System Using Vibration Signals

Tyre Pressure Monitoring Systems(TPMS)are installed in automobiles to monitor the pressure of the tyres.Tyre pressure is an important parameter for the comfort of the travelers and the safety of the passengers.Many methods have been researched and reported for TPMS.Amongst them,vibration-based indirect TPMS using machine learning techniques are the recent ones.The literature reported the results for a perfectly balanced wheel.However,if there is a small unbalance,which is very common in automobile wheels,‘What will be the effect on the classification accuracy?’is the question on hand.This paper attempts to study the effect of unbalance of the wheel on the classification accuracy of an indirect TPMS system.The tyres filled with air are considered with different pressure values to represent puncture,normal,under pressure and overpressure conditions.The vibration signals of each condition were acquired and processed using machine learning techniques.The procedure is carried out with perfectly balanced wheels and known unbalanced wheels.The results are compared and presented.

Sensorless Monitoring of a Motor-Drive Machanical System Based on Adaptive Signal Decomposition

A method for estimating current harmonics of an induction motor is introduced which is used for sensorless monitoring of a mechanical system driven by the motor. The method is based on an adaptive signal representation and is proposed to extract weak harmonics from a noisy current signal, especially in the presence of additive interference caused by transient modulation waves. As an application, a rotor unbalance experiment of rotating machinery driven by an induction motor is carried out, The result shows that the eccentricity harmonic magnitude of a current signal obtained by the method represents the rotor unbalance conditions sensitively. Vibration analysis is used to validate the proposed method.

Three-Phase Optimal Power Flow for Study of PV Plant Distributed Impact on Distribution Systems

This paper presents a TOPF （three-phase optimal power flow） model that represents photovoltaic systems. The PV plant is modeled in the TOPF as active and reactive power source. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. The reduction of unbalance voltage and losses in the distribution systems is obtained by actions of reactive power control of the inverter. The TOPF is formulated by current balance equations and the PV systems are modeled via an equivalent circuit. The primal-dual interior point method is used to obtain the optimal operating points for the systems for different scenarios of solar irradiance and temperature, thus providing a detailed view of the impact of photovoltaic distributed generation.

Online Unbalance Detection and Diagnosis on Large Flexible Rotors by SVR and ANN trained by Dynamic Multibody Simulations

Multiple-stage steam turbine generators,like those found in nuclear power plants,pose special challenges with regards to mechanical unbalance diagnosis.Several factors contribute to a complex vibrational response,which can lead to incorrect assessments if traditional condition monitoring strategies are used without considering the mechanical system as a whole.This,in turn,can lead to prolonged machinery downtime.Several machine learning techniques can be used to integrally correlate mechanical unbalance along the shaft with transducer signals from rotor bearings.Unfortunately,this type of machinery has scarce data regarding faulty behavior.However,a variety of fault conditions can be simulated in order to generate these data using computational models to simulate the dynamic response of individual machines.In the present work,a multibody model of a 640MWsteam turbine flexible rotor is employed to simulate mechanical unbalance in several positions along the shaft.Synchronous components of the resulting vibration signals at each bearing are obtained and utilized as training data for two regression models designed for mechanical unbalance diagnosis.The first approach uses an artificial neural network and the second one utilizes a support vector regression algorithm.In order to test their performance,the stiffness of each bearing in the multibody simulation was altered between 50%and 150%of the training model values,random noise was added to the signal and several dynamic unbalance conditions were simulated.Results show that both approaches can reliably diagnose dynamic rotor unbalance even when there is a typical degree of uncertainty in bearing stiffness values.

Control strategy for microgrid under three-phase unbalance condition

Microgrid(MG) is generally developed at utility terminal which contains lots of unbalanced loads and distributed generations(DGs). The interaction between MG and the unbalance loads or DGs will degrades the control performance of interfaced inverter in MG and dramatically leads to MG voltage unbalance. In this paper, a negative-sequence compensation based three-phase voltage unified correction strategy is proposed. While MG operates in islanded mode, a positive virtual impedance control is used to eliminate the negative voltage resulted from the negative-sequence current,and then a positive-sequence voltage control loop and negative-sequence control loop are used to improve the inverter control performance. While MG operates in grid-tied mode,the inverter operates as a negative-sequence current source to compensate the negative-sequence currents of loads to guarantee the point of common coupling(PCC) voltage balance.By using the proposed strategy, the voltage control performance of inverter can be improved;the MG power quality can be enhanced significantly. Simulation and experimental results verify the effectiveness of the proposed method.

Optimal Planning of Hybrid AC/DC Low-voltage Distribution Networks Considering DC Conversion of Three-phase Four-wire Low-voltage AC Systems

The increasing integration of distributed household photovoltaics(PVs)and electric vehicles(EVs)may further ag gravate voltage violations and unbalance of low-voltage distribu tion networks(LVDNs).DC distribution networks can increase the accommodation of PVs and EVs and mitigate mutilple pow er quality problems by the flexible power regulation capability of voltage source converters.This paper proposes schemes to es tablish hybrid AC/DC LVDNs considering the conversion of the existing three-phase four-wire low-voltage AC systems to DC op eration.The characteristics and DC conversion constraints of typical LVDNs are analyzed.In addition,converter configura tions for typical LVDNs are proposed based on the three-phase four-wire characteristics and quantitative analysis of various DC configurations.Moreover,an optimal planning method of hybrid AC/DC LVDNs is proposed,which is modeled as a bi-level programming model considering the annual investments and three-phase unbalance.Simulations are conducted to verify the effectiveness of the proposed optimal planning method.Sim ulation results show that the proposed optimal planning method can increase the integration of PVs while simultaneously reduc ing issues related to voltage violation and unbalance.

变压器谐波损耗计算及影响因素分析

为了准确分析配电网谐波对变压器损耗的影响,依据电路理论建立了变压器谐波损耗模型,推导出变压器谐波损耗的计算关系式。针对谐波次数和变压器负载不平衡引起的谐波损耗进行了分析,提出了变压器谐波损耗在线监测方法,并通过实验对该方法的有效性进行了分析。分析结果表明:建立的变压器谐波损耗模型一方面由于不需要考虑变压器一次侧谐波电流,简化了计算复杂程度;另一方面能够准确计算出变压器的各次谐波引起的变压器损耗。基于配电网3次与5次谐波引起的变压器损耗占变压器总谐波损耗的90%以上,有效降低配电网3次与5次谐波对于变压器的降损节能具有很好的工程实用价值。

接地极线路不平衡保护的相关问题研究

天广、兴安直流在运行中已多次出现接地极线路电流不平衡保护动作,而且接地极线路故障监视装置没有启动。从接地极线路不平衡保护的原理以及整定原则角度分析了保护的动作情况,及接地极线路故障监视装置在运行中存在的不足之处,提出了改进接地极线路不平衡保护的原理、加强接地极线路保护与接地极线路故障监视装置之间的参数配合等方案以改善目前的运行状况。

一种优化的光伏电站直流系统绝缘在线监测装置设计

光伏电站直流母线对地绝缘故障将会对设备运行和人员安全造成严重影响,对直流系统绝缘性能进行在线监测,是防止事故发生和蔓延的有效途径。比较了常用的几种绝缘在线监测原理,选择了不平衡电桥和平衡电桥相结合的方法进行原理设计,并从工程应用的角度对传统的监测方法进行了优化改进。有效防止了投切开关故障击穿时引起正负直流母线短路的问题。对所设计的光伏电站直流母线对地绝缘监测装置的测量原理,以及硬件电路设计、软件实现流程等进行了详细说明,并通过试验验证了装置的测量精度和绝缘耐压性能。

基于无线负控信道的电能质量管理系统

本文探讨了一种在原有的负荷管理系统平台上增加电能质量监测功能的方法。通过对远程终端硬件的改造和原有系统软件的升级 ,在配电网中增加了谐波、电压、三相不平衡的监测和管理 ,保证了电能质量。在软件中采取了数据仓库技术 ,提高了数据操作的响应速度。

电网相序和缺相监测电路的设计

文章论述了电网相序变化的原因及其造成的影响，提供了实用的相序监测电路，分析了相序监测原理。

电磁动力吸振器式转子在线监测方法研究

电磁动力吸振器具有重大的工程应用价值。在给出转子+电磁动力吸振器系统模型的基础上,采用输出调节器理论,设计了电磁动力吸振器控制系统,实现了控制系统的主要目标:在指定的多个频率位置,将转子的不平衡响应减为零,而在其余较宽的频率范围内,抑制了不平衡响应的水平,使之处于非共振量级。因此,用电磁动力吸振器可实现对转子振动的在线控制。在此基础上,因为在电磁动力吸振器控制系统的设计中,构造了反映不平衡力的状态量及其观测器,所以还可以利用状态观测器获得转子的不平衡信息,实现不平衡量的识别,从而给出了用电磁动力吸振器进行不平衡识别的方法。该方法的提出,有益于在线监测转子的不平衡状态、及时诊断故障以及无试转的平衡。

基于谐波阻抗的感应电机系统无传感器监测方法研究

从信号处理的观点出发 ,结合阻抗理论和谐波分析 ,提出了感应电机系统无传感器监测的谐波阻抗和谐波导纳法 ,给出了获取和计算谐波阻抗和谐波导纳的方法。在鼠笼式三相感应电机上用提出的方法进行了转子失衡的实验研究。实验结果证实了方法的可行性 。

关于低压配电网系统三相不平衡度监测的研究

为了建立对低压配电网系统的三相不平衡度的综合监控技术,改善电网运行质量,文中提出一种适配于低压配电网系统的三相不平衡度监测装置,包括采样电路、控制系统、换相开关、电容器组、执行机构。通过对三相电力参数的采样分析,合理调配三相负载并动态投切电容器组,始终使三相负荷趋近平衡并在故障时切断电源与负载之间的联结。该三相不平衡度监测装置可以减少因三相不平衡度异常对低压电网与用电设备的不良影响,降低线路与变压器的电能损耗,提高变压器效率。

基于固态智能换相开关的三相负荷不平衡解决方案研究

针对低压配电网三相负荷不平衡的现状和常规解决方案,提出了基于固态智能换相开关的新解决方案。设计了固态智能换相开关的拓扑结构、工作模式和控制方法,完成了低压配电网智能换相监控系统,同时进行了MATLAB仿真,并建立了低压配电网系统模型。仿真结果表明,所提出的方案在解决三相负荷不平衡、改善低电压、提高供电质量方面具有可行性。

状态监测技术在尾气压缩机检维修中的应用

苯乙烯尾气压缩机因减速箱振动高报联锁停机,经过多次检修,故障依然未消除。通过使用system 1在线监测系统,从力不平衡,偶不平衡、动不平衡和装配尺寸四个方面对振动图谱进行分析。根据振动轴心轨迹图反映出的振动特点,最终诊断出减速箱振动高报联锁停机的原因是动不平衡故障。经过现场重新制定检修方案,在线和离线动平衡合格后开机运行正常,故障得到解决。

船载特装设备电能质量监测系统设计与实现

针对测量船特装设备供电系统可能受到短路、断路、漏电、谐波等因素的干扰而影响供电的电能质量问题,构建和实现了一种基于智能网络仪表的电能质量监测系统;该系统实现了对电能质量的在线监测以及采集数据的分析和处理,可准确、实时、连续地对供电系统的电能质量数据进行监测,以获取多方面的电能质量数据;同时实现了电能数据的信息共享,提高了电能数据资源的利用率,为电能质量监测数据进一步分析提供了有力支撑;电能质量监测系统投入运行后,实践结果表明,该系统具有较好的监测效果。

新型电容保护的形制与整定

通过对新型电容保护与现有继电保护在技术特性方面的比较,引得"研发新型保护是技术进步的必然,从低端技术到智能化技术发展之必需"的见解;通过对新型保护的形制与整定的深入研讨,推出与电容器组基本接线方式相对应的单星形相电容、单星形段电容(串联段数为2段及以上者)、双星形臂电容和单星形桥差臂电容等4种保护型式;推出以保护配合整定原则,求导电容量变化率的允许值作为故障判据的理念,及其保护整定算式符合工程便捷实用与安全可靠的要求。