Development of a real-time power system dynamic performancemonitoring system

Power systems have grown in both size and complexity, and the dynamic characteristics of the systems vary, as well. A computer simulation revealed the possibility of low-frequency oscillation after the connection of a cogeneration plant to the utility grid. Though there are several possible methods to improve the dynamic stability performance of the system, a thorough understanding of the system characteristics and possible operating conditions is required before an appropriate measure can be proposed. In order to collect more operating information without affecting normal system operation, a programmable logic controller (PLC)-based dynamic performance monitoring system (DPMS) was designed and installed at the tie substation. The recorded information will be valuable for system analysis and/or power system stabilizer (PSS) design. The DPMS design, its laboratory testing results, and several field-operation records are discussed in this paper     

Effects of various power system stabilizers on improving power system dynamic performance

To ensure the small-signal stability of a power system, power system stabilizers (PSSs) are extensively applied for damping low frequency power oscillations through modulating the excitation supplied to synchronous machines, and increasing interest has been focused on developing different PSS schemes to tackle the threat of damping oscillations to power system stability. This paper examines four different PSS models and investigates their performances on damping power system dynamics using both small-signal eigenvalue analysis and large-signal dynamic simulations. The four kinds of PSSs examined include the Conventional PSS (CPSS), Single Neuron based PSS (SNPSS), Adaptive PSS (APSS) and Multi-band PSS (MBPSS). A steep descent parameter optimization algorithm is employed to seek the optimal PSS design parameters. To evaluate the effects of these PSSs on improving power system dynamic behaviors, case studies are carried out on an 8-unit 24-bus power system through both small-signal eigenvalue analysis and large-signal time-domain simulations.     

Multiple time-scale power system dynamic simulation

A new program, EXSTAB (extended time-scale stability) has been developed for representing a wide variety of power system performance problems, from transient stability through long-term dynamics and voltage instability. The capability of the program includes multiple execution modes and automatic step size selection to address conflicting goals of accuracy and efficiency. The modeling includes a broad range of apparatus to provide the needed time-scale representation (four orders of magnitude). Models for automatic generation control, plant characteristics and control, voltage and reactive power control, static and dynamic loads, and protective relaying for apparatus and system connections are provided. Technologies were developed to perform analysis of voltage stability and prediction of peak power transfer to avoid voltage collapse     

电力电子变压器在改善电力系统动态特性中的应用

依据电力电子变压器PET(Power Electronic Transfomer)的功率特性,提出了一种利用PET改善电力系统动态特性的新方法。PET副方接入输电线路。原方接无穷大系统,这时PET等效为一个可控电压源．建立发电机励磁和PET所构成电力系统的数学模型,分别以发电机功角、角速度、机端电压为状态变量,以发电机励磁电压、可控电压源的幅值和相角为控制变量。在此基础上推导了PET和发电机励磁的最优协调控制规律。仿真分析发现。通过PET与系统间功率的迅速交换和双向流动．提高了系统阻尼,有效抑制了扰动下的系统振荡。     

动平衡测试系统中不平衡量的测试方法研究

针对动平衡测试系统中不平衡量测试精度较低的问题,提出了一种基于希尔伯特黄变换(HHT)的滤波方法,该方法应用于动平衡测试系统,对获取的转子原始振动信号和转频信号进行分析,可以有效得到不平衡量的质量和相位.方法先对原始振动信号进行经验模态分解(EMD),将振动信号分解为一系列固有模态函数(IMF),再经过希尔伯特(Hilbert)变换计算出各IMF的希尔伯特边际谱,根据转子转频信号滤除掉高低频干扰信号,筛选出针对不平衡量的有效振动信号,根据该信号的幅度和频率即可得到不平衡量的质量和相位.与普通数字滤波方法比较,实验结果表明,该方法用于动平衡测试系统比普通数字滤波方法精度高,效果好.     

Monitoring power system dynamic stability with a kohonen neural net

This paper presents a method for monitoring the dynamic stability of power systems using a Kohonen-type neural network. The QR factorization algorithm is widely used in eigenvalue calculations for power system dynamic stability studies, due to its numerical stability. However, the method has the drawback that the computational requirements increase as the cube of the problem size. The S-matrix method is therefore attractive, because it focuses on the most critical eigenvalue. However, this method is difficult to use in numerical calculations. The method proposed here makes use of a mapping of the eigenvalues that allows us to regard the absolute value of the most critical eigenvalue as a quantitative dynamic stability index. In this paper, a Kohonen-type neural network is used to estimate the index. The neural network has the following advantages: (1) it uses a simple algorithm which requires no training signal, (2) it effectively classifies the input data, and (3) it presents at the outputs a two-dimensional mapping of the input data which makes it easy to visually comprehend their classification.     

计及风力发电风险的电力系统多目标动态优化调度

为解决风电的随机性给电力系统调度带来的问题,引入负荷预测误差和风速的概率分布函数来建立负荷及风电功率的随机性模型。基于对负荷及风电功率随机性模型的深入分析,对风电接入将导致系统维持稳定运行的成本增加风险加以考虑。并在约束条件中引入失负荷及风电浪费风险指标,构建计及风力发电风险的电力系统多目标优化调度模型,以实现系统总污染排放量最少和运行成本最低的综合优化目标。采用一种新颖的蝙蝠算法对模型进行求解,并对蝙蝠算法的不足之处进行了改进,有效地解决了该算法迭代后期收敛慢、易陷入局部极值等问题。以含大规模风电并网电力系统为例进行环境经济调度仿真,验证了所提模型及算法的有效性,并进一步分析了相关参数对含风电并网电力系统优化调度的影响。     

分布式电源并网动态无功优化调度的研究

根据分布式电源并网的控制特性,将分布式电源设计为电压控制型和无功补偿型,考虑其与地区电网的电压无功控制手段相结合,参与地区电网动态无功优化调度。建立以降低地区电网网损、抑制电压波动为综合目标的地区电网模糊动态无功优化调度模型。在该模型中,通过构造模糊评价函数,将目标函数转化为对优化结果的满意度,并利用自适应权重法将综合目标进行归一化处理。最后采用改进遗传算法有效求解含分布式电源的地区电网动态无功优化调度策略。算例表明,提出的模型和方法是合理的,具有一定参考价值。     

利用国内某些微机继电保护装置实现电力系统的振荡模拟

在一个并列运行的系统和发电厂的运行中,可能失去同步,考验保护在振荡过程中的动作情况是必要的.介绍了如何利用微机测试仪模拟系统振荡,来检查保护的动作情况.     

利用国内某些微机继电保护装置实现电力系统的振荡模拟

在一个并列运行的系统和发电厂的运行中 ,可能失去同步 ,考验保护在振荡过程中的动作情况是必要的。介绍了如何利用微机测试仪模拟系统振荡 ,来检查保护的动作情况。     

电动汽车用动力电池性能检测系统

电动汽车用动力电池性能检测系统以AT 89C 5 2系列单片机作为系统的控制核心 ,采用电子逆变技术 ,由IGBT构成恒流充电电路及VMOS管并联方式组成恒流放电电路 ,以达到节能 ,减小体积 ,降低功耗的目的。系统集电池电压采样、数据处理、充放电控制、数据及曲线打印、键盘显示于一体 ,不需上位微机即可完成全部检测。充放电过程既可自动控制 ,也可手动控制。经实际应用证明 ,本系统性能稳定、实用性强 ,节能效果明显 ,充放电电流可达到 5 0 0A ,满足了电动汽车用大容量动力电池及电池组的充放电性能检测、容量和能量测量及寿命实验 ,解决了电动汽车用动力电池检测的难题。     

动力电池数字化测试系统--DSP在电池检测中的应用

介绍了一种动力电池数字化测试设备的软硬件设计。该系统以TMS320LF2407DSP作为核心处理器,采用主从式结构设计方法,用FPGA配合DSP实现了数字化PWM输出电流调节,可对动力电池恒电流充放电过程中的电池电压、电流、容量、-驻V进行实时监控。实际测试结果表明,系统的可靠性好、检测精度高、响应速度快、使用方便,能很好的满足动力电池测试的各种要求,适合于大规模动力电池的化成与检测。     

电力系统频率动态与功角振荡的耦合特性分析

为探究频率动态与功角振荡间的耦合特性,文中以双机系统为例推导扰动后系统稳定电网频率动态特性和功角振荡机理,基于扩展等面积准则(extended equal area criterion,EEAC)扩展至多机系统,提出了基于Pearson系数的耦合强度量化评估指标,根据频率动态特征和功角振荡特征对耦合关系进行量化。文中分析了功角振荡对频率动态特征指标的影响,量化评估了不同频率动态指标与功角振荡指标的耦合强度。理论分析和算例结果表明构建的指标体系具有合理性,电力系统的频率动态与功角振荡相互耦合,为频率和功角的优化控制措施提供了参考。     

电动汽车用动力电池组性能测试系统

介绍了新研制的电动汽车动力电池组性能测试系统。该系统以工业控制计算机为核心,采用全桥逆变器作为充电器主电路,Cuk变换器作为放电器主电路,可根据多种控制时序自动完成充放电过程。另外该系统还具有实时采集与显示数据、数据自动保存及处理、数据及曲线打印等多项功能,并可用于电动汽车动力电池实际运行状况的模拟。大量试验证明,该系统性能稳定,测试结果准确,完全可用于电动汽车动力电池组的性能测试。     

电力系统频率动态过程研究综述

介绍了研究电力系统频率动态过程现有的研究手段、数值仿真方法和基于实测轨迹研究方法。在基于实测轨迹研究电力系统频率动态过程方面,概括了时空分布特性、量化描述、校正仿真模型参数及其对低频减载的影响四个研究方向,阐述各方向研究目的及现有国内外研究成果,并讨论大规模风电并网对频率动态过程的影响。针对电力系统频率动态过程这一课题提出研究展望,为该方向进一步研究提供理论依据。     

Sensitivity analysis in power system dynamic stability studies

The stability limits for power systems can be defined by curves on the capability chart. In this paper the sensitivity of these curves versus system parameter perturbations is considered. The results also look interesting from a practical point of view, since a more realistic and efficient margin for stability can be defined. On this basis, the margin variations due to parameter perturbations are determined. Finally, a useful criterion is introduced to determine globally the influence of the parameter perturbations on the dynamic behaviour of the system.     

Modeling of a large electric power system for optimal control of dynamic stability

This paper describes a general state-variable form of mathematical modeling which may be used to control the dynamic stability of a larger power system optimally. Based on the linearization about the operating point of the system, a complete model for dynamic stability control is obtained by combining transmission network equations, full-order synchronous machine equations, the exciter and voltage regulator model, torque equations, and the governor-hydraulic model in a matrix form which includes supplementary excitation and governor control signals. The complete model may then be simplified as a low-order model by neglecting the governor effects, exciter time constant, and all but the field flux linkage variations of the machines in order to reduce computational requirements.