A dynamic state estimator for power system dynamic security assessment

A global modularized dynamic state estimator is formulated to provide the data which will be required for future dynamic security assessment and dynamic security enhancement applications. The dynamic state estimator is global because it is capable of estimating small and large dynamic fluctuations in voltage angle and frequency for an entire area. The dynamic state estimator is composed of the sum of the static state estimate, obtained by using present hardware and algorithms and a modularized dynamic state estimate based on a linearized classical transient stability model with a stochastic load model. This dynamic state estimate component is modularized to (1) eliminate the need to measure or model external system generation and (2) to permit a reduction in computation requirements for (a) updating the linearized power system dynamic model and (b) for computing the state estimate. The modularization, which is accomplished by decoupling the linearized dynamic model for each subregion by measuring the power injections on lines connecting the subregion to the rest of the power system, causes the dynamic state estimate to be locally referenced. A global referencing procedure is proposed and discussed. A linearized stochastic model for the Michigan Electric Coordinated System is developed to illustrate the procedures proposed for developing the stochastic load model and determining the constant gain approximation for the governor turbine energy system dynamics. A summary of results on the performance of the Kalman state estimator is presented.     

动态系统的一致同余安全

研究动态系统的安全问题．针对动态系统运行时间配置的可变特性，引入了动态系统的进程代数模型和复杂动态系统概念，定义了动态系统的一致安全性质和一致同余安全性质．基于观察同余等价，构造了一类一致同余安全模型．本文证明，动态系统的安全性质是一致安全性质，而对于复杂动态系统，其安全性质是一致同余安全性质．     

模型指导的多维GPU软件低功耗优化方法

作为众核体系结构的典型代表,GPU(Graphics Processing Units)芯片集成了大量并行处理核心,其功耗开销也在随之增大,逐渐成为计算机系统中功耗开销最大的组成部分之一,而软件低功耗优化技术是降低芯片功耗的有效方法.文中提出了一种模型指导的多维低功耗优化技术,通过结合动态电压/频率调节和动态核心关闭技术,在不影响性能的情况下降低GPU功耗.首先,针对GPU多线程执行模型的特点,建立了访存受限程序的功耗优化模型;然后,基于该模型,分别分析了动态电压/频率调节和动态核心关闭技术对程序执行时间和能量消耗的影响,进而将功耗优化问题归纳为一般整数规划问题;最后,通过对9个典型GPU程序的评测以及与已有方法的对比分析,验证了该文提出的低功耗优化技术可以在不影响性能的情况下有效降低芯片功耗.     

On the phase portrait of a class of large nonlinear dynamic systemssuch as the power system

Complete results are presented on the phase portrait of a class of large nonlinear dynamic systems that includes the power system. The connection between the constant energy surface and the stability boundary of the power system is explored. This gives valuable insight into classical stability tests, which are based on the constant energy surface. An approach to stability monitoring of the power system derived from these results is outlined     

一种防火墙系统安全模型的形式描述

文中提出了一种防火墙系统的安全模型，该模型构筑在防火墙系统的安全服务基础之上，将安全模型抽象为若干安全服务的集合并用形式化的方法进行了描述，着重描述了安全服务的动态特性，安全模型的动态特性以及安全模型和防火墙系统之间的相互关系，提出了安全服务的双向性及关键服务集的概念，该模型在已实现的分布式动态防火墙原型系统中得到了验证。     

Combined use of supervised and unsupervised learning for power system dynamic security mapping

This paper proposes a new methodology which combines supervised and unsupervised learning for evaluating power system dynamic security. Based on the concept of stability margin, pre-fault power system conditions are assigned to the output neurons on the two-dimensional grid with the growing hierarchical self-organizing map technique (GHSOM) via supervised artificial neural networks (ANNs) which perform an estimation of post-fault power system state. The technique estimates the dynamic stability index that corresponds to the most critical value of synchronizing and damping torques of multimachine power systems. ANN-based pattern recognition is carried out with the growing hierarchical self-organizing feature mapping in order to provide adaptive neural network architecture during its unsupervised training process. Numerical tests, carried out on a IEEE 9 bus power system are presented and discussed. The analysis using such method provides accurate results and improves the effectiveness of system security evaluation.     

Machine learning for frequency estimation of power systems

In this paper the application of machine learning techniques for on-line dynamic security assessment of power systems is presented. Decision trees (DT), artificial neural networks (ANN) and entropy networks (EN) are developed and applied on the power system of Crete, the largest Greek island. Comparison of these methods reveals their relative advantages and disadvantages. These methods have been integrated in the dynamic security assessment module of the advanced control system of Crete island, helping to identify the operating conditions and parameters that lead to a less robust operation of the system. The results are considered very satisfactory, both in accuracy that increases the reliability of the method and in computational time, which is a necessity for real time applications.     

流程工业能耗系统多维子模型及其开放性集成框架

流程工业组成因素多,运行结构复杂,针对单一模型无法合理、全面地描述其能源消耗系统各因素及其关联关系的问题,提出了流程工业能耗系统多维子模型及其集成化构建方法。首先,综合设备、能量、信息、人员等多方面因素,从静态结构描述、能源消耗的动态行为以及企业能耗系统运作的目的性3个层面建立流程工业能耗系统多维子模型;然后,分析了不同视角子模型关联关系;最后,详细研究了能耗系统多维模型的开放性集成框架,从而为流程工业能耗系统建立集信息流、能源流和物料流为一体,并同时反映内、外部关键因素的多维集成化模型提供了方法支持。这种内外关联、高度集成的流程工业能耗系统模型的构建将为流程工业综合性能效评估奠定基础。     

面向工作流应用的可组合授权模型

针对分布式工作流系统授权管理的动态性、统一性和自治性的特点,将RBAC的授权管理思想和TBAC的动态访问机制结合起来,提出了支持工作流组合和动态授权控制的可组合授权模型。该模型提供了从工作流的组成结构和执行关系进行建模的方法,通过将各个处理单元的授权方案按照工作流的组合结构、执行依赖关系和主体依赖关系进行组合,从而构造适应更复杂的工作流系统的授权方案。对模型的定义和组合运算进行了形式化描述,给出了模型的表达能力和一致性、组合运算的兼容性和安全性的相关性质分析。最后介绍了支持动态授权的授权控制引擎原型。     

Comparison of microprocessor systems for real-time phasor measurements for large-scale power systems: a case study

Recent progress in microprocessor-based relaying systems and the technology involved in the new measurement systems for assessment of on-line dynamic security of electric power systems are described. The technique of obtaining the measurements from selected locations on interconnected electric power systems is presented. The measurements require a number of algorithms that have been developed. A comparison of the different approaches has also been conducted using a realistic system for confirmation of the developed technique.     

Improved linear model of self oscillating systems such as relay feedback current controllers

In this paper, some analytical tools for the study of self-oscillating systems such as current-controlled static converters using pulse-width modulators are presented. These tools, based on the Tsypkin locus, concern the prediction of the switching frequency of the power stage and the characterization of its input–output behavior by an equivalent linear model. These first results, that can be used for any value of the duty cycle, are extended to the construction of the frequency response of the closed-loop system, where the power stage is replaced by a constant gain, associated with a constant time delay. This study is validated by experiments using a classical hysteresis current controller and a recent current controller without hysteresis. The obtained results are particularly useful for applications such as active filtering or high precision power supplies, where the frequency of the signal to follow can be close to one fifth of the switching frequency.     

基于多维标识的文件分级保护模型

针对传统文件保护技术中普遍存在的分级管理差、管控粒度不细等问题,结合多维多密级的文件应用环境,提出基于多维标识的文件分级保护模型.该模型将静态特征标识和动态密级标识相结合,引入域标识的概念,并证明其安全性.经分析和应用表明,该模型能在不影响文件正常使用的基础上,使不同环境中的文件访问都能得到有效控制,从而保证文件的安全...     

Non-linear smoothing algorithm for multi-dimensional dynamic systems

A new sub-optimum smoothing algorithm is presented for multi-dimensional dynamic systems. This algorithm is based upon quantization, multiple hypothesis testing, and the Viterbi decoding algorithm. The estimation of state vectors is carried out sequentially, component-by-component, and in parallel. A considerable memory reduction is achieved for state estimation implementation with the proposed algorithm. Simulation results, some of which are presented, show that the sub-optimum algorithm performs better than the extended Kalman filter algorithm for some non-linear multi-dimensional models with white gaussian disturbance and observation noises. In addition, the performance of the sub-optimum algorithm is almost as good as the Kalman filter algorithm for linear multi-dimensional models with white gaussian noise.     

工业信息物理系统安全风险动态表现分析量化评估模型

针对当前工业信息物理系统的安全风险评估模型极少考虑系统的动态进程对评估准确性的影响,给出一种工业信息物理系统安全风险动态表现分析量化评估模型.首先,运用贝叶斯网络对攻击在网络层的入侵过程建模,计算网络攻击成功入侵的概率;然后,在攻击成功入侵的前提下,采用卡尔曼状态观测器实时观测被控对象的状态,研究系统的动态表现,定量分析系统的表现损失,从经济损失的角度量化攻击对系统造成的影响,并结合攻击成功入侵的概率,实现对系统安全风险的动态评估.最后,通过Matlab对攻击下沸水发电厂模型的运行状态进行仿真,结果表明所提模型能有效地评估工业信息物理系统的风险.     

面向电力系统网络安全的多层协同防御模型研究

为满足电力监控系统组网架构及网络安全协同防护的需求,提出一种多层次且纵深分布的主动安全协同防御模型,并从模型架构、功能机制等方面设计一整套实现方案。基于域内自防御和跨域协防的特性,通过基于灰色关联分析的最高关联度防御决策,并协同安全防护设备间协作,实现从主机层、安防设备层到网络层的网络安全多级防御。通过电力监控系统典型现场对网络安全应用场景进行实验验证,结果表明,该协同防御模型增强了各层级间安全防护能力,能够提供更高效的安全风险监测、安全事件响应及动态处置的手段。     

基于间歇反馈多维泰勒网的动力学模型

具有羊群效应的系统,因为结构复杂,内部要素互相影响,参与其中的人类行为难以预测而不易建立整体模型. 本文提出建立间歇反馈多维泰勒网动力学模型方法,通过叠加的死区函数模拟了羊群效应中从众心理对系统产生的间歇反馈,结合多维泰勒网建立了适合普遍系统的一般动力学方程. 该方法区别于以往羊群效应的以个体研究为出发点,通过系统对外表征的数据波动建立了含有羊群效应的整体模型. 实例结果表明,这种基于间歇反馈多维泰勒网的动力学建模方法是可行和有效的.     

基于粒子系统的虚拟战场环境特殊效果模拟

作战系统在军事训练和军事演习的应用上具有经济性、科学性、实时性、交互性等其他训练模式无法比拟的优点,能够提高军事训练的效率,减少训练的成本,增加战士在训练过程中的安全性。虚拟战场环境是作战系统的一个非常基础的平台,值得研究探讨。在虚拟战场环境模拟中,对不规则动态形状物体建模的最有效的方法是粒子系统。而文中深入研究了粒子系统的基本原理,应用粒子系统的方法构建了一个战场爆炸模型来实现爆炸效果的具体实现过程,并分析爆炸粒子所受的动力来建立爆炸粒子的物理模型。实验结果表明这一模拟方法简单有效,逼真度和实时性效果较好。     

电力系统微分代数模型耗散Hamilton实现

对非线性微分代数模型电力系统的耗散Hamilton实现问题进行了研究．首先提出了非线性微分代数系统的耗散Hamilton实现结构,给出了完成常值耗散Hamilton实现的充分条件;然后证明单机单负荷电力系统必然存在耗散Hamilton实现,并构造出系统的一个耗散Hamilton实现．     

基于DBN的计算系统动态安全分析模型

计算系统脆弱性分析是系统安全领域研究的热点问题之一。随着多核技术的出现,计算系统呈现开放性和动态性的特征。有鉴于此,在研究现有系统安全风险分析的基础上,提出了面向动态计算系统的安全分析模型,它利用动态贝叶斯网络构建攻击图,以解决计算系统脆弱性动态转移的问题。最后,以虚拟计算系统为实例验证了所提方法的效率和性能。实例仿真表明,该方法是动态系统安全风险分析的一种新的有效途径。     

面向服务的工作流动态访问控制模型

访问控制是提高工作流系统安全的重要机制.基于角色的访问控制(RBAC)被绝大多数工作流系统所采用,已成为工作流领域研究的热点.基于传统的RBAC模型,从工作流访问控制模型与流程模型分离的角度出发,提出了一种面向服务的工作流动态访问控制模型--SWDAC模型.模型中引入服务和上下文的概念,加强了对动态工作流系统的描述能力,并有效增强了访问控制的灵活性和系统的安全性.该访问控制模型已在自主研发的基于J2EE的工作流管理平台中实施.