基于节点集合的PMU优化配置方法

同步相量测量单元(PMU)的最优配置要求在全局可观的前提下所配置的PMU最少。0-1线性整数规划在分析求解多目标PMU最优配置有极大的优势。在实际电力系统中存在一定数量的零注入节点。作为虚拟测量数据,虽然有利于PMU最优配置,然而引入到整数规划进行计算时,将使模型非线性化而难以求解。给出了考虑零注入功率节点情况下的条件函数,该函数能够有效保持函数的线性性从而仍能适用于0-1整数规划。当考虑N-1情况下的PMU最优布点时,该方法具有很强的继承能力,有效解决了传统方法无法解决的N-1优化配置问题。最后将该方法应用于IEEE14节点以及IEEE39节点的算例,相对于其他配置方法,减少了PMU配置数量,从而体现了该方法的优越性。     

基于0-1整数规划算法的PMU量测点优化配置新方法

为了提高同步相量测量装置的优化配置速度,提出了基于0-1整数规划算法的PMU量测点优化配置方法。在0-1整数规划算法的基础上,根据节点的可观测性建立数学模型,考虑节点间的相互关系构建邻接矩阵并进行分析,求解量测点模型获得量测配置优化位置。对IEEE-14和IEEE-18节点系统进行实验仿真,并利用Lingo工具验证所提0-1整数规划算法,获取PMU优化位置和速度。该算法与未改进的0-1整数规划算法相对比,结果表明,该方法减少了变量数目,简化了约束条件,减少了迭代次数,提高了收敛速度,验证了所提方法的有效性和实用性。     

基于非线性混合整数规划的配电终端布点优化研究

提出一种考虑供电可靠性和经济成本的配电自动化终端布点优化方法,在架空馈线安装故障指示器、电压时间型终端和电压电流型终端,在电缆馈线安装故障指示器、二遥终端和三遥终端,对配网进行配电自动化改造以提高供电可靠性,可靠性指标取为用户年平均故障停电时间,故障影响模式根据配电终端类型确定。用Java语言编程实现,从XML文件读取配网数据,使用JGraphT图形库存储配网拓扑信息,建立非线性混合整数规划模型,使用建模系统Gams求解模型,为便于工程实施,分阶段输出优化结果。采用某市的配电终端布点规划作为算例,验证了方法的可行性。     

重载机车粘着性能参数的极大似然辨识方法

针对重载机车运行中机车的粘着利用率低、易空转、易打滑的问题,提出一种对轨面粘着性能参数的实时在线估计算法。首先从分析机车粘着行为出发,选用Kiencke的粘着-蠕滑模型作为辨识模型,然后算法利用极大似然意义下的模型参数辨识框架,将参数估计转化为二次规划问题求解,进而构造出辨识的迭代算法。同时考虑到轮轨环境突变的不可测,辨识算法引入时变遗忘因子来适应轨面环境的切换。仿真结果表明,该算法能及时跟踪上轮轨环境的变化,有效辨识出粘着性能参数。     

考虑污染物排放约束的传统电厂与虚拟电厂间环境经济调度模型

为有效实现分布式能源(distributed energy resource,DER)单元参与电力系统能源市场,深度挖掘负荷侧灵活供能潜力,首先建立虚拟电厂(virtual power plant,VPP)作为管理运行分布式能源的代理模型,并基于组件特性分析对虚拟电厂的外特性进行了量化;然后基于当前电力行业面临的经济环境热点问题,建立了考虑污染物排放约束的传统电厂(conventional power plant,CPP)和虚拟电厂间的环境经济调度(environmental economic dispatch,EED)二阶约束二阶规划(quadratically constraint quadratic programming,QCQP)模型;接着介绍了CPLEX优化引擎和YALMIP软件包的功能,并采用建模与求解解耦的方式来求解模型;最后对改进10机系统进行仿真计算,验证了所提模型的有效性和正确性。     

Response covariance-based sensor placement for structural damage detection

One important function of a structural health monitoring system is to detect structural damage in a structure. However, this is a very challenging task since the measurement is often incomplete in a civil structure due to a limited number of sensors. This paper presents a response covariance-based sensor placement method for structural damage detection with two objective functions for optimisation. The relationship between the covariance of acceleration responses and the covariance of unit impulse responses of a structure subjected to multiple white noise excitations is first derived. The response covariance-based damage detection method is then presented. Two objective functions based on the response covariance sensitivity and the response independence are, respectively, formulated and finally integrated into a single objective function for optimal sensor placement. Numerical studies are conducted to investigate the feasibility and effectiveness of the proposed method via a three-dimensional frame structure. Numerical results show that the proposed method with the backward sequential sensor placement algorithm is effective for damage detection.     

WASTE FLOW ALLOCATION PLANNING THROUGH A GREY FUZZY QUADRATIC PROGRAMMING APPROACH

This paper proposes a grey fuzzy quadratic programming (GFQP) approach as a means for optimization analysis under uncertainty. The method combines the ideas of grey fuzzy linear programming (GFLP) and fuzzy quadratic programming (FQP) within a general optimization famework. It improves upon the previous GFLP method by using n grey control variables, ® (A,j (i = 1,2,..., n), for n constraints instead of one ® (X) for n constraints in order to incorporate the independent properties of the stipulation uncertainties; it also improves upon the FQP method by further introducing grey numbers for coefficients in A and C to effectively reflect the lefthand side uncertainties. Compared with the GFLP method, the GFQP approach is helpful for better satisfying model objective/constraints and providing grey solutions with higher system certainty and lower system cost; compared with the FQP method, more information of the independent uncertain features of not only the stipulations but also the lefthand side coefficients are effectively reflected in the GFQP method.

The GFQP modelling approach is applied to a hypothetical case study of waste flow allocation planning under uncertainty, with the input model stipulations fluctuating within wide intervals and having independent uncertain characteristics. The results indicated that reasonable solutions have been generated. Comparisons between the GFQP and FQP/GFLP solutions are also provided, which demonstrate that the GFQP method could better reflect system uncertainties and provide more realistic and applicable solutions with lower system uncertainties and higher system benefits.     

基于模拟退火的粒子群算法优化的二次回归在混凝土抗压强度预测中的应用

混凝土抗压强度与其影响因素之间存在着很强的非线性关系,精确预测混凝土抗压强度对提高工程质量和施工进度等具有重要意义。为了提高预测值的精确度,建立了二次回归预测模型,利用基于模拟退火的粒子群算法对模型系数进行了优化和求解。实例仿真表明这种经智能算法优化后的二次回归预测模型优于传统神经网络预测模型,预测精度得到了较大提高。     

Optical fiber multiparameter sensor for real-time monitoring of thermoplastic composites during in situ consolidation process

Temperature and strain are important parameters in the in situ consolidation process of thermoplastic composites and have been monitored based on optical fiber Bragg gratings. A special polyimide fiber grating (PFBG) is used in this article. PFBG can monitor temperatures up to 400°C and strains up to 40,000 με. The wavelengths of the PFBGs are obtained by wavelength demodulation system and fast digital signal processing with field programmable gate array. Temperature and strain in auto fiber placement process of thermoplastic composites are monitored accurately according to wavelengths. During the whole consolidation process, temperatures have been monitored with the accuracy of 0.1°C in the range of 100–250°C and strains have been monitored with the accuracy of 1 με in the range of ?250 to 500 με. The validity and correctness of the results have been validated by the thermocouple and the strain gauge.     

基于本地内容流行度预测的主动缓存策略

已有边缘缓存技术研究假设已知固定的全局流行度,忽略了反映基站接收到的内容请求历史中的流行度地域差异特性和动态特性,为此,提出了一种基于本地内容流行度预测的内容部署策略.首先,考虑流行度的地域特性,将内容请求历史记录相似的小基站分簇;然后,使用线性回归方法预测每个小基站簇群的本地内容流行度,基于预测的本地内容流行度,利用随机几何和凸优化理论求得次优内容部署决策;最后,基于真实数据集的实验验证了所提算法性能以及相应的缓存系统性能.仿真结果表明,所提算法优于对比算法的缓存命中率性能.