基于改进Dijkstra算法的配电网网架扩展规划

电气工程领域中配电网网架扩展规划的目的是确定最优的配电网网架接线方案。配电网网架扩展规划的本质与最短路径问题有相同之处。作为典型的最短路径求解算法之一的Dijkstra算法,在进行配电网网架扩展规划时,需要建立邻接矩阵,并反复对无序排列的初始数据进行遍历搜索,反复遍历搜索影响了算法的计算速度。针对Dijkstra算法对无序排列的初始数据反复遍历搜索对计算速度造成的影响,基于排序思想,提出了改进Dijkstra算法,以提高Dijkstra算法在进行配电网网架扩展规划时的计算速度,然后根据某10 kV中压配电网网架扩展规划算例,基于全寿命周期概念建立了中压配电网网架扩展规划的数学模型,经算例分析验证了所提方法的有效性。     

基于人群密度的最优路径规划算法研究

在众多路径规划算法中,A^*算法是一种典型的最短路径规划算法,但是该算法的应用环境较为局限。为此综合复杂环境中人群密度的因素,以时间最短为准则,将最短距离路径规划问题优化为最短时间路径规划。最优路径规划算法在A^*算法的基础上,引入不同人群密度环境下的行人速度模型,将A^*算法中基于距离的评估函数改变为基于时间的评估函数。实验通过标准网格地图对144种情况进行了模拟,结果表明,相较于传统A^*算法,最优路径规划算法优先选择从周围低人群密度区域绕行到达终点,规划路径在距离上可能更长,但是花费的时间更短。     

基于最小生成树算法的配电网架扩展规划

基于改进最小生成树算法,提出了一种高效率的配电网扩展规划方法。以最大投资额度为约束条件,以建设费用与运行费用的加权和最低为目标函数,采用prim算法求取最小生成树获得初步规划结果,根据潮流计算结果调整导线截面并计算运行费用,依此反复迭代调整规划网架直至最优。规划过程中考虑了对道路交叉点区别对待,并且只将采用Dijkstral算法获得的顶点间的最短路径作为边,还考虑了拆除线路的残值和拆除费用。对两个典型算例进行了规划,结果表明所提出的方法是可行的且具有较高的效率。     

基于改进蚁群算法的车辆路径优化

针对基本蚁群算法易陷于局部最优解及道路交通流易产生拥塞等缺陷,提出了一种改进蚁群算法。结合实时交通信息,以时间最短建立了动态路径规划的目标转换模型,应用改进蚁群算法求解车辆最短路径,对于求解过程中出现局部最优解,引入了随机蚂蚁这一概念,同时基于Greenshields模型处理了正反馈以及个体最优策略造成的拥塞现象。     

基于多级自校验和多重切换的自适应相量算法

配电网同步相量测量装置可以大幅提升配电网的可测、可观、可控水平,可以解决大规模分布式电源和柔性负荷接入后现代配电网所面临的巨大挑战,促进配电网转型升级。本文提出了基于多级自校验和多重切换的自适应相量算法。在多级校验方面,提出了基于多级自校验识别稳态、动态和暂态3种模式,并设计了适应3种状态的算法。在多重切换方面,提出了通过校验算法、传感器类型、采样率、窗函数类型、数据窗长度和相量算法的多重自切换,以满足同步相量测量装置性能的要求。为进一步验证本文所提算法的优越性能,在仿真软件上进行了仿真测试分析,结果表明所提算法能满足实际应用要求。     

基于最小生成树的电力通信系统时钟同步网规划算法

电力通信网要求具有高稳定度、高精度、安全可靠的网络时钟同步环境。通过对电力系统时钟同步网规划问题的研究,提出了一种基于最小生成树的电力系统时钟同步网的规划算法,该算法针对单一时钟源网络,在传输级数最少的基础上以传输距离最短为目标,并借助最小生成树理论和层内优化思想实现两阶段优化以确定最佳路径,该算法速度快,效率高,适合大规模时钟同步网的规划求解。     

基于最小生成树算法的配电网架扩展规划

基于改进最小生成树算法，提出了一种高效率的配电网扩展规划方法。以最大投资额度为约束条件，以建设费用与运行费用的加权和最低为目标函数，采用prim算法求取最小生成树获得初步规划结果，根据潮流计算结果调整导线截面并计算运行费用，依此反复迭代调整规划网架直至最优。规划过程中考虑了对道路交叉点区别对待，并且只将采用Dijkstral算法获得的顶点间的最短路径作为边，还考虑了拆除线路的残值和拆除费用。对两个典型算例进行了规划，结果表明所提出的方法是可行的且具有较高的效率。     

基于增量最短路径法的全电缆中压配电网络规划

电缆化供电是城市中压配电网供电的发展趋势。提出一种实用的基于增量最短路径法的全电缆中压配电网络主干网架规划方法,考虑了电缆通道约束以及城市规划约束,将全网整体优化分解为电源供电分区的电缆线路规划和分区间线路联络规划两部分,利用增量最短路径法规划电源供电分区的电缆供电线路,应用最佳匹配算法完成分区间线路联络。通过一实际算例验证了所提方法可应用于全电缆中压配电网的网络新建规划和扩展规划。     

一种高性能的多级异构电能质量数据库同步方法

为提高分布式电能质量管理系统中数据同步性能,提出了一种高性能的多级异构电能质量数据库同步方法。首先针对电能质量数据的特点,建立了基于事件驱动的多级异构数据库同步模型,然后提出了基于持久化消息队列的数据可靠同步方法,给出了基于事件日志的数据一致性检查和恢复算法,实现了海量电能质量数据在多级异构数据库中的高效同步。分析表明,该方法能有效提高多级异构电能质量数据库的同步性能。     

城市集中型充电站规划方法

为实现城市集中型充电站合理规划,在分析影响电动汽车充电站规划因素的基础上,根据电动汽车空间分布特点,提出基于图论的集中型充电站选址图模型。结合图中央点理论对K-means聚类算法进行改进,提出了集中型充电站服务范围最优划分和站点选址算法。采用某中央城区实际规划算例计算,并与K-means和Vor-onoi图计算几何法比较,计算结果表明,本文所提方法具有更好的规划效果,获得更均衡的服务区域划分和更短的充电路径距离。     

Efficient power pad assignment for multi‐voltage SoC and its application in floorplanning

Multi‐voltage techniques are being developed to improve power savings by providing lower supply voltages for noncritical blocks under the performance constraint. However, the resulted lower voltage drop noise margin brings serious obstacles in power/ground (P/G) network design of the wire‐bonding package. For voltage drop optimization, both block and power pad positions are important factors that need to be considered. Traditional multi‐voltage floorplanning methods use rough estimation to evaluate the P/G network resource without considering the locations of power pads. To remedy this deficiency, in this paper, an efficient voltage drops aware power pad assignment (PPA) method is proposed, and it is further integrated into a floorplanning algorithm. We first present a fast PPA method for each power domain by the spring model. Then, to evaluate voltage drops during floorplanning iterations, the weighted distance from the blocks to the power pads is adopted as an optimization objective instead of time‐consuming matrix computation. Experimental results on Gigascale System Research Center (GSRC) benchmark circuits indicate that the proposed method generates an optimized placement of power pads and floorplanning of blocks with high efficiency. Copyright © 2015 John Wiley & Sons, Ltd.     

Cost reduction in bottom‐up hierarchical‐based VLSI floorplanning designs

From the industrial perspective, floorplanning is a crucial step in the VLSI physical design process as its efficiency determines the quality and the time‐to‐market of the product. A new perturbation method, called Cull‐and‐Aggregate Bottom‐up Floorplanner (CABF), which consists of culling and aggregating stages, is developed to perform variable‐order automated floorplanning for VLSI. CABF will generate VLSI floorplan layout by calculating the modules' dimensions' differences (hard module floorplanning problems) and the modules' areas' differences (soft module floorplanning problems). Through mathematical derivation, the hard modules floorplanning area minimization cost function (two‐dimensional) during culling stage is proven that a dimensional reduction can be carried out to be the difference‐based cost function (one‐dimensional) which simplifies the computation. During the culling stage, CABF employs linear ordering method to select and determine the order of modules where this linear runtime complexity property allows CABF to cull the modules faster. The aggregating stage of CABF will reduce the subsequent search space of this floorplanner, and the variable order aggregation enables CABF to search for the best near‐optimal solution. Based on Gigascale Systems Research Center and Microelectronics Center of North Carolina circuit benchmarks, CABF gives better optimal solutions and faster runtimes for floorplanning problems involving 9 to 600 modules. This has established that CABF is performing well in respect of reliability and scalability. Besides, CABF shows its potential to be implemented in VLSI physical design as the runtime of CABF is faster with a near‐optimal outcome as compared to the other existing algorithms. Copyright © 2013 John Wiley & Sons, Ltd.     

A multiobjective optimization tool for Very Large Scale Integrated nonslicing floorplanning

Floorplanning is a vital phase in the design process of Very Large Scale Integrated (VLSI) circuit physical design process. The main objective of floorplanning is to minimize the area and wire length with the fixed‐outline constraints. Most of the tools developed so for are using weighted some approach. Hence, these tools suffer from weights assignment and undesirable bias toward particular objective. A tailor‐made multiobjective optimization tool could overcome this issue. In this article, we propose a new multiobjective optimization technique named self adaptive B*tree coded Archived Multiobjective Simulated Annealing Algorithm (AMOSA) and implemented to solve the VLSI nonslicing floorplanning problem. The proposed model provides choices from among different trade‐off solutions. The self adaptive B*tree coded AMOSA combines the novel cooling schedule, B*tree encoding, improved neighborhood search procedure, self adaptive local search, and the AMOSA. In B*tree coded AMOSA, the solution is represented using a B*tree. This representation causes a reduction in time and space complexity of AMOSA. The B*tree coded AMOSA is further improved with a novel cooling schedule, a self adaptive local search mechanism, and an improved neighborhood search procedure, resulting in further reduction of computational time and improvement in exploration capability. The FastSA, B*tree coded AMOSA, and the self adaptive B*tree coded AMOSA are tested with Microelectronics Center of North Carolina (MCNC) benchmarks. The results are compared and validated. The proposed method shows 59.8% improvement in the computational time for ami49 without changing the system quality. Copyright © 2012 John Wiley & Sons, Ltd.     

Function‐in‐layout: a demonstration with bio‐inspired hyperacuity chip

Below 100 nm a new scenario is emerging in VLSI design: floorplanning and function are inherently interrelated. Using mainly local connectivity, wire delay and crosstalk problems are eliminated. A new design methodology is proposed, called function‐in‐layout, that possesses: regular layout, mainly local connectivity, functional ‘parasitics’. A bio‐inspired demonstration is presented, a hyperacuity chip, with 30 ps time difference detection using 0.35 mm complementary metal‐oxide semiconductor (CMOS) technology. Copyright © 2006 John Wiley & Sons, Ltd.     

Variation of distribution factors with loading

Power transfer distribution factors depend on the operating point and topology of an electric power system. However, it is known empirically that, for a fixed topology, the power transfer distribution factors are relatively insensitive to the operating point. We demonstrate this result theoretically for systems of arbitrary topology with losses, but only for the special case of having reactive compensation sufficient to keep voltages constant at all busses. We also analyze a power to current distribution factor that more closely relates to thermal constraints. We provide empirical corroboration for the theoretical result.     

Many-Body Terms in van der Waals Cohesion Energy of Nanotubes

We have developed a model for the calculation of van der Waals force for layered systems with axial symmetry. Our result can be applied to compute the cohesion of a carbon nanotube to a substrate, the cohesion between nanotubes, and between shells of multiwall nanotubes. We have obtained unusal power laws for the distance dependence of the many-body van der Waals potential.     

AMDS&ADS在手机天线初期设计仿真中的应用

本文简要介绍了一款实物手机天线的初期设计(mockup),同时用AMDS和ADS软件进行协同仿真,得到的仿真和模拟测试结果基本一致,并进一步对该天线在整机中的性能作出评估,极大地缩短了的设计周期,降低了风险。这说明AMDS对天线复杂的电磁仿真可以得到非常接近实际的结果,是一种理想的3D天线分析仿真工具,对天线设计具有很好的指导意义。     

Stochastic stability of a neural‐net robot controller subject to signal‐dependent noise in the learning rule

We consider a neural network‐based controller for a rigid serial link manipulator with uncertain plant parameters. We assume that the training signal to the network is corrupted by signal‐dependent noise. A radial basis function network is utilized in the feedforward control to approximate the unknown inverse dynamics. The weights are adaptively adjusted according to a gradient descent plus a regulation term (Narendra's e‐modification). We prove a theorem that extends the Yoshizawa D‐boundedness results to the stochastic setting. As in the deterministic setting, this result is particularly useful for neural network robot control when there exists bounded torque disturbances and neural net approximation errors over a known compact set. Using this result, we establish bounds on the feedback gains and learning rate parameters that guarantee the origin of the closed‐loop system is semi‐globally, uniformly bounded in expected value. Copyright © 2009 John Wiley & Sons, Ltd.     

Zooming算法在磁极优化设计中的应用

把一种新型全局优化算法-Zooming算法引进到电机优化设计中.首先介绍Zooming算法的基本原理,然后以该算法对永磁起动机进行磁极优化设计,取得较为满意的结果.     

一种电压有效值的低温漂、高精度测量方案

电力参数电压有效值的测量一般都是采用真有效值来测量,测量中人们关心的是测量准确度和测量稳定性,即温度漂移特性。本利用专用高性能真有效值(RMS)测量芯片AD736,并结合单片机技术给出了一种高精度、高稳定度、低温度漂移的交流电压有效值测量方法。