基于稀疏学习的微电网负载建模

微电网由负载、储能系统和分布式电源互联集成到能源系统中, 微电网系统可以作为一个整体系统与电网并行运行或以孤岛模式运行. 负载建模是微电网运行和管理中的一个基本问题. 本文着重解决以下两个关键问题: 1)协调负载模型结构的合理性和简洁性; 2)负载模型参数的校准. 与常规负载建模方法不同, 本文提出了一类数据驱动建模方法以同时实现负载模型结构选择和参数校准. 具体地, 该方法从量测数据中稀疏学习静态负载模型和动态负载模型, 其关键方法分别来自于稀疏贝叶斯学习方法和交替方向方法, 即从一组备选非线性字典函数中稀疏学习最主要的非线性项以平衡数据拟合度并实现模型学习. 所提出的方法将机器学习与稀疏表示相结合, 旨在对负载模型从物理角度提供机理解释并向配电网系统操作员提供有关负载的动态信息. 在孤岛微电网测试系统中验证并评估了所提出的算法. 研究测例表明所提出算法从量测数据中实现负载稀疏学习的合理性和对于噪声的鲁棒性.     

一种新的参数自适应主动移频孤岛检测方法

在分布式发电系统中,孤岛检测方案是必不可少的部分。但是当逆变器输出负载发生有功无功匹配时,准确及时地检测孤岛将变得十分困难。一些基于频率或相位偏移的孤岛检测方案在这种时候将失去效用。提出一种参数自适应的主动频移孤岛检测方法。在该方法中,受控制的逆变器输出电流频率将随着公共连接点(PCC)的电压频率变化而自适应的改变其频率,依据正反馈信号进行调节打破逆变器输出与负载之间的相位和功率匹配,从而实现快速的孤岛检测。干扰信号被周期性的注入逆变器输出电流中,通过两种频率范围内的不同算法来避免孤岛检测误动作,并尽量减少干扰信号对电网的影响。最后,通过Matlab/Simulink平台对该方法进行的仿真验证,仿真结果证明,该方法可以针对多种不同的负载情况实现快速准确的孤岛检测,达到了预计的目标。     

孤岛模式下VSG的转动惯量无模型自适应控制

频率稳定是微网在孤岛模式下稳定运行的关键.由于传统下垂控制的转动惯量固定,当微网中接入时变负载时无法满足系统的频率稳定需求.针对传统控制方式的不足,提出虚拟同步发电机的转动惯量无模型自适应控制.首先,分析在孤岛模式下的传统虚拟同步发电机控制算法的角速度变化率的抑制效果和恢复时长;其次,设计无模型自适应控制器并证明控制算...     

基于方差检验的并行负载抖动检测

负载抖动是影响负载模型准确性和代表性的关键因素。本文通过两个负载抖动例子给出负载抖动的定义，研究了抖动日志对负载模型的影响情况，提出了一种通过分析总资源向量和最大资源向量的方差检测负载抖动的算法，研究时间刻度参数△t对算法的影响情况，并给出了其较合理的取值范围。     

负载类型相关的Xen虚拟机系统性能模型

针对Xen虚拟机系统执行网络I/O密集型负载时容易耗尽Domain0的CPU资源而过载和执行计算密集型负载时在客户域平均性能与数目之间存在线性规划的问题,提出了两个负载类型相关的性能模型。首先,通过分析Xen虚拟机系统处理网络I/O操作的CPU资源消耗规律,建立了CPU核共享和CPU核隔离两种情况下的客户域网络I/O操作请求次数计算模型;然后,通过分析多个相同客户域并行执行计算密集型负载的平均性能与一个相同客户域执行相同负载的性能表现之间的关系,建立了并行执行计算密集型负载的客户域平均性能分析模型。实验结果表明,两个性能模型能够有效地限制客户域提交的网络I/O操作请求次数以防止Xen虚拟机系统过载,并求解给定资源配置情况下执行计算密集型负载的Xen虚拟机系统客户域伸缩性数目。     

分布式系统中主机负载预测的一种普适性方法

分布式系统中为了获得高效的动态负载均衡,需要对主机负载进行有效的预测,这区别于网络流量的预测。论文从分析主机负载的特性入手,依据负载动态变化的规律,提出了一种具有普遍适用性的主机负载预测方法—线性时间序列模型法,并按该方法建立了HLPS(HostLoadPredictionSystem)模型,提出了HLPS的实现策略。     

基于相位偏移的主动移频式孤岛检测方法

针对传统过压/欠压、过频/欠频、相位突变、主动频率偏移孤岛检测方法的不足,提出了一种改进方法.将相位偏移量作为辅助量加入主动移频孤岛检测方法中,使检测容性负载的孤岛现象具有与感性负载同样的快速性,并能有效降低主动频率偏移法对电网电能的影响.该方法实现简单,检测快速,仿真结果验证了其快速性和有效性.     

超级节点的负载模型研究

在混合式P2P系统里,超级节点对查询消息的处理效率决定了系统性能。本文首先将超级节点收到的所有消息分为三类,然后将他们产生的负载分为公有负载和私有负载,建立起超级节点的负载模型,最后分析了两类负载对系统性能的影响。     

一种面向多用户的负载感知动态服务选择模型

在面向多用户的动态环境中进行基于QoS 的服务选择需要面临诸多挑战,而动态的服务负载就是其中之一.当前的服务选择方法难以在多用户多业务的开放环境下应对服务执行时的负载动态变化,缺乏实时感知负载的应变能力.针对这一问题,首先,提出一种基于负载等级的服务多维QoS 模型（load level based multidimensional QoS,简称LLBMQoS）;在此基础上,提出了一种面向多用户的负载感知的动态服务选择模型（load-aware dynamic serviceselection model,简称LADSSM）以实现动态负载环境下的服务优化选择.该模型采用两阶段服务选择：在组合服务规划阶段,生成候选服务队列;在组合服务执行阶段,依据当前负载状态实现服务的动态选择;最后,仿真实验的结果表明：该模型较好地适应了多用户动态环境下的服务负载变化,能够在保证用户端到端QoS需求的前提下,及时而有效地提供效用优化的服务选择方案.     

中间件负载均衡的模型和实现

由于客户机访问服务器的随机性,中间件服务器负载不均衡的现象时有发生,所以负载均衡是提高三层系统效率的重要手段。文中介绍了中间件负载均衡的原理,提出了两种中间件负载均衡的实现模型,并且评价了这两种模型的性能,指出了各自的优越点与适用范围,最后给出了基于COM 的的实现方法与关键技术。     

Parallel models of computation: an introductory survey

The paper gives an overview of some models of computation which have proved successful in laying a foundation for a general theory of parallel computation. We present three models of parallel computation, namelyboolean andarithmetic circuit families, andParallel Random Access Machines. They represent different viewpoints on parallel computing: boolean circuit families are useful for in-depth theoretical studies on the power and limitations of parallel computers; Parallel Random Access Machines are the most general vehicles for designing highly parallel algorithms; arithmetic circuit families are an important tool for undertaking studies related to one of the most active areas in parallel computing, i.e. parallel algebraic complexity.     

可扩展并行计算机系统结构和发展现状

Scalable parallel computer is becoming a trend in developing parallel computers. Scalable computers are classified into three system models: the Symmetric Multiprocessor, the Massively Parallel Processor and the Cluster of Workstation. In this paper, the three models are discussed and Dawn parallel computers which belong to MPP and COW models are introduced.     

基于FPGA的细粒度并行CYK算法加速器设计与实现

基于随机上下文无关文法(SCFG)理论模型进行RNA二级结构预测是目前采用计算方法研究RNA二级结构的一种重要途径.由于基于SCFG模型的标准结构预测算法(Coche-Younger-Kasami,CYK)巨大的时空复杂度,对CYK算法进行加速成为计算生物学领域一个极具挑战性的热点问题.CYK的并行性能受限于算法多维度、非一致性的数据依赖关系和较低的计算/通信比,现有的基于通用微处理器结构的大规模并行处理方案不能获得令人满意的加速效果,并且大规模并行计算机系统硬件设备的购置、使用、日常维护的成本高昂,其适用性受到诸多限制.文中在深入分析CYK算法计算特征的基础上,基于FPGA平台提出并实现了一种细粒度的并行CYK算法.设计采用了对三维动态规划矩阵按区域分割和逐层按列并行处理的计算策略实现了多个处理单元间的负载均衡;采用数据预取、滑动窗口和数据传递流水线实现处理单元间的数据重用,有效解决了计算和通信间的平衡问题;设计了一种类似脉动阵列(systolic-like array)结构的主从多PE并行计算阵列,并在目前最大规模的FPGA芯片(Xilinx XC5VLX330)上成功集成了16个处理单元(process...     

Parallel solution of a traffic flow simulation problem

Computational Fluid Dynamics (CFD) methods for solving traffic flow continuum models have been studied and efficiently implemented in traffic simulation codes in the past. This is the first time that such methods are studied from the point of view of parallel computing. We studied and implemented an implicit numerical method for solving the high-order flow conservation traffic model on parallel computers. Implicit methods allow much larger time-step than explicit methods, for the same accuracy. However, at each time-step a nonlinear system must be solved. We used the Newton method coupled with a linear iterative method (Orthomin). We accelerated the convergence of Orthomin with parallel incomplete LU factorization preconditionings. We ran simulation tests with real traffic data from an 12-mile freeway section (in Minnesota) on the nCUBE2 parallel computer. These tests gave the same accuracy as past tests, which were performed on one-processor computers, and the overall execution time was significantly reduced.     

Parallel automatic adaptive analysis

Consideration is given to the techniques required to support adaptive analysis of automatically generated unstructured meshes on distributed memory MIMD parallel computers. Emphasis is placed on the structures needed to support effective parallel computations when the numerical discretization, the mesh, is defined and evolves during the computation. The key base structures are a distributed mesh based on a topological hierarchy, and a parallel distributed octree. Parallel control of the mesh and octree structures is done through a set of partition communication operations and entity migration routines. Load balance is maintained through iterative load balance, or distributed repartitioning. Building on these structures, procedures to automatically generate and adaptively refine meshes in parallel, starting from CAD geometric models, are given. Finally, the combination of these techniques to produce a parallel automated analysis procedure is demonstrated.     

Parallel processing of the radiosity method

The radiosity method gives one of the best solutions for synthetizing realistic images. However, the method is also the most computationally expensive. Using parallel computers will cut the time required to solve this problem provided that care is taken in the design of the system. Various models of parallel computing are explored for both the gather radiosity method and the progressive refinement radiosity method.     

基于并行Benchmark的高性能机实用测试与评价方法

文中分析了传统基于并行基准测试程序测试方法的不足，针对目前高性能计算机处理机台数多的特点，给出了实用的测试方法，推广了传统加速比的概念，提出了一种可扩展性评价方法。使用文中给出的方法，可方便地对高性能计算机进行测试和性能评价，同时可以使用小规模的并行机测试结果预测大规模并行机的性能。最后给出了NPB在某高
性能计算机上的测试和性能评价结果。     

Parallel Machines

Because it is time-dependent, parallel computation is fundamentally different from sequential computation. Parallel programs are non-deterministic and are not effective procedures. Given the brain operates in parallel, this casts doubt on AI's attempt to make sequential computers intelligent.     

Parallel Coarse Grain Computing of Boltzmann Machines

The resolution of combinatorial optimization problems can greatly benefit from the parallel and distributed processing which is characteristic of neural network paradigms. Nevertheless, the fine grain parallelism of the usual neural models cannot be implemented in an entirely efficient way either in general-purpose multicomputers or in networks of computers, which are nowadays the most common parallel computer architectures. Therefore, we present a parallel implementation of a modified Boltzmann machine where the neurons are distributed among the processors of the multicomputer, which asynchronously compute the evolution of their subset of neurons using values for the other neurons that might not be updated, thus reducing the communication requirements. Several alternatives to allow the processors to work cooperatively are analyzed and their performance detailed. Among the proposed schemes, we have identified one that allows the corresponding Boltzmann Machine to converge to solutions with high quality and which provides a high acceleration over the execution of the Boltzmann machine in uniprocessor computers.     

多核环境下边缘提取并行算法研究

随着处理器由高主频的单核处理器逐步转向片上多核处理器(CMP),计算机并行处理能力不断提升。通过分析GIS串行算法面临的性能瓶颈,利用CMP的优势,采用线程级并行处理栅格数据。针对边缘提取算法,深入分析和比较了MPI、OpenMP等当前主流的并行编程模式,提出了并行性能估计模型。基于OpenMP编程模型分析线程数、调度方式和分块大小对算法并行性能的影响,实现边缘提取最优并行。实验证明,性能评估模型能够准确预测CMP环境下的并行性能,基于OpenMP实现的边缘提取并行算法能够提高图像边缘提取效率。