构网型分布式电源渗透率高的微电网潮流计算及优化控制

随着微电网(microgrid,MG)中构网型分布式电源(distributed generator,DG)渗透率的提高,传统的潮流计算和优化方法不再适用。基于下垂控制的数学模型,改进传统牛顿拉夫逊法;应用虚拟阻抗松弛DG的无功与电压约束,改进下垂控制;应用改进粒子群优化算法,得到使网损最小的MG优化潮流;通过仿真和实验,验证了该方法的有效性。该文有助于指导构网型DG渗透率高的末端电网或MG的规划与控制。

分布式离网型风力·光伏发电系统应用及核心技术

分布式离网型风力、光伏发电是解决边远地区人口用电问题有效途径,文中介绍了分布式离网型风力、光伏发电系统在该领域的各种应用、各种应用模式系统构成和基本适用条件,以及系统核心技术。

综合集成的内容与方法——复杂巨系统问题研究

本文归纳了解决复杂巨系统问题时遇到的困难，给出了解决复杂巨系统问题的一般分析步骤，研究了用综合集成技术研究解决复杂巨系统问题的方法。综合集成包括“知识集成”和“系统综合”两层含义。“知识集成”包括四项支撑技术：分布式网络、信息融合、定性定量相结合、专家研讨。

虚拟环境和人在回路中的计算机应用

本文说明了近年来得到迅速发展的虚拟环境技术，及其为人在回路中的各种计算机应用提供的一些基本特性。文中例举了人在回路中的计算机应用领域涉及到的某些虚拟环境特性。

STUDY ON MEASURES OF FAULT TOLERANCE FOR DISTRIBUTED SYSTEM

Fault tolerant ability is an important aspect for overall evaluation of distributed system(DS). This paper discusses three measures for the evaluation: node/edge connectivity, number of spanning trees and synthetic connectivity. A numerical example for illustration and analysis is given, and the synthetic connectivity measure presented by this paper is proved to be rational and satisfactory.

Distributed amplifier of L-type network with 2-μm GaAs HBT process

The characteristic impedances of L-type and T-type networks are first investigated for a distributed amplifier design.The analysis shows that the L-type network has better frequency characteristics than the T-type one.A distribution amplifier based on the L-type network is implemented with the 2-μm GaAs HBT（heterojunction-bipolar transistor） process of WIN semiconductors.The measurement result presents excellent bandwidth performance and gives a gain of 5.5 dB with a gain flatness of ±1dB over a frequency range from 3 to 18 GHz.The return losses S11 and S22 are below-10dB in the designed frequency range.The output 1-dB compression point at 5 GHz is 13.3 dBm.The chip area is 0.95 mm2 and the power dissipation is 95 mW under a 3.5 V supply.

A Distributed Optimal Scheme Based on Local QoS for Web Service Composition

The goal of web service composition is to choose an optimal scheme according to Quantity of Service （QoS） which selects instances in a distributed network. The networks are clustered with some web services such as ontologies, algorithms and rule engines with similar function and interfaces. In this scheme, web services acted as candidate service construct a distributed model which can＇t obtain the global services＇ information. The model is utilized to choose instances according to local QoS information in the progress of service composition. Some QoS matrixes are used to record and compare the instance paths and then choose a better one. Simulation result has proven that our ~pproach has a tradeoff between efficiency and ~quality.

Mean-field Theory for Some Bus Transport Networks with Random Overlapping Clique Structure

Transport networks, such as railway networks and airport networks, are a kind of random network with complex topology. Recently, more and more scholars paid attention to various kinds of transport networks and try to explore their inherent characteristics. Here we study the exponential properties of a recently introduced Bus Transport Networks （BTNs） evolution model with random overlapping clique structure, which gives a possible explanation for the observed exponential distribution of the connectivities of some BTNs of three major cities in China. Applying mean-field theory, we analyze the BTNs model and prove that this model has the character of exponential distribution of the connectivities, and develop a method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the exponents. By comparing mean-field based theoretic results with the statistical data of real BTNs, we observe that, as a whole, both of their data show similar character of exponential distribution of the connectivities, and their exponents have same order of magnitude, which show the availability of the analytical result of this paper.

A statistical end-to-end performance model for networks with complex topologies

Network calculus provides new tools for performance analysis of networks, but analyzing networks with complex topologies is a challenging research issue using statistical network calculus. A service model is proposed to characterize a service process of network with complex topologies. To obtain closed-form expression of statistical end-to-end performance bounds for a wide range of traffic source models, the traffic model and service model are expanded according to error function. Based on the proposed models, the explicit end-to-end delay bound of Fractional Brownian Motion（FBM） traffic is derived, the factors that affect the delay bound are analyzed, and a comparison between theoretical and simulation results is performed. The results illustrate that the proposed models not only fit the network behaviors well, but also facilitate the network performance analysis.

Distributed Chunk-Based Optimization for MultiCarrier Ultra-Dense Networks

In this paper,a distributed chunkbased optimization algorithm is proposed for the resource allocation in broadband ultra-dense small cell networks.Based on the proposed algorithm,the power and subcarrier allocation problems are jointly optimized.In order to make the resource allocation suitable for large scale networks,the optimization problem is decomposed first based on an effective decomposition algorithm named optimal condition decomposition(OCD) algorithm.Furthermore,aiming at reducing implementation complexity,the subcarriers are divided into chunks and are allocated chunk by chunk.The simulation results show that the proposed algorithm achieves more superior performance than uniform power allocation scheme and Lagrange relaxation method,and then the proposed algorithm can strike a balance between the complexity and performance of the multi-carrier Ultra-Dense Networks.

Dynamic Distribution Model with Prime Granularity for Parallel Computing

Dynamic distribution model is one of the best schemes for parallel volume rendering. How- ever, in homogeneous cluster system.since the granularity is traditionally identical, all processors communicate almost simultaneously and computation load may lose balance. Due to problems above, a dynamic distribution model with prime granularity for parallel computing is presented. Granularities of each processor are relatively prime, and related theories are introduced. A high parallel performance can be achieved by minimizing network competition and using a load balancing strategy that ensures all processors finish almost simultaneously. Based on Master-Slave-Gleaner ( MSG) scheme, the parallel Splatting Algorithm for volume rendering is used to test the model on IBM Cluster 1350 system. The experimental results show that the model can bring a considerable improvement in performance, including computation efficiency, total execution time, speed, and load balancing.

Internet of Things for Demand Side Management

The introduction of new kinds of energy mixes to the electricity grid is a challenging environmental task for present and future generations as they fight the pollution and global warming issues associated with urbanization. Individual appliances and whole buildings that continuously incorporate local intelligence which originates from the new technologies of Internet of Things are the new infrastructure that this integration is based on. Smart Electricity Grids are becoming more intensively integrated with tertiary building energy management systems and distributed energy generators such as wind and solar. This new smart network type harnesses the loT （lnternet of Things） principles by generating a new network made of active elements combined with the necessary control and distributed coordination mechanisms. This new self-organized overlay network of connected DER （distributed energy resources） allows for the seamless management and control of the active grid as well as the efficient coordination and exploration of single and aggregated technical prosumer potential （generation and consumption） to participate in energy balancing and other distributed grid related services, applying energy management strategies based on control and predict of the DERs behavior for facing demand side management issues.

Tangential stress analysis of myocardial wall by finite element method

A novel method is presented to build the triangular surface model and calculate the tangential stress and strain of myocardial wall ,which can be further used to reflect the left ventricle twisting—a sensitive index to assess the systolic and diastolic function of heart. Firstly, a point distribution model is used to obtain the feature points of the ventricular surface in medical images. Secondly, the surface model is constructed by triangular mesh, and then the subdivision strategy is introduced to refine the model. Thirdly, plane projection and finite element method(FEM) are applied to calculate the tangential stress and strain.Finally, the distribution of tangential modulus of elasticity is discussed. The stimulation results show that the proposed method can be used to compute the tangential stress and strain of myocardial wall effectively and the computing result is consistent with the results mentioned in the literatures.

Interference Coordination for Secrecy Enhancement in Random Wireless Networks

The co-channel interference modeling is vital for evaluating the secrecy performance in random wireless networks,where the legitimate nodes and eavesdroppers are randomly distributed.In this paper,a new interference model is proposed from the userdominant perspective.The model can provide a better analytical assessment of secrecy performance with interference coordination for the presence of eavesdroppers.The typical legitimate is assumed to be located at the origin,and chooses the closest base station(BS) as its serving BS.The field of interferers is obtained by excluding the desired BSs(including the serving BS and its cooperative BS(s)).In contract with the exiting interference model,it is assumed that desired BSs and interferers belong to the same Poisson Point Process(PPP),and eavesdroppers are distributed according to another independent PPP.Based on this model,the average secrecy transmission capacity is derived in simply analytical forms with interference coordination.Analysis and simulation results show that the secrecy performance can be significantly enhanced by exploiting interference coordination.Furthermore,the average secrecy transmission capacity increases with increasing number of cooperative BSs.

Nonlinear magnetic network models for flux-switching permanent magnet machines

In this paper, firstly, a basic nonlinear magnetic network model considering iron saturations is proposed for a three-phase 12-stator-slot/10-rotor-pole flux-switching permanent magnet(FSPM) machine. This model is built under cylindrical coordinates and enables the open-circuit air-gap flux-density distributions, phase permanent magnet(PM) flux-linkage, and electromotive-force(EMF) to be predicted with acceptable accuracy. However, large discrepancies are found in the predictions of armature inductances. Then, the basic model is modified by taking into account the localized saturation effect. As a result, the electromagnetic performance can be predicted more accurately, especially for the air-gap flux-density distributions. Furthermore, two improved models are proposed by adding bypass-bridge branches in stator network, to enhance the calculating accuracy of both saturated and unsaturated armature inductances. Finally, the predicted results from the four magnetic network models are validated by both 2D finite element analysis(FEA) and experimental measurements on a machine prototype. Overall, comparisons indicate that the model with bypass-bridge branches between stator teeth and back irons exhibits best performances.

Low-Dimensional SIR Epidemic Models with Demographics on Heterogeneous Networks

To investigate the impacts of demographics on the spread of infectious diseases, a susceptib- le-infectious-recovered （SIR） pairwise model on heterogeneous networks is established. This model is reduced by using the probability generating function and moment closure approximations. The basic reproduction number of the low-dimensional model is derived to rely on the recruitment and death rate, the first and second moments of newcomers＇ degree distribution. Sensitivity analysis for the basic reproduction number is performed, which indicates that a larger variance of newcomers＇ degrees can lead to an epidemic outbreak with a smaller transmission rate, and contribute to a slight decrease of the final density of infectious nodes with a larger transmission rate. Besides, stochastic simulations indicate that the low-dimensional model based on the log-normal moment closure assumption can well capture important properties of an epidemic. And the authors discover that a larger recruitment rate can inhibit the spread of disease.