关注区可变的实时仿真方法与平台

交直流混合电网的实时仿真既要考虑电力电子设备的开关特性,又要保证适应较大的电网规模,在实际工程中面临诸多困难.给子网络赋予动态可变的关注标志,对关注子网络采用存储压力小的节点消去法,对非关注子网络采用计算量少的线性组合法,从而保证骨架型节点电压法的实用性.在Xilinx公司的Virtex-7 FPGA VC709开发板中,采用无缝的并行化仿真计算程序对接方式和灵活的结构参数查询方法解决了现场可编程逻辑门阵列资源的紧缺问题,设计了一种关注区可变的实时数字仿真平台.以典型的交直流混合电网为例,仿真验证了所提方法的可行性与所研发平台的有效性.     

考虑样本类别不平衡的电网故障事件智能识别方法

电网中不同设备的故障概率存在差异,影响智能诊断技术的准确性.为解决此问题,提出了一种基于代价敏感学习和模型自适应选择融合的电网故障事件智能识别方法.首先,利用Word2vec模型将预处理后的电网告警信息向量化,并搭建2个双向长短期记忆网络作为基础分类器;然后,设计代价敏感损失函数,将交叉熵损失函数与代价敏感损失函数分别应用于2个分类器中;最后,提出一种模型自适应选择融合法,融合上述分类器,得到故障事件识别结果.实际数据测试表明,所提方法能够有效降低故障事件识别中样本类别不平衡的影响.     

基于改进自注意力机制生成对抗网络的智能电网GPS欺骗攻击防御方法

为了避免全球定位系统欺骗攻击(GSA)对相量测量装置造成的危害,提出了一种基于改进自注意力机制生成对抗网络(SAGAN)的智能电网GSA防御方法.首先,通过引入深度学习参数,构建了改进网络-物理模型,利用历史数据计算得到当前时刻的量测值.然后,在SAGAN的生成器和判别器网络中分别融入一个时间注意力模块,提出了一种用于实现网络-物理模型的改进SAGAN防御方法.通过训练改进SAGAN,得到一对判别器和生成器,利用判别器检测采集的量测值是否遭受GSA,当检测到攻击时,利用生成器生成的数据替换欺骗数据,从而实现智能电网对GSA的主动防御.最后,基于IEEE 14节点和IEEE 118节点系统进行仿真测试,结果验证了所提方法的可行性和有效性.     

冲压成形仿真过程中有限元网格模型的建立

网格模型对冲压成形模拟的精度和效率影响极大 ,文中阐述了有限元网格模型建立的方法 ,并从单元尺寸、单元类型、自适应网格再划分技术等方面论述了如何解决精度与效率的问题。     

Semantic weak signal tracing

The weak signal concept according to Ansoff has the aim to advance strategic early warning. It enables to predict the appearance of events in advance that are relevant for an organization. An example is to predict the appearance of a new and relevant technology for a research organization. Existing approaches detect weak signals based on an environmental scanning procedure that considers textual information from the internet. This is because about 80% of all data in the internet are textual information. The texts are processed by a specific clustering approach where clusters that represent weak signals are identified. In contrast to these related approaches, we propose a new methodology that investigates a sequence of clusters measured at successive points in time. This enables to trace the development of weak signals over time and thus, it enables to identify relevant weak signal developments for organization’s decision making in strategic early warning environment.     

Dynamic replica placement and selection strategies in data grids— A comprehensive survey

Data replication techniques are used in data grid to reduce makespan, storage consumption, access latency and network bandwidth. Data replication enhances data availability and thereby increases the system reliability. There are two steps involved in data replication, namely, replica placement and replica selection. Replica placement involves identifying the best possible node to duplicate data based on network latency and user request. Replica selection involves selecting the best replica location to access the data for job execution in the data grid. Various replica placement and selection algorithms are available in the literature. These algorithms measure and analyze different parameters such as bandwidth consumption, access cost, scalability, execution time, storage consumption and makespan. In this paper, various replica placement and selection strategies along with their merits and demerits are discussed. This paper also analyses the performance of various strategies with respect to the parameters mentioned above. In particular, this paper focuses on the dynamic replica placement and selection strategies in the data grid environment.     

Smart pricing scheme: A multi-layered scoring rule application

Defining appropriate pricing strategy for smart environment is important and complex task at the same time. It holds the primal fraction in Demand Response (DR) program. In our work, we devise an incentive based smart dynamic pricing scheme for consumers facilitating a multi-layered scoring rule. The proposed strategy characterizes both incentive based DR and price based DR programs facilities. This mechanism is applied between consumer agents (CA) to electricity provider agent (EP) and EP to Generation Company (GENCO). Based on the Continuous Ranked Probability Score (CRPS), a hierarchical scoring system is formed among these entities, CA–EP–GENCO. As CA receives the dynamic day-ahead pricing signal from EP, it will schedule the household appliances to lower price period and report the prediction in a form of a probability distribution function to EP. EP, in similar way reports the aggregated demand prediction to GENCO. Finally, GENCO computes the base discount after running a cost-optimization problem. GENCO will reward EP with a fraction of discount based on their prediction accuracy. EP will do the same to CA based on how truthful they were reporting their intentions on device scheduling. The method is tested on real data provided by Ontario Power Company and we show that this scheme is capable to reduce energy consumption and consumers’ payment.     

Text classification using genetic algorithm oriented latent semantic features

In this paper, genetic algorithm oriented latent semantic features (GALSF) are proposed to obtain better representation of documents in text classification. The proposed approach consists of feature selection and feature transformation stages. The first stage is carried out using the state-of-the-art filter-based methods. The second stage employs latent semantic indexing (LSI) empowered by genetic algorithm such that a better projection is attained using appropriate singular vectors, which are not limited to the ones corresponding to the largest singular values, unlike standard LSI approach. In this way, the singular vectors with small singular values may also be used for projection whereas the vectors with large singular values may be eliminated as well to obtain better discrimination. Experimental results demonstrate that GALSF outperforms both LSI and filter-based feature selection methods on benchmark datasets for various feature dimensions.     

基于随机词汇迭代模型的POI分类检索

从特征选择、局部区域划分和词汇语义相似性计算入手,利用随机词汇迭代模型(random terms iterativemodel,RTIM)进行海量兴趣点(point of interest,POI)文本分类.通过词汇频度、集中度和离散度方法筛选出特征词汇;依据文本与各POI类别间的相似度进行局部区域划分;在每个局部区域内基于词汇在文本中的排列顺序构建词频向量,基于词频向量中词频的随机删除和重构,获取特征映射矩阵;通过特征映射矩阵将文本转为特征向量,并采用SVM分类器进行POI文本分类.实验证明,该方法有效提升了POI文本分类准确性和覆盖率.     

一种电网综合展现可视化系统的设计与应用

笔者在分析一种电网信息综合展现可视化系统建设目标和设计思路的基础上,详细阐述该系统的总体架构、业务架构、数据架构、技术架构、部署架构设计。该系统由智能信息集成模块、视频监控模块和综合展现可视化模块三部分组成,基于先进的多层架构体系和SOA构架模型,以ETL、数据挖掘、视频、GIS、图形图像技术为依托,实现电网信息视频、温湿度、风速、雨量气象环境、负荷、潮流等电网运行信息以及安防消防等各类辅助决策信息有逻辑的、互联互通的、交互的和实时的可视化展现,满足业务运行和对外展示的可视化需求,建成电网公司“汇集信息、全面监控、专业联动、统一展现”的电网信息综合展现可视化系统。该系统支持视频、GIS专题图和图形图表等多种展现方式,适用于不同的需求场景,在海南电网公司的实际应用结果证明了其可行性。