随着输变电设备状态监测的广度和深度不断加强,收集的监测数据越来越多,逐渐形成了智能电网状态监测大数据。然而,如何有效的存储和分析状态监测大数据是大数据在状态监测领域应用的关键问题之一。基于云计算平台并考虑状态监测数据的特...随着输变电设备状态监测的广度和深度不断加强,收集的监测数据越来越多,逐渐形成了智能电网状态监测大数据。然而,如何有效的存储和分析状态监测大数据是大数据在状态监测领域应用的关键问题之一。基于云计算平台并考虑状态监测数据的特点,将监测数据海量小文件组合成大的序列文件,并压缩存储,从而提高存储和处理效率。针对状态监测大数据价值密度低的特点,首先利用分形理论对监测数据降维处理,提取时域和频域特征量,并使用密度聚类算法DBSCAN(Density-Based Spatial Clustering of Applications with Noise)对样本数据聚类划分,提取不同聚类的特征数据;然后结合云平台的数据处理能力设计MapReduce并行算法,实现状态监测大数据的聚类划分,从而有助于从大数据中发现有价值的特征量;最后,利用大数据聚类结果更新和丰富样本特征数据。实验结果表明该方法可以有效存储状态监测大数据并对其聚类划分,对提高设备的状态评估及故障诊断水平具有一定辅助作用。展开更多
面向企业网或校园网的移动办公与存储的网盘系统有着广泛的市场需求,传统的网盘技术在性能、用户共享、安全性、可扩展性等方面存在诸多缺陷。针对这些不足,本文提出了一种基于云存储的高性能网盘系统架构:采用分布式文件系统MooseFS实...面向企业网或校园网的移动办公与存储的网盘系统有着广泛的市场需求,传统的网盘技术在性能、用户共享、安全性、可扩展性等方面存在诸多缺陷。针对这些不足,本文提出了一种基于云存储的高性能网盘系统架构:采用分布式文件系统MooseFS实现用户数据存储与访问的集群架构;在安全性方面,结合SAMBA实现用户权限管理,用户数据存储支持128 bit AES加密,SSH保证了传输链路的安全;最后,结合用户的实际需求,提供基于Web的访问方式以及客户端的同步盘模式。结果表明,系统在性能、安全性、可扩展性等多方面具有显著优势。展开更多
In this paper,a typical-operation-curve generation method of a hydrogen energy storage system operating under the mode of stabilizing wind power fluctuations is proposed.This method is used to optimize the power and c...In this paper,a typical-operation-curve generation method of a hydrogen energy storage system operating under the mode of stabilizing wind power fluctuations is proposed.This method is used to optimize the power and capacity configuration of the energy storage system.The time series curves of the charging and discharging powers of the hydrogen energy storage are obtained by EMD decomposition,and the curves are classified according to the similarities and differences of the characteristic parameters in different time periods.After the classification,typical charging and discharging power values of each type of curve at each moment are obtained by a cloud model,and then,typical operation curves of each type are obtained by integration.On this basis,the power and capacity of the energy storage system are optimized with the objective of economic optimization through the MATLAB CPLEX toolbox.Combined with the measured data of a wind farm with an installed capacity of 400 MW in Northeast China,the validity and rationality of the typical operation curve generation method proposed in this paper are verified.展开更多
Considering the nonlinear, multifunctional properties of double-flywheel with closed- loop control, a two-step method including clustering and principal component analysis is proposed to detect the two faults in the m...Considering the nonlinear, multifunctional properties of double-flywheel with closed- loop control, a two-step method including clustering and principal component analysis is proposed to detect the two faults in the multifunctional flywheels. At the first step of the proposed algorithm, clustering is taken as feature recognition to check the instructions of ＂integrated power and attitude control＂ system, such as attitude control, energy storage or energy discharge. These commands will ask the flywheel system to work in different operation modes. Therefore, the relationship of parameters in different operations can define the cluster structure of training data. Ordering points to identify the clustering structure （OPTICS） can automatically identify these clusters by the reachability-plot. K-means algorithm can divide the training data into the corresponding operations according to the teachability-plot. Finally, the last step of proposed model is used to define the rela- tionship of parameters in each operation through the principal component analysis （PCA） method. Compared with the PCA model, the proposed approach is capable of identifying the new clusters and learning the new behavior of incoming data. The simulation results show that it can effectively detect the faults in the multifunctional flywheels system.展开更多
文摘随着输变电设备状态监测的广度和深度不断加强,收集的监测数据越来越多,逐渐形成了智能电网状态监测大数据。然而,如何有效的存储和分析状态监测大数据是大数据在状态监测领域应用的关键问题之一。基于云计算平台并考虑状态监测数据的特点,将监测数据海量小文件组合成大的序列文件,并压缩存储,从而提高存储和处理效率。针对状态监测大数据价值密度低的特点,首先利用分形理论对监测数据降维处理,提取时域和频域特征量,并使用密度聚类算法DBSCAN(Density-Based Spatial Clustering of Applications with Noise)对样本数据聚类划分,提取不同聚类的特征数据;然后结合云平台的数据处理能力设计MapReduce并行算法,实现状态监测大数据的聚类划分,从而有助于从大数据中发现有价值的特征量;最后,利用大数据聚类结果更新和丰富样本特征数据。实验结果表明该方法可以有效存储状态监测大数据并对其聚类划分,对提高设备的状态评估及故障诊断水平具有一定辅助作用。
文摘面向企业网或校园网的移动办公与存储的网盘系统有着广泛的市场需求,传统的网盘技术在性能、用户共享、安全性、可扩展性等方面存在诸多缺陷。针对这些不足,本文提出了一种基于云存储的高性能网盘系统架构:采用分布式文件系统MooseFS实现用户数据存储与访问的集群架构;在安全性方面,结合SAMBA实现用户权限管理,用户数据存储支持128 bit AES加密,SSH保证了传输链路的安全;最后,结合用户的实际需求,提供基于Web的访问方式以及客户端的同步盘模式。结果表明,系统在性能、安全性、可扩展性等多方面具有显著优势。
基金This work was supported by the National Key Research and Development Program of China(Materials and Process Basis of Electrolytic Hydrogen Production from Fluctuating Power Sources such as Photovoltaic/Wind Power,No.2021YFB4000100).
文摘In this paper,a typical-operation-curve generation method of a hydrogen energy storage system operating under the mode of stabilizing wind power fluctuations is proposed.This method is used to optimize the power and capacity configuration of the energy storage system.The time series curves of the charging and discharging powers of the hydrogen energy storage are obtained by EMD decomposition,and the curves are classified according to the similarities and differences of the characteristic parameters in different time periods.After the classification,typical charging and discharging power values of each type of curve at each moment are obtained by a cloud model,and then,typical operation curves of each type are obtained by integration.On this basis,the power and capacity of the energy storage system are optimized with the objective of economic optimization through the MATLAB CPLEX toolbox.Combined with the measured data of a wind farm with an installed capacity of 400 MW in Northeast China,the validity and rationality of the typical operation curve generation method proposed in this paper are verified.
基金supported by the National Basic Research Program of China(No.2012CB720003)
文摘Considering the nonlinear, multifunctional properties of double-flywheel with closed- loop control, a two-step method including clustering and principal component analysis is proposed to detect the two faults in the multifunctional flywheels. At the first step of the proposed algorithm, clustering is taken as feature recognition to check the instructions of ＂integrated power and attitude control＂ system, such as attitude control, energy storage or energy discharge. These commands will ask the flywheel system to work in different operation modes. Therefore, the relationship of parameters in different operations can define the cluster structure of training data. Ordering points to identify the clustering structure （OPTICS） can automatically identify these clusters by the reachability-plot. K-means algorithm can divide the training data into the corresponding operations according to the teachability-plot. Finally, the last step of proposed model is used to define the rela- tionship of parameters in each operation through the principal component analysis （PCA） method. Compared with the PCA model, the proposed approach is capable of identifying the new clusters and learning the new behavior of incoming data. The simulation results show that it can effectively detect the faults in the multifunctional flywheels system.
