Massive deployment of distributed energy resources (DER) through zero-inertia power electronic converters has made the power grid vulnerable to frequency instabilities and in particular inter-area oscillations. Low-fr...
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ISBN:
(纸本)9781728161273
Massive deployment of distributed energy resources (DER) through zero-inertia power electronic converters has made the power grid vulnerable to frequency instabilities and in particular inter-area oscillations. Low-frequency oscillations are of major concerns as they have the potential to limit maximum power transfer, and even cause blackouts. This paper presents a novel distributed control algorithm called distributed frequency deviation control (DFDC) based on local frequency deviation from the estimate of the average frequency of the network. The efficacy of the control unit is demonstrated via modal analyses and time-domain simulations. The results show that all the inter-area oscillation modes are damped for all the test cases without affecting the other dynamic modes of the system.
distributed-generation (DG) facilities widely employ gas-turbine (GTU) and gas-piston (GPU) generator sets (GS) capable of islanded operation or running in parallel with the grid. This paper considers various operatin...
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ISBN:
(纸本)9781728145907
distributed-generation (DG) facilities widely employ gas-turbine (GTU) and gas-piston (GPU) generator sets (GS) capable of islanded operation or running in parallel with the grid. This paper considers various operating conditions that may cause significant GS load throw and load-shedding that entails disconnecting and subsequent consumer power outage. Analysis reveals which GTU/GPU design features may result in damage and/or outage if the unit is exposed to external disturbances in the adjacent grid. It also demonstrates the efficiency of comprehensive solutions that use energy storage and variable-frequency motor-based drives to prevent GS damage and/or outage. Besides, the paper substantiates the need of, and proposes DG GS maneuverability requirements for more efficient use.
Companies built IT Center and operated an on-premise system because IT is a kind of asset. But the pace of change in management is accelerating and the pressure on cost efficiency in the IT sector is increasing. Cloud...
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Companies built IT Center and operated an on-premise system because IT is a kind of asset. But the pace of change in management is accelerating and the pressure on cost efficiency in the IT sector is increasing. Cloud computing is considered to secure system reliability and reduce management costs. IT resources can be efficiently utilized and paid for used. Cloud computing for each service unit was considered as a way to meet an efficient utilization of IT resources without compromising existing system reliability when providing new services. Cloud system enables real-time orchestration, and has excellent security. As a hybrid method that implemented cloud computing while maintaining the existing infrastructure, it was possible to operate an uninterrupted system as a result of system construction Therefore, companies were deploying and migrating their intranet services to cloud servers. However, it is also true that cloud migration makes system complexity increase, and system reliability is compromised by the increase of management points especially securities. It is necessary to learn about practice-oriented cloud migration and how to maintain mixed security policies when maintaining on-premises systems is effective.
Feedback-based optimization algorithms use real-time measurements to update the optimal control for the underlying system which may not be fully identified. Recently, we have developed a distributed feedback-based alg...
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ISBN:
(纸本)9781728161273
Feedback-based optimization algorithms use real-time measurements to update the optimal control for the underlying system which may not be fully identified. Recently, we have developed a distributed feedback-based algorithm [1] that avoids the requirement of fast communication between central computing and local actuator/sensor agents. This paper extends the work by greatly reducing the number of copies of variables involved in the distributed feedback-based algorithm, which results in faster convergence and lower communication requirement. The main idea is to leverage the specific structural properties of the admittance matrix for distribution systems with tree network topology. We also show the effectiveness of the proposed algorithm in simulations.
Edge computing is a promising cloud computing paradigm that reduces computing latency by deploying edge servers near data sources and users, which is of great importance to implement delay-sensitive applications like ...
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We describe the artifact, publicly available at [1], that implements the proposal in [2], and the reproduction of the experimental results. It is an extended and distributed version of the Mondrian anonymization algor...
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We describe the artifact, publicly available at [1], that implements the proposal in [2], and the reproduction of the experimental results. It is an extended and distributed version of the Mondrian anonymization algorithm. Our solution anonymizes large datasets by partitioning data among workers in a distributed setting. It provides parallel execution on a dynamically chosen number of workers, limiting their interaction and data exchange.
Large number of physical systems such as electric vehicles and energy storage elements are connected to the main grid. Monitoring and regulating of this interconnected cyberphysical power system state within a short p...
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Large number of physical systems such as electric vehicles and energy storage elements are connected to the main grid. Monitoring and regulating of this interconnected cyberphysical power system state within a short period of time is a challenging task, and it can perform by the process of grid state estimation. This paper proposes a multi-agent based optimal distributed dynamic state estimation algorithm for smart grid incorporating intermittent electric vehicles and turbines. After mathematically representation of large-scale grid systems into a compact state-space framework, the smart sensors are installed to get real-time measurements which are manipulated by environmental noise. A distributed smart grid state estimation process is developed and verified. Each agent learns and runs an innovation and consensus type distributed scheme based on local measurements, previous and neighbouring estimated grid states. In this way, each local agent estimated grid state converges to the global consensus estimation over time. The proposed algorithm can effectively reconstruct the original grid states.
The proceedings contain 130 papers. The special focus in this conference is on Intelligent computing. The topics include: A Comparable Study on Dimensionality Reduction Methods for Endmember Extraction;Hyperspectral I...
ISBN:
(纸本)9783030845315
The proceedings contain 130 papers. The special focus in this conference is on Intelligent computing. The topics include: A Comparable Study on Dimensionality Reduction Methods for Endmember Extraction;Hyperspectral Image Classification with Locally Linear Embedding, 2D Spatial Filtering, and SVM;a Hierarchical Retrieval Method Based on Hash Table for Audio Fingerprinting;Automatic Extraction of Document Information Based on OCR and Image Registration Technology;using Simplified Slime Mould Algorithm for Wireless Sensor Network Coverage Problem;super-Large Medical Image Storage and Display Technology Based on Concentrated Points of Interest;person Re-identification Based on Hash;a Robust and Automatic Recognition Method of Pointer Instruments in Power System;partial Distillation of Deep Feature for Unsupervised Image Anomaly Detection and Segmentation;an Evolutionary Neuron Model with Dendritic Computation for Classification and Prediction;Speech Recognition Method for Home Service Robots Based on CLSTM-HMM Hybrid Acoustic Model;serialized Local Feature Representation Learning for Infrared-Visible Person Re-identification;a Novel Decision Mechanism for Image Edge Detection;Rapid Earthquake Assessment from Satellite Imagery Using RPN and Yolo v3;attention-Based Deep Multi-scale Network for Plant Leaf Recognition;short Video Users’ Personal Privacy Leakage and Protection Measures;An Efficient Video Steganography Method Based on HEVC;analysis on the Application of Blockchain Technology in Ideological and Political Education in Universities;parallel Security Video Streaming in Cloud Server Environment;An Efficient Video Steganography Scheme for Data Protection in H.265/HEVC;an Improved Genetic Algorithm for distributed Job Shop Scheduling Problem;A Robust Lossless Steganography Method Based on H.264/AVC;detection of Pointing Position by Omnidirectional Camera.
I/O Memory Management Unit (IOMMU) is im-portant hardware support for I/O virtualization, and it is widely used in device passthrough. However, IOMMU sacrifices memory utilization due to the static mapping requirement...
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I/O Memory Management Unit (IOMMU) is im-portant hardware support for I/O virtualization, and it is widely used in device passthrough. However, IOMMU sacrifices memory utilization due to the static mapping requirement. Moreover, it lacks DMA security guarantees inside the guest. IOMMU virtual-ization is a decent solution among existing studies to address these problems. Nevertheless, pure software IOMMU virtualization suffers from high overhead, while hardware-assisted IOMMU virtualization needs complex hardware redesign. Therefore, en-abling efficient design with low hardware overhead remains chal-lenging. In this paper, we propose an efficient hardware-software co-design of IOMMU virtualization, named LA-vIOMMU, to achieve high I/O performance with low hardware overhead. LA-vIOMMU is designed based on the existing vIOMMU mode and can be adapted to other platforms. We describe the design and implementation of LA-vIOMMU. The LA-vIOMMU combines hardware expansion and software optimization to minimize the performance cost. Furthermore, we evaluate the effectiveness and security of LA-vIOMMU and analyze the advantages compared with the existing design in x86. The experiment results show that LA-vIOMMU can get superior throughput than existing software approaches and achieve throughput pretty close to hardware-assisted virtualization with fewer hardware design changes and less verification overhead.
Network virtualization recognized as an enabling technology for the forthcoming networks is utterly popular. One of the main challenges of network virtualization is called the virtual network embedding problem. Virtua...
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ISBN:
(纸本)9781728185262
Network virtualization recognized as an enabling technology for the forthcoming networks is utterly popular. One of the main challenges of network virtualization is called the virtual network embedding problem. Virtual network embedding (VNE) aims to allocate a set of virtual machines onto a set of interconnected physical hardware in the cloud computing environment. Traditional exact solutions, considered as a time-consuming process to achieve a global optimal solution, have been proofed to be NP-hard. On the other hand, some existing heuristic solutions tend to decouple VNE problems into two stages: virtual node mapping (VNoM) and virtual link mapping (VLiM). Undoubtedly, these kinds of decomposition would result in low acceptance ratio and inefficient substrate resource utilization. In this paper, we propose a distributedparallel Genetic Algorithm combined with graph theory for solving VNE in one-stage. Our proposed algorithm achieves better performance than previous baseline solutions while meeting the stringent time requirements for online VNE problems.
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