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检索条件"任意字段=International Conference on Parallel Distributed and Grid Computing"

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Adequacy Assessment of grid-Connected Nanogrid

Adequacy Assessment of Grid-Connected Nanogrid

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international conference on Cyber Physical, Computer and Automation Systems, CPCAS 2019

作者： Wijayanto, Danang Leksono, Edi Widyotriatmo, Augie Bandung Institute of Technology Jawa Barat Bandung40116 Indonesia

ISBN: (纸本)9789813340619

Microgrid, an autonomous power distribution system that utilizes distributed generation, offers advantages by means of increasing of reliability, efficiency, etc. Currently, the microgrid implementation extends to a smaller scale called nanogrid. Increasing number of microgrids and nanogrids raises the need for a measurement tool that can be used to assess the performance level of a microgrid system so that it can be used to compare one system with another, to measure the ups and downs of a system’s performance over a time period, and to use the evaluation result as the base of further improvement. This paper offers a method for evaluating the reliability of a nanogrid system using a Markov model. The reliability indicator selected in this study is the loss of energy expectation (LOLE), which is considered to be more suitable for this purpose. As the validation of this model, the reliability evaluation of a nanogrid in the energy management laboratory, Institut Teknologi Bandung (ITB) is reported. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reliability

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grid Scrutinize Based Heuristic Sensor Node Scheduling Protocol with Partial Coverage Constraint in WSN 4th

Grid Scrutinize Based Heuristic Sensor Node Scheduling Proto...

引用

4th international conference on Internet of Things and Connected Technologies (ICIoTCT)

作者： Sharma, Anamika Chauhan, Siddhartha Natl Inst Technol Hamirpur Comp Sci & Engn Dept Hamirpur Himachal Prades India

ISBN: (纸本)9783030398750;9783030398743

Random deployment of wireless sensor nodes' with high density to enhance the coverage area and lifetime imposes many challenges inwireless sensor networks such as coverage redundancy, redundancy in packet generation, radio channel contention, high network cost and network congestion. This paper presents a distributed grid Scrutinize based Heuristic Sensor Node Scheduling (GS-HSS) coverage protocol to design the efficient node duty schedules that maximize the area coverage andminimize the energy expenditure of sensor nodes. GS-HSS also detects and eliminates the coverage redundancy tomitigate the problem of data and packet generation redundancy. Simulation results show that GS-HSS outperforms in terms of average scheduling rounds and energy expenditure.

关键词： Coverage area Customize sensing range Node scheduling Partial coverage Random deployment

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Fault isolation and location prediction using support vector machine and gaussian process regression for meshed AC microgrid

Fault isolation and location prediction using support vector...

引用

2020 IEEE international conference on computing, Power and Communication Technologies, GUCON 2020

作者： Srivastava, Adhishree Parida, S.K. Indian Institute of Technology Electrical Engineering Department Patna India

ISBN: (纸本)9781728150703

Better reliability of power is assured with the inculcation of distributed generations in a distribution network. Smart sensors and latest grid communication protocols has led to the development of intelligent microgrids (MG). Protection of such grids are a key concern for power engineers, as conventional protection schemes fails while operating in microgrids. This paper presents, data analysis based fault isolation and its location prognosis. The proposed approach takes post fault, one cycle three phase voltage and current measurements as the inputs for developing a fault isolation module (FIM) and fault locator module (FLM). These modules are supposed to be available at central protection system (CPS), designed through meticulous data training, using Gaussian process regression (GPR) for fault location prediction and support vector machine (SVM) for fault identification. The effectiveness of proposed methodology is represented by considering practical grid scenarios such as varying load and DG penetration. A 14 bus meshed AC microgrid structure has been modelled in SIMULINK having three DGs and two grid sources. Data analytics tools of MATLAB 2018a has been explored to develop machine learning based protection strategy for microgrids. © 2020 IEEE.

关键词： distributed power generation

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Transmission Line Decoupling Based parallel Simulation Method of an Active Distribution Network

Transmission Line Decoupling Based Parallel Simulation Metho...

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Sustainable Power and Energy conference (iSPEC)

作者： Songtao Wei Zhichun Yang Guannan Lou Ke Li Fan Yang Yu Shen School of Electrical Engineering Southeast University Nanjing China Electric Power Research Institute State Grid Hubei Electric Power Co. Ltd Wuhan China

ISBN: (纸本)9781665414401

Now that a large number of distributed generations (DGs) and nonlinear loads are included in the distribution network, the current active distribution network gradually presents the characteristics of multiple time scales and wide-ranging frequency domain, which undoubtedly increases the complexity of electromagnetic transient (EMT) simulation. Because of this, to improve the efficiency of electromagnetic transient simulation in the condition, this study proposes a network decoupling method that can be suitable for parallel simulation of distribution networks. According to the characteristics of distributed parameter transmission lines, the study introduces a linear interpolation algorithm into the traditional Bergeron model to match the requirements of short-distance line simulation in distribution networks. In addition, applying the improved model to the decoupling of distribution networks, a novel parallel simulation interface of distribution networks is designed and established, and a multi-area decoupling simulation of the distribution network was realized. Finally, the proposed decoupling method is turn out to be more accurate and efficient than the traditional method and more suitable for parallel computing of distribution networks by a simulation example of IEEE13 Node Test Feeders.

关键词： Adaptation models Interpolation Power transmission lines Computational modeling Simulation Distribution networks parallel processing

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Neural Network-Based DDoS Detection on Edge computing Architecture

Neural Network-Based DDoS Detection on Edge Computing Archit...

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international conference on Applied Machine Learning (ICAML)

作者： Xiao Zhang Xiaoming Chen Yuxiong He Youhuai Wang Yong Cai Bo Li State Grid Hubei Electric Power Co. Ltd. Wuhan China Beijing Kedong Electric Power Control System Co. Ltd. Beijing China

The safety of the power system is inherently vital, due to the high risk of the electronic power system. In the wave of digitization in recent years, many power systems have been digitized to a certain extent. Under this circumstance, network security is particularly important, in order to ensure the normal operation of the power system. However, with the development of the Internet, network security issues are becoming more and more serious. Among all kinds of network attacks, the distributed Denial of Service (DDoS) is a major threat. Once, attackers used huge volumes of traffic in short time to bring down the victim server. Now some attackers just use low volumes of traffic but for a long time to create trouble for attack detection. There are many methods for DDoS detection, but no one can fully detect it because of the huge volumes of traffic. In order to better detect DDoS and make sure the safety of electronic power system, we propose a novel detection method based on neural network. The proposed model and its service are deployed to the edge cloud, which can improve the real-time performance for detection. The experiment results show that our model can detect attacks well and has good real-time performance.

关键词： Cloud computing Vocabulary Computational modeling Image edge detection Neural networks Network security Real-time systems

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Graceful Performance Degradation in Apache Storm 21st

Graceful Performance Degradation in Apache Storm

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21st international conference on parallel and distributed computing, Applications, and Technologies, PDCAT 2020

作者： HoseinyFarahabady, Mohammad Reza Taheri, Javid Zomaya, Albert Y. Tari, Zahir School of Computer Science Center for Distributed and High Performance Computing The University of Sydney SydneyNSW Australia Department of Mathematics and Computer Science Karlstad University Karlstad Sweden School of Science RMIT University MelbourneVIC Australia

ISBN: (纸本)9783030692438

The concept of stream data processing is becoming challenging in most business sectors where try to improve their operational efficiency by deriving valuable information from unstructured, yet, contentiously generated high volume raw data in an expected time spans. A modern streamlined data processing platform is required to execute analytical pipelines over a continues flow of data-items that might arrive in a high rate. In most cases, the platform is also expected to dynamically adapt to dynamic characteristics of the incoming traffic rates and the ever-changing condition of underlying computational resources while fulfill the tight latency constraints imposed by the end-users. Apache Storm has emerged as an important open source technology for performing stream processing with very tight latency constraints over a cluster of computing nodes. To increase the overall resource utilization, however, the service provider might be tempted to use a consolidation strategy to pack as many applications as possible in a (cloud-centric) cluster with limited number of working nodes. However, collocated applications can negatively compete with each other, for obtaining the resource capacity in a shared platform that, in turn, the result may lead to a severe performance degradation among all running applications. The main objective of this work is to develop an elastic solution in a modern stream processing ecosystem, for addressing the shared resource contention problem among collocated applications. We propose a mechanism, based on design principles of Model Predictive Control theory, for coping with the extreme conditions in which the collocated analytical applications have different quality of service (QoS) levels while the shared-resource interference is considered as a key performance limiting parameter. Experimental results confirm that the proposed controller can successfully enhance the p -99 latency of high priority applications by 67%, compared to the default round r

关键词： Storms

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Intelligent Vehicle to grid Based Plug-in Electric Vehicle with Cloud computing

Intelligent Vehicle to Grid Based Plug-in Electric Vehicle w...

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2020 international conference on Computer Science, Engineering and Applications, ICCSEA 2020

作者： Misra, Srikant Panigrahi, Pratap Kumar Ghosh, Saradindu GIET University Dept of EEE Gunupur India NIT Dept. of EE Durgapur India

ISBN: (纸本)9781728158303

The electric vehicle revolution is going to be the game-changer which is doing quite to reduce carbon emissions. Vehicle to grid (V2G) is specially designed to empower the utility grid by feeding back the stored energy from batteries of the vehicles to the grid. V2G technology reflects the bidirectional power flow between the utility grid and higher thrust batteries of vehicles. When a grid needs extra power it can draw from each individual vehicle when energy is abundant. It's a functional awareness once we consider that the maximum number of vehicles is parked in parking lots any point of time which reflects a huge amount of energy kept ideal without any use. This V2G will enables us self-sufficient by managing our own energy effectively through our process. It plays a crucial part in helping to 'balance' the grid. Under the scenario of a sustainable world, electric vehicles are one of the fundamental parts of the utility system by functioning as distributed energy sources in the vision of the smart grid. Electric vehicles can provide additional storage and enhance grid stability by pumping the required amount of additional power. With this process, the owner of the electric vehicle can earn some reward points in terms of cash. With the help of the electric vehicles movement in the existing grid, the amount of renewable energy inclusion to the system will be enhanced. Electric vehicles can stabilize the grid integration through penetration of return energy from the vehicle to grid during peak load time and during off-peak, it can store charge. V2G shows a significant role during load shedding. These kinds of distributed generation systems can be feasible to crucial load during an outage. This paper proposes a replacement of the traditional control arrangement of a battery system with an intelligent battery management and control system which is working in association with cloud computing. The proposed algorithm offers the computational allocation of PEV to work ef

关键词： Vehicle-to-grid

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11th international Symposium on parallel Architectures, Algorithms and Programming, PAAP 2020

11th International Symposium on Parallel Architectures, Algo...

引用

11th international Symposium on parallel Architectures, Algorithms and Programming, PAAP 2020

ISBN: (纸本)9789811600098

The proceedings contain 37 papers. The special focus in this conference is on parallel Architectures, Algorithms and Programming. The topics include: Analysing and Forecasting Electricity Demand and Price Using Deep Learning Model During the COVID-19 Pandemic;cross-database Micro Expression Recognition Based on Apex Frame Optical Flow and Multi-head Self-attention;GPS Intelligent Solution of Aerial Image Target in State grid EIA Survey;Encryption and Decryption in Conic Curves Cryptosystem Over Finite Field GF(2n) Using Tile Self-assembly;optimizing Embedding-Related Quantum Annealing Parameters for Reducing Hardware Bias;a Behavioural Network Traffic Novelty Detection for the Internet of Things Infrastructures;a Fast Algorithm for Image Segmentation Based on Global Cosine Fitting Energy Model;household Garbage Classification: A Transfer Learning Based Method and a Benchmark;lightweight Neural Network Based Garbage Image Classification Using a Deep Mutual Learning;on the Decycling Problem in a Torus;VBSSR: Variable Bitrate Encoded Video Streaming with Super-Resolution on HPC Education Platform;An Investigation on the Performance of Highly Congested Home WiFi Networks During the COVID-19 Pandemic;using Feed-Forward Network for Fast Arbitrary Style Transfer with Contextual Loss;enhancing Underwater Image Using Multi-scale Generative Adversarial Networks;Inferring Prerequisite Relationships Among Learning Resources for HPC Education;research on Bank Knowledge Transaction Coverage Model Based on Innovation Capacity Analysis;deep Deterministic Policy Gradient Based Resource Allocation in Internet of Vehicles;a Pufferfish Privacy Mechanism for the Trajectory Clustering Task;a Novel Attention Model of Deep Learning in Image Classification;FDRA: Fully distributed Routing Architecture for Private Virtual Network in Public Cloud.

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Optimization of Data-parallel Applications on Heterogeneous HPC Platforms for Dynamic Energy Through Workload Distribution 25th

Optimization of Data-Parallel Applications on Heterogeneous ...

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25th international conference on parallel and distributed computing (Euro-Par)

作者： Khaleghzadeh, Hamidreza Fahad, Muhammad Manumachu, Ravi Reddy Lastovetsky, Alexey Univ Coll Dublin Sch Comp Sci Dublin 4 Ireland

ISBN: (纸本)9783030483401;9783030483395

Energy is one of the most important objectives for optimization on modern heterogeneous high performance computing (HPC) platforms. The tight integration of multicore CPUs with accelerators in these platforms present several challenges to optimization of multithreaded data-parallel applications for dynamic energy. In this work, we formulate the optimization problem of data-parallel applications on heterogeneous HPC platforms for dynamic energy through workload distribution. We propose a solution method to solve the problem. It consists of a data-partitioning algorithm that employs load imbalancing technique to determine the workload distribution minimizing the dynamic energy consumption of the parallel execution of an application. The inputs to the algorithm are discrete dynamic energy profiles of individual computing devices. We experimentally analyse the proposed algorithm using two multithreaded data-parallel applications, matrix multiplication and 2D fast Fourier transform. The load-imbalanced solutions provided by the algorithm achieve significant dynamic energy reductions (on the average 130% and 44%) compared to the load-balanced ones for the applications.

关键词： High performance computing Heterogeneous platforms Energy of computation Multicore CPU GPU Xeon Phi

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parallel Learning of Weighted Association Rules in Human Phenotype Ontology 25th

Parallel Learning of Weighted Association Rules in Human Phe...

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25th international conference on parallel and distributed computing (Euro-Par)

作者： Agapito, Giuseppe Cannataro, Mario Guzzi, Pietro Hiram Milano, Marianna Magna Graecia Univ Catanzaro I-88100 Catanzaro Italy

ISBN: (纸本)9783030483401;9783030483395

The Human Phenotype Ontology (HPO) is a standardized vocabulary of terms related to diseases. The importance and the specificity of HPO terms are estimated employing the Information Content (IC). Thus, the analysis of annotated data is a critical challenge for bioinformatics. There exist several approaches to support ontology curators in maintaining and analysing data. Among these, the use of Association Rules (AR) can improve the quality of annotations. In this paper, we present an algorithm for the parallel extraction of Weighted Association Rules (WAR) from HPO terms and annotations, able to face high dimension of data. Experiments performed on real and synthetic datasets show good speed-up and scalability.

关键词： Human Phenotype Ontology Gene Ontology Weighted Association Rules parallel computing

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