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Evaluation of ancillary services in distribution grid using large-scale battery energy storage systems

IET RENEWABLE POWER GENERATION 2020年第19期14卷 4216-4222页

作者： Mahesh, M. Vijaya Bhaskar, D. Narsa Reddy, T. Sanjeevikumar, P. Holm-Nielsen, Jens Bo Power Grid Corp India Ltd Pondicherry India IIT ISM Dhanbad Dept Elect Engn Dhanbad Bihar India IIT Mandi Sch Comp & Elect Engn Suran India Aalborg Univ Dept Energy Technol Ctr Bioenergy & Green Engn Aalborg Denmark

Battery energy storage systems (BESSs) are being presented as a prominent solution to the various imminent issues associated with the integration of variable renewable energy sources in the distribution system. Performance of grid-connected BESS depends on the type of application (power and energy), grid operating parameters and level of interconnection point, which shows the necessity of benefit assessment of BESS technology and its applications in terms of economic and grid operations before investment at a larger scale. In this study, real-time analysis and evaluation of two different battery technologies connected in a medium voltage (MV) distribution system are carried out. The main objective of this paper is focused on the impact analysis of large-scale BESS on MV distribution feeder. A real case of installation of lithium-ion and advanced lead-acid battery systems into the Indian distribution system has been considered for this study. Different operational strategies of BESS such as frequency regulation and energy time-shift have been performed with real-time data. The effectiveness in usage of BESS with these functionalities has been verified in terms of peak shaving, improvement in voltage profile and reduction in power losses in the feeder.

关键词： battery storage plants lead acid batteries power grids renewable energy sources energy storage distributed power generation frequency control secondary cells real-time analysis different battery technologies medium voltage distribution system large-scale BESS MV distribution feeder lead-acid battery systems Indian distribution system energy time-shift ancillary services distribution grid large-scale battery energy storage systems prominent solution imminent issues variable renewable energy sources grid-connected BESS grid operating parameters BESS technology economic grid operations

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Airborne nanoparticle analysis mini-system using a parallel-type inertial impaction technique for real-time monitoring size distribution and effective density

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SENSORS AND ACTUATORS A-PHYSICAL 2022年 341卷

作者： Song, Woo-Young Lee, Seung-Soo Kim, Yong-Jun Yonsei Univ Sch Mech Engn Seoul 03722 South Korea

To elucidate the relationship between exposure to airborne nanoparticles (NPs;< 300 nm particles) and adverse health effects, two of their characteristics - size distribution and effective density- should be measured in realtime as they are key parameters that determine the particle deposition patterns in human airways. However, current lab-grade and portable instruments that assess airborne NPs only measure their size distribution;in addition, they are bulky and expensive, limiting their application to the analysis of individual NP exposure. To overcome these limitations, in this paper, we introduce and successfully demonstrate an NP analyzer realized in a mini-fluidic system whose main components were realized on two printed circuit boards (PCBs) that were subsequently adjoined. Our sensor could analyze the effective density and lognormal size distribution (number concentration, median diameter, and geometric standard deviation) of NPs in real time. Moreover, since an innovative NP analysis algorithm based on a parallel-type microfluidic inertial impaction technique is integrated in a miniature system, our sensor was portable (16.0 x 9.9 x 7.85 cm(3), 980 g) and cost-efficient. In performance tests using synthesized NPs and in real-world environmental application tests, the performance of our sensor was comparable to that of conventional NP analysis systems. These results indicate that our mini-system is excellently suited to be used in hand-held sensors or distributed sensor networks for personal NP exposure monitoring, and toxicological studies.

关键词： Airborne nanoparticles Effective density Size distribution real-time measurements parallel-type microfluidic cascade impactor

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distributed Control System for Medium-Voltage STATCOM based on parallel Connected Power Converters 19

Distributed Control System for Medium-Voltage STATCOM based ...

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IEEE 19th International Power Electronics and Motion Control Conference (PEMC)

作者： Stengl, Josef Komrska, Tomas Talla, Jakub Kosan, Tomas Burian, Petr Polacek, Libor Peroutka, Zdenek Turjanica, Pavel Univ West Bohemia Reg Innovat Ctr Elect Engn Plzen Czech Republic

ISBN: (纸本)9781728156606

Power semiconductor installations in medium-voltage power grids are usually built by numerous particular power converter units containing large number of power modules. Such large installations place high demands on control systems including precise timing and signal distribution across the whole system. This paper deals with a proposed distributed modular control system designed for STATCOM installed in a MV power grid of 22 kV. The proposed control system is designed for a real-time control of the converter with high-speed interference-immune communication, reliable synchronization of numerous PWM outputs and synchronous immediate blocking of fire pulses for safe central stop in case of error handling.

关键词： Converter control STATCOM parallel operation System integration

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SPIDER: An Effective, Efficient and Robust Load Scheduler for real-time Split Frame Rendering

SPIDER: An Effective, Efficient and Robust Load Scheduler fo...

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International Symposium on parallel and distributed Processing (IPDPS)

作者： Bingzheng Ma Ziqiang Zhang Yusen Li Wentong Cai Gang Wang Xiaoguang Liu School of Computer Science Nankai University Tianjin China School of Computer Science and Engineering Nanyang Technological University Singapore

Interactive graphics applications are generally latency-critical, while using multiple GPUs to accelerate such applications becomes possible recently with support from both hardware and software. Split frame rendering (SFR) is a popular approach for multi-GPU rendering, which splits a frame into disjoint regions and assigns the regions to different GPUs. Load scheduling of SFR is a crucial but challenging issue for achieving maximum rendering performance in real-time rendering, which is not well addressed by the existing solutions. In this paper, we propose SPIDER, a load scheduler which leverages fuzzy PID (proportional integral derivative) controller to schedule the rendering workload among GPUs. SPIDER has several distinguished properties: it is a feedback based mechanism which does not need a full knowledge of the dynamic system; it is very computationally efficient and easy to implement; it is highly robust to dynamic workload changes. Extensive experiments are conducted to evaluate SPIDER and the results show that SPIDER always achieves near-optimal performance for various workload patterns, which outperforms the state-of-the-art baselines signif-icantly.

关键词： Graphics Schedules distributed processing Rendering (computer graphics) real-time systems Software Hardware

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A Decentralized Edge Computing Latency-Aware Task Management Method With High Availability for IoT Applications

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IEEE ACCESS 2021年 9卷 138994-139008页

作者： Bukhsh, Muhammad Abdullah, Saima Bajwa, Imran Sarwar Islamia Univ Bahawalpur Dept Comp Sci & IT Bahawalpur 63100 Pakistan

Rapid growth of Internet of Things (IoT), and other intelligent devices, introduced different applications which offer real-time latency features;however, it is difficult to handle the large volumes of data produced during the computational process, to adequately complete tasks. The decentralized edge computing process handles the task at the user's end to accomplish latency applications, but recent research adopted centralized methodologies for computing in the edge network, placing additional overhead for cluster management and grouping. In this paper, we formulate an edge nodes group on task arrivals with a decentralized technique to process jobs, in a parallel mode, to complete execution. In addition, high availability will be added to promise effective processing of IoT based applications executed in the edge computing system. In the edge node environment, where resources are restricted, there is a requirement for high availability methods, which can deliver system reliability according to the local device information, without the data of network topology. In this paper, our technique is to enhance network reliability with the help of the edge node's local information, which is executed in the distributed edge computing network, while also proposing a high availability technique to enhance the overall IoT environment. Our proposed Latency Aware Algorithm for Edge Computing with High Availability (LAAECHA) detects edge nodes faults, repairs edge nodes and replaces edge nodes with backups, using a new algorithm in a decentralized mode. Our research results show that the proposed LAAECHA method is more effective than existing methods, ensuring latency-aware IoT applications achieve their deadlines, while significantly reducing network traffic as well as guaranteeing system availability and reliability of the IoT network.

关键词： Edge computing Internet of Things Task analysis Fault tolerant systems Reliability Fault tolerance Servers Edge computing distributed computing Internet of Things fault tolerance high availability

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Highly accurate and efficient two phase-intrusion detection system (TP-IDS) using distributed processing of HADOOP and machine learning techniques

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JOURNAL OF BIG DATA 2021年第1期8卷 1-22页

作者： Jadhav, Abhijit Dnyaneshwar Pellakuri, Vidyullatha Koneru Lakshmaiah Educ Fdn Dept Comp Sci & Engn Vaddeswaram Andhra Pradesh India Dr DY Patil Inst Technol Dept Comp Engn Pune 411018 Maharashtra India

Network security and data security are the biggest concerns now a days. Every organization decides their future business process based on the past and day to day transactional data. This data may consist of consumer's confidential data, which needs to be kept secure. Also, the network connections when established with the external communication devices or entities, a care should be taken to authenticate these and block the unwanted access. This consists of identification of the malicious connection nodes and identification of normal connection nodes. For that, we use a continuous monitoring of the network input traffic to recognize the malicious connection request called as intrusion and this type of monitoring system is called as an Intrusion detection system (IDS). IDS helps us to protect our network and data from insecure and malicious network connections. Many such systems exists in the real time scenario, but they have critical issues of performance like accuracy and efficiency. These issues are addressed as a part of this research work of IDS using machine learning techniques and HDFS. The TP-IDS is designed in two phases for increasing accuracy. In phase I of TP-IDS, Support Vector Machine (SVM) and k Nearest Neighbor (kNN) are used. In phase II of TP-IDS, Decision Tree (DT) and Naive Bayes (NB) are used, where phase II is the validation phase of the system for increasing accuracy. Also, both the phases are having Hadoop distributed file system underlying data storage and processing architecture, which allows parallel processing to increase the speed of the system and hence achieve the efficiency in TP-IDS.

关键词： Accuracy Efficiency Intrusion detection Machine learning Security TP-IDS

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DL_FFLUX: A parallel, Quantum Chemical Topology Force Field

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JOURNAL OF CHEMICAL THEORY AND COMPUTATION 2021年第11期17卷 7043-7055页

作者： Symons, Benjamin C. B. Bane, Michael K. Popelier, Paul L. A. Manchester Inst Biotechnol MIB Manchester M1 7DN Lancs England Univ Manchester Dept Chem Manchester M13 9PL Lancs England High End Compute LTD Manchester M13 0EL Lancs England Manchester Metropolitan Univ Dept Comp & Math Manchester M15 6BH Lancs England

DL_FFLUX is a force field based on quantum chemical topology that can perform molecular dynamics for flexible molecules endowed with polarizable atomic multipole moments (up to hexadecapole). Using the machine learning method kriging (aka Gaussian process regression), DL_FFLUX has access to atomic properties (energy, charge, dipole moment, etc.) with quantum mechanical accuracy. Newly optimized and parallelized using domain decomposition Message Passing Interface (MPI), DL_FFLUX is now able to deliver this rigorous methodology at scale while still in reasonable time frames. DL_FFLUX is delivered as an add-on to the widely distributed molecular dynamics code DL_POLY 4.08. For the systems studied here (10(3)-10(5)atoms), DL_FFLUX is shown to add minimal computational cost to the standard DL_POLY package. In fact, the optimization of the electrostatics in DL_FFLUX means that, when high-rank multipole moments are enabled, DL_FFLUX is up to 1.25X faster than standard DL POLY. The parallel DL_FFLUX preserves the quality of the scaling of MPI implementation in standard DL_POLY. For the first time, it is feasible to use the full capability of DL_FFLUX to study systems that are large enough to be of real-world interest. For example, a fully flexible, high-rank polarized (up to and including quadrupole moments) 1 ns simulation of a system of 10 125 atoms (3375 water molecules) takes 30 h (wall time) on 18 cores.

关键词： Molecular mechanics Electrical energy Electrostatics Energy Molecules

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ADSTS: Automatic distributed Storage Tuning System Using Deep Reinforcement Learning 22

ADSTS: Automatic Distributed Storage Tuning System Using Dee...

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Proceedings of the 51st International Conference on parallel Processing

作者： Kai Lu Guokuan Li Jiguang Wan Ruixiang Ma Wei Zhao Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology China SenseTime Research China

ISBN: (纸本)9781450397339

Modern distributed storage systems with the immense number of configurations, unpredictable workloads and difficult performance evaluation pose higher requirements to parameter tuning. Providing an automatic parameter tuning solution for distributed storage systems is in demand. Lots of researches have attempted to build automatic tuning systems based on deep reinforcement learning (RL). However, they have several limitations in the face of these requirements, including lack of parameter spaces processing, less advanced RL models and time-consuming and unstable training process. In this paper, we present and evaluate the ADSTS, which is an automatic distributed storage tuning system based on deep reinforcement learning. A general preprocessing guideline is first proposed to generate standardized tunable parameter domain. Thereinto, Recursive Stratified Sampling without the nonincremental nature is designed to sample huge parameter spaces and Lasso regression is adopted to identify important parameters. Besides, the twin-delayed deep deterministic policy gradient method is utilized to find the optimal values of tunable parameters. Finally, Multi-processing Training and Workload-directed Model Fine-tuning are adopted to accelerate the model convergence. ADSTS is implemented on Park and is used in the real-world system Ceph. The evaluation results show that ADSTS can recommend near-optimal configurations and improve system performance by 1.5 × ∼2.5 × with acceptable overheads.

关键词： Parameter Identification distributed Storage System Auto-tuning Reinforcement Learning

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Toward Profiling IoT Processes for Remote Service Attestation

Toward Profiling IoT Processes for Remote Service Attestatio...

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International Symposium on parallel and distributed Computing

作者： William A. Johnson John Housley Sheikh Ghafoor Stacy Prowell Cyber and Computer Sciences The Citadel Charleston SC USA Computer Science Tennessee Tech University Cookeville TN USA Computational Sciences Oak Ridge National Lab Oak Ridge TN USA

ISBN: (数字)9798350369199

ISBN: (纸本)9798350369205

The Internet of Things (IoT) is ubiquitous in modern life and is being used very widely in industrial control systems, smart grids, home appliances and many more. IoT devices are used to get information from sensors, process information, and send signals to actuators and controllers. In general these devices form a distributed computing network while in operation. Malware in IoT or any embedded devices is a potential security threat. Detecting malware in such a setting while in operation is non-trivial, because these low power devices may not have the computational ability to perform traditional security operations. Additionally, an infected device may cause other machines to misbehave by interfering with the data they receive. Remote Attestation is a security service designed to detect an infection in a device well before the malware detonates. Recent works have turned their attention to service attestation, or attesting the service that a network provides, rather than the individual devices themselves. Traditional remote attestation schemes use cryptographic hashing algorithms as evidence, but this approach generates exponentially more hashes as heterogeneous IoT devices are added to the network and their jobs’ complexity increases. In this work, we propose an approach to collect the contents of executable virtual memory from an IoT device. We develop a protocol based on our approach that can build a profile of a process running on an IoT device, such evidence can be analyzed automatically with high granularity. We validate our protocol by testing on both a personal computer, and a real-world Industrial IoT device under process injection attacks. Our results show that our protocol will be able to detect small changes to process memory over time, and that an injection as small as one word can be detected and read.

关键词： Protocols Scalability Production Malware Complexity theory Smart grids Internet of Things Cryptography distributed computing Testing

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Scheduling across Multiple Applications using Task-Based Programming Models 4

Scheduling across Multiple Applications using Task-Based Pro...

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IEEE/ACM 4th Annual workshop on Emerging parallel and distributed Runtime systems and Middleware (IPDRM)

作者： Chung, Minh Thanh Weidendorfer, Josef Samfass, Philipp Fuerlinger, Karl Kranzlmuller, Dieter Ludwig Maximilians Univ Munchen MNM Team Munich Germany Leibniz Supercomp Ctr LRZ Garching Germany Tech Univ Munich Dept Informat Munich Germany Ludwig Maximilians Univ Munchen MNM Team Leibniz Supercomp Ctr LRZ Munich Germany

ISBN: (纸本)9780738110646

Task-based programming models have shown their potential for efficiency and scalability in parallel and distributed systems. With such a model, a parallel application is broken down into a graph of tasks, which are subsequently scheduled for execution. Recently, implementations of task-based models have addressed distributed memory and heterogeneous systems with accelerators. However, the problem of scheduling tasks as well as allocating resources at runtime is still a challenge. In this paper, we propose coordinated and cooperative task scheduling across multiple applications. The main idea is to exploit the application's idle time e.g. from imbalance to serve tasks from another application. The experiments use Chameleon, a task-based framework for reactive tasking in distributed memory systems. In various example scenarios, we show improvements in CPU utilization of 5% - 15% by coordinated scheduling.

关键词： task-based programming model distributed system scheduling resource management task migration

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