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检索条件"任意字段=3rd International Symposium on Code Generation and Optimization"

共 319 条记录，以下是51-60 订阅

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Parameter optimization method of energy storage controller based on power system transient stability

Parameter optimization method of energy storage controller b...

引用

Smart Grids and Energy Systems (SGES), international Conference on

作者： Weitao Zhang Libin Yang Yongyu Qi Jinzhong Zhao Minghui Zhang Tao Shi Department of Ecology and Safety Quality Qinghai Branch of Luneng New Energy (Group) Co. Ltd Xining China Research Institute of Economy and Technology State Grid Qinghai Electric Power Company Xining China Qinghai Branch of Luneng New Energy (Group) Co. Ltd Xining China Nanjing Nanrui Jibao Electrical Co. Ltd Nanjing China College of Automation Nanjing University of Posts and Telecommunications Nanjing China Institute of Advance Technology for Carbon Neutrality Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9798331539634

ISBN: (纸本)9798331539641

Battery energy storage system plays an important role in calming wind and wind power volatility and maintaining system safety and stability. In view of the parameter optimization of the controller of the energy storage system, considering the impact of the energy storage system on the transient stability of the power system, data interaction was realized by studying the interface configuration between DIgSILENT and Python, and optimization code of co-simulation was written based on Particle Swarm optimization (PSO) algorithm. A parameter optimization method of energy storage controller based on DIgSILENT-Python is proposed. Finally, the IEEE9-node system is used to analyze the optimization method. The experimental results verify that the co-simulation framework can effectively optimize the parameters of the energy storage controller, which solves the problem that DIgSILENT can only set the components with measurement functions as the optimization target, and is suitable for a number of circuit faults in the system. It can guarantee the safe and stable operation of power system.

关键词： optimization methods Energy measurement Power system stability Wind power generation Stability analysis Circuit stability Transient analysis Particle swarm optimization Voltage control Energy storage

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Leveraging Reinforcement Learning for a Novel Traffic-Aware Scheduler in 5G NR IIoT Networks

Leveraging Reinforcement Learning for a Novel Traffic-Aware ...

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IEEE international symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Luciano Miuccio Salvatore Riolo Giampaolo Cuozzo Riccardo Marini Department of Electrical Electronic and Computer Engineering University of Catania Italy National Laboratory of Wireless Communications (WiLab) CNIT Italy

ISBN: (数字)9798350362244

ISBN: (纸本)9798350362251

The integration of 5G New Radio (NR) into the manufacturing industry stands as a pivotal aspect of the Industrial Internet of Things (IIoT) paradigm, mitigating constraints posed by traditional wired communication technologies in terms of flexibility, mobility, and adaptability. However, ensuring comparable performance levels presents challenges in the scheduling design of 5G NR networks, particularly due to the emphasis on uplink transmissions within industrial applications. Indeed, current uplink schedulers proposed by the 3rd generation Partnership Project (3GPP) exhibit performance trade-offs, forcing the network to acquire knowledge of uplink traffic and faltering in the presence of heterogeneous traffic sources, commonplace in industrial environments. In this paper, we thus propose a Reinforcement Learning (RL)-based approach that dynamically assigns users to the most suitable uplink scheduler without prior or acquired knowledge of the different traffic patterns. Through 3GPP-compliant network simulations, we demonstrate the effectiveness of our approach in optimizing network performance while addressing the complexities of heterogeneous IIoT environments and maintaining standard compliance.

关键词： Hands Job shop scheduling Reinforcement learning Traffic control Production facilities 3GPP Uplink Standards optimization Industrial Internet of Things

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Deep Learning Based Uplink Power Allocation in Multi-Radio Dual Connectivity Heterogeneous Wireless Networks

Deep Learning Based Uplink Power Allocation in Multi-Radio D...

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IEEE international symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Md. Habibur Rahman Mayukh Roy Chowdhury Abida Sultana Asheesh Tripathi Aloizio Pereira Da Silva Commonwealth Cyber Initiative Virginia Tech USA

ISBN: (数字)9798350362244

ISBN: (纸本)9798350362251

Multi-Radio dual connectivity (MR-DC) has been emerged as a promising 3rd generation Partnership Project (3GPP) feature aiming at improving per-user data throughput enabling traffic aggregation from two base stations (BSs) simultaneously operating the same or different radio access technologies (RATs). In MR-DC uplink (UL) data transmission, UL power assigned to the two interfaces may exceed the maximum transmission power of the user equipment (UE) leading to increased UL effective interference at the network. An optimal power allocation strategy can significantly reduce the effective UL interference which also leads to the enhancement of network throughput. But in the MR-DC scenario, dynamic switching of node assignment and consideration of effective UL transmission in a given sub-frame introduce additional challenges, making existing methods like semi-static or iterative and heuristic optimization algorithms inefficient. In this study, we aim to design a deep convolutional neural network (DCNN) model, more specifically a U-Net based model, for intelligent power allocation in the MR-DC network. A constrained optimization function is formulated considering data rate maximization, UL effective interference reduction, and effective UL transmission towards any node in the MR-DC, as well as an Interior-point method (IPM) algorithm is utilized to generate a labeled dataset. The proposed model is trained to predict the optimal power label more efficiently, especially when dealing with varying numbers of UEs and BSs. Finally, we have depicted that the proposed U-Net based model can achieve up to 10.98% total throughput improvement predicting optimal power label for 88 UEs within 0.07 seconds through simulations.

关键词： Heuristic algorithms Wireless networks Interference Predictive models Throughput Mathematical models Resource management 3GPP Uplink optimization

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Performance of Single-Carrier LOS-MIMO Using FDE in 3GPP TDL Channel Models

Performance of Single-Carrier LOS-MIMO Using FDE in 3GPP TDL...

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international symposium on Antennas and Propagation (ISAP)

作者： Aono, Kana Sawahashi, Mamoru Kamiya, Norifumi Tokyo City Univ Dept Elect Elect Commun Engn Tokyo Japan NEC Corp Ltd Syst Platform Res Labs Kawasaki Kanagawa Japan

ISBN: (纸本)9784885523267

In the future cellular systems based on heterogeneous networks (HetNets), the application of line-of-sight (LOS)-multiple-input multiple-output (MIMO) to backhaul or fronthaul between a macro cell and small cells is promising from the viewpoint of low-cost deployment. For this purpose, this paper presents the bit error rate (BER) performance of single-carrier 2 x 2 LOS-MIMO using frequency domain equalization (FDE) in the 3rd generation partnership project (3GPP) tapped delay line (TDL) channel models. Computer simulation results show the effectiveness of LOS-MIMO using FDE in the 3GPP TDL based LOS channel models.

关键词： LOS-MIMO FDE LDPC code tapped delay line channel model backhaul

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Optimized Allocation of Solar PV in Batam-Bintan Power System 2021-2025 3

Optimized Allocation of Solar PV in Batam-Bintan Power Syste...

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3rd international Conference on High Voltage Engineering and Power Systems, ICHVEPS 2021

作者： Syafrianto, Devni Marojahan Banjar-Nahor, Kevin Hariyanto, Nanang Institut Teknologi Bandung School of Electrical Engineering Informatics Bandung Indonesia

ISBN: (纸本)9781665443548

PLN Batam targeted to achieve 23% of renewable energy mix in 2025. However, PLN Batam only schedules 3x10 MW undefined renewable energy power plant in 2025 through to three connected substations: Sei Harapan, Nagoya, and Panaran in 2025. This condition encourages to conduct maximum renewable energy penetration assessment. Refer to solar potency in Batam-Bintan and global capital cost trend, this paper justifies optimized allocation for solar photovoltaic (PV) in Batam-Bintan 2021-2025 from three consideration aspects: electric, finance and geographic. This paper calculates that 654 MW-minimum midday load in Batam-Bintan 2025 then elaborated with 322 MW as Technical Minimum Loading (TML) system. Thus, maximum solar PV penetration capacity defined as 332 MW. Furthermore, since system strength of Batam-Bintan 2025 about 36 MW and grid code requires normal operation frequency range within 50±0.2 Hz, maximum capacity for one solar PV power plant about 7 MW. Then, Batam-Bintan geographical condition deliver 3 substations that deal with two adjacent solar PV power plants at 12 km. Therefore, frequency and geographic consideration obtain 3x7 MW as optimized capacity from connected substations: Batu Besar, Sri Bintan, and Kijang. Cost optimization using HOMER software then clarifies that 21 MW solar PV in 2025 may produces cost saving 2.7 million. Subsequently, grid impact analysis justifies that 21 MW installed capacity in 2025 that deliver no issue. Finally, this paper proposes different solar PV allocation from RUPTL PLN Batam. The difference as product of cascading stages that projected to be novelty in renewable energy penetration assessment. © 2021 IEEE.

关键词： Solar power generation

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Joint Link Adaptation and Resource Allocation for Uplink in 3GPP Machine-Type Communications 14

Joint Link Adaptation and Resource Allocation for Uplink in ...

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14th international Conference on COMmunication Systems and NETworkS, COMSNETS 2022

作者： M., Pavan Reddy Kumar, Abhinav Kuchi, Kiran Indian Institute of Technology Department of Electrical Engineering Hyderabad502284 India

ISBN: (纸本)9781665421041

Enhanced Machine-Type Communications (eMTC) is a low-power wide-area network technology introduced by the 3rd generation Partnership Project (3GPP). The eMTC devices are of low cost and can operate in poor signal coverage areas. To ensure successful transmission in such scenarios, 3GPP has adopted the repetition of data over time. In 4G-LTE/5G-NR, the resource allocation and link adaptation are one-dimensional problems where the modulation and coding scheme (MCS) is either incremented or decremented over time. However, in eMTC, there exists a two-dimensional problem, as the base station can update either MCS or repetitions. Further, the base station has to consider the devices' limited transmit power while allocating resources in the uplink. An optimal selection of these values has a significant impact on the network capacity and the devices' battery power. Motivated by this, we present novel resource allocation, link adaptation, and scheduling algorithms for the eMTC uplink. We show that the proposed algorithms result in a suitable selection of resource blocks, MCS, repetition levels, and link adaptation. To reduce the computation load, we also propose a low-complexity sub-optimal scheduling algorithm. Through system-level simulations, we show that all the proposed algorithms significantly outperform the state-of-the-art algorithms. © 2022 IEEE.

关键词： Resource allocation

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Tie-line Power Adjustment Method Based on Proximal Policy optimization Algorithm 3

Tie-line Power Adjustment Method Based on Proximal Policy Op...

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2020 3rd international symposium on Power Electronics and Control Engineering, ISPECE 2020

作者： Hou, Jinxiu Yu, Zhihong Zheng, Qingping Xu, Huating Li, Shufang China Electric Power Research Institute Beijing100192 China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing100876 China College of Electrical Engineering Zhejiang University Hangzhou310027 China

The tie-line power adjustment is an essential part of the power system operation state calculation. Various existing algorithms to solve the tie-line power adjustment problem are mainly implemented by introducing tie-line power equation constraints into conventional power flow calculations. Such methods have low calculation efficiency, not enough automation, and are prone to non-convergence in the power flow calculation. In this paper, the tie-line power adjustment problem is formulated as a Markov decision process, and the proximal policy optimization algorithm is introduced to optimize the decision policy. In order to enhance the effectiveness of the proposed method, a new deep neural network structure suitable for the proximal policy optimization algorithm is designed. The proposed method is verified with the IEEE 39-bus system. © Published under licence by IOP Publishing Ltd.

关键词： Markov processes

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Development of a methodology for cost optimization of software testing for the automatically tests generation 3

Development of a methodology for cost optimization of softwa...

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3rd international Workshop on Modeling, Information Processing and Computing, MIP: Computing 2021

作者： Platonov, Alexander A. Mamedova, Natalia A. Plekhanov Russian University of Economics Stremyanny lane 36 Moscow117997 Russia

The paper is devoted to issues of software development and support processes, in particular, for software testing. The task of developing a methodology for testing has been solved. It allows optimizing the company's costs for the automatically tests generation. The widely applied software quality control practices were analyzed;the requirements for the developed method were formulated. The IT infrastructure for software quality control has been designed on the basis of the developed methodology. A new result of the research is tools representation for the automatically qualitative tests generation that does not require a significant transformation of the architecture of the software under the test. The presented solution can help companies to optimize significantly their costs for quality control of the developed software. The object for the analysis and implementation of solutions was a company that is a specialized depository, i.e, a participant of the securities market. Its information system is a complex multi-module product. The best practice for increasing the reliability of software, i.e., code coverage with tests has been implemented for it. The task was to find automatically generating tests solution to support the business processes of a specialized depository. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0).

关键词： Software testing

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PSCAD-MATLAB Coupled Simulation Method for Power Flow optimization using Continuous Reactive Power Controllable Device 3

PSCAD-MATLAB Coupled Simulation Method for Power Flow Optimi...

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2020 3rd international symposium on Power Electronics and Control Engineering, ISPECE 2020

作者： Yang, Fan Chen, Kai Qian, Shaofeng Zhan, Jiangyang Yu, Rui Song, Pan Zhejiang Electric Power Company STATE GRID Corporation of China Hangzhou Zhejiang China Hangzhou Power Supply Company STATE GRID Corporation of China Hangzhou Zhejiang China Wuhan HaiO Electric Corporation Wuhan Hubei China

With the integration of distributed generation (DG), micro-grids and are becoming attractive. Power flow studies are very important in the planning or expansion of power systems. The paper proposed a novel method that incorporates MATLAB and PSCAD to study the optimal control of the reactive control algorithm to reduce the power loss in the transmission lines. The proposed strategy is easy to implement and effective in solving the dynamic power flow problems. The results can apply to control the continuous reactive power controllable device and show that the power loss can be greatly reduced. © Published under licence by IOP Publishing Ltd.

关键词： Reactive power

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optimization of the Himeno Benchmark for SX-Aurora TSUBASA 3rd

Optimization of the Himeno Benchmark for SX-Aurora TSUBASA

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3rd BenchCouncil international symposium on Benchmarking, Measuring, and Optimizing, Bench 2020

作者： Onodera, Akito Komatsu, Kazuhiko Fujimoto, Soya Isobe, Yoko Sato, Masayuki Kobayashi, Hiroaki Graduate School of Information Sciences Tohoku University Sendai Japan Cyberscience Center Tohoku University Sendai Japan NEC Corporation Minato-ku Japan

ISBN: (纸本)9783030710576

This paper focuses on optimizing the Himeno benchmark for the vector computing system SX-Aurora TSUBASA and analyzes its performance in detail. The Vector Engine (VE) of SX-Aurora TSUBASA achieves a high memory bandwidth by High Bandwidth Memory (HBM2). The Himeno benchmark solves Poisson’s equation using the Jacobi iteration method. The kernel performs 19-point stencil calculations in the 3D domain, which is known as a memory-intensive kernel. This paper introduces four optimizations in a single VE or multiple VEs for the Himeno benchmark. First, for a single VE, to exploit the high bandwidth of the last-level cache (LLC) in the VE, the highly reusable array elements are stored in the LLC with the highest priority. Second, the computational domain is decomposed by considering the architecture of the VE so that this optimization can achieve a high LLC hit ratio and a long vector length. Third, to alleviate the loop overhead that tends to be large for vector computation, loop unrolling is applied to the kernel. Fourth, for multiple VEs, the optimization to improve the sustained MPI communication bandwidth is applied. The process mapping is optimized by considering different types of communication mechanisms of SX-Aurora TSUBASA. The evaluation results show that the optimizations contribute to the long vector length, the high LLC hit ratio, and the short MPI communication time of the Himeno benchmark. As a result, the performance and the power efficiency are improved due to efficient vector processing through the optimizations. © 2021, Springer Nature Switzerland AG.

关键词： Vectors

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