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检索条件"任意字段=3rd Euro-NF Conference on Network Control and Optimization"

共 1643 条记录，以下是461-470 订阅

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Research on Reactive Power optimization of Active Distribution network Based on Deep Reinforcement Learning

Research on Reactive Power Optimization of Active Distributi...

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Power System and Green Energy conference (PSGEC)

作者： Changchun Cai Jingna Liu Yuanyuan Wang Yuanjia Li Jinghao Fan Jie He Jiangsu Key Laboratory of Power Transmission & Distribution Equipment Technology Hohai University Changzhou China College of Information Sciences and Engineering Hohai University Changzhou China Dongying Power Supply Company State Grid Shandong Electric Power Company Dongying China

The installed proportion of renewable energy is constantly increasing. Due to the intermittency and volatility of renewable energy output, its connection to the power grid can easily affect voltage, leading to voltage violations and safety issues in grid operation. At the same time, considering fast regulation characteristics of Static Var Generator (SVG), a method utilizing deep reinforcement learning is introduced for controlling active distribution network reactive power and voltage. This method converts reactive power and voltage control problem of the power grid under renewable energy access conditions into a Markov Decision Process (MDP), and then constructs a reactive power and voltage control model under renewable energy access. Based on the actual operating environment requirements of the power grid, constraint conditions are proposed, and the model is solved using Deep Deterministic Policy Gradient (DDPG) algorithm. Finally, simulations were performed for improved 33 node instances. The effectiveness of the reactive power and voltage optimization control strategy given in this paper is verified by comparing the reactive power and voltage optimization control effects under different levels of renewable energy access conditions.

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Voltage control Strategy for Cooperative Regulation of Fast and Slow Devices in Active Distribution network

Voltage Control Strategy for Cooperative Regulation of Fast ...

引用

Intelligent Power and Systems (ICIPS), International conference on

作者： Guangde Dong Yongtao Chen Xiaojun Zhu Tao Chen Yiyao Zhou Qianggang Wang Electric Power Research Institute State Grid Chongqing Electric Power Company Chongqing China

Although voltage control of an active distribution network (ADN) is regulated by voltage regulation devices which can be classified according to the speed of voltage regulation, devices, slow devices lack intra-day regulation flexibility, whereas fast devices have a narrow voltage regulation range. To enable intra-day cooperative regulation of fast and slow devices in an ADN, we propose a voltage control strategy comprising a mixed-integer nonlinear programming (MINLP) model considering predictive variables. We introduced a strict time constraint, limited the solution range via scene filtering, and converted discrete variable to continuous ones based on Gaussian penalty function (GPF), which was further solved using the firework algorithm (FWA) to obtain quick and accurate optimization results. Compared to the traditional voltage control strategy, the proposed strategy can increase voltage control range and accelerate convergence speed, and its effectiveness was verified using an actual circuit in the Anhui province.

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3rd International conference on Data, Engineering, and Applications, IDEA 2021

3rd International Conference on Data, Engineering, and Appli...

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3rd International conference on Data, Engineering, and Applications, IDEA 2021

ISBN: (纸本)9789811946868

The proceedings contain 53 papers. The special focus in this conference is on Data, Engineering, and Applications. The topics include: An In-Field Real-Time Automatic Weed Detection Using Deep Learning Techniques;sentiment Analysis of Indians Due to Conflict Between India and China at the Actual Line of control in Galwan Valley, Ladakh;feature Selection Using Information Gain for Software Effort Prediction Using Neural network Model;a Comprehensive Survey of Web and Mobile Apps for Fishermen;study of Machine Learning Classifiers for Intrusion Detection System;the Analysis of Time Series Data;computed Tomography Image Processing Methods for Lung Nodule Detection and Classification: A Review;Implementation and Analyzing SURF Feature Detection and Extraction on WANG Images Using Custom Bag of Features Model;A Method for Improving Efficiency and Security of FANET Using Chaotic Black Hole optimization-Based Routing (BHOR) Technique;machine Learning Approaches for Image-Based Screening of Cervical Cancer;A Comparative Analysis of Image Steganography Based on Discrete Wavelet Transform (DWT) and Exploiting Modification Direction (EMD);web Attack Detection Using Machine Learning;pragmatic Analysis of Web Service Discovery Models and Architectures from a Qualitative Perspective;An Integrated Semi-Supervised Learning Framework for Image Compression Using DCT, Huffman Encoding, and LZW Coding;analyzing the Need for Video Summarization for Online Classes Conducted During Covid-19 Lockdown;local Roughness Binary Pattern for Texture Classification;Speech Enhancement Using VAD for Noise Estimation in Compressive Sensing;a Comparative Study on Single Image De-Raining Using Convolutional Neural network;a Hybrid Translation Model for Pidgin English to English Language Translation.

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Application of Social network Analysis and Autoencoder in Enterprise Internal Collaboration optimization System

Application of Social Network Analysis and Autoencoder in En...

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Data Analytics, Computing and Artificial Intelligence (ICDACAI), International conference on

作者： Siting Chang School of Management Shanghai University Shanghai China

ISBN: (数字)9798331519032

ISBN: (纸本)9798331519049

It is difficult for the existing workflow modeling technology to effectively deal with the complex and dynamic characteristics of business processes between enterprises, especially to support the ability of process collaboration. This project intends to study the modeling theory and method of flexible workflow system based on business agent from the perspective of multi-agent cooperation and high flexibility requirements. Construct a flexible workflow architecture with multi-level and multi-authority control. In this paper, the process management and implementation of hierarchical management and control. The process is optimized using social network analysis and self-encoder method. The advantage is that the original input can be restored in the case of noise, while taking full advantage of the diversity and complexity of noise. The deep neural network is used to enhance the recovery ability of the initial features, so as to effectively suppress the external noise. Through a case study of the actual process of a cashmere enterprise, the corresponding model is established. The research proves that the model proposed in this paper can deal with the cooperative relationship between process flexibility and enterprise organization well.

关键词： Data analysis Social networking (online) Computational modeling Noise Autoencoders Noise reduction Collaboration Process control Organizations optimization

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A New Min-Max Limit Protection Design Method for Aero-engine based on Inverse Mapping 3

A New Min-Max Limit Protection Design Method for Aero-engine...

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3rd International conference on Artificial Intelligence and Computer Engineering, ICAICE 2022

作者： Zhu, Zhengchen Zheng, Qiangang Zhang, Shubo AECC Aero Engine Control System Institute Wuxi214063 China Nanjing University of Aeronautics and Astronautics Jiangsu Province Key Laboratory of Aerospace Power System Nanjing210016 China

ISBN: (纸本)9781510663473

In order to improve the control accuracy of aero-engine operation limits, a novel design approach of Min-Max limit protection is proposed. The inverse mapping models of different limits based on On-Line Sliding Window Deep Neural network (OL SW DNN) are proposed and established firstly. The OL SW DNN models calculate the limit value of fuel flows to ensure that engine satisfies all operation limits. The operation restrictions in the proposed method can vary in different flight conditions. With the application of on-line learning modeling method, the engine can always operate within the given operation limits no matter whether engine degrades or not. Moreover, the OL SW DNN adopts deep learning structure and has strong fitting capacity for the nonlinear object. The comparison simulations of the popular limit protection design method based on optimization method and the proposed one are carried out. Compared with the popular method, the limit line of each operation limits in the proposed method not only has much higher accuracy especially when engine appears degradation, but also can be continuous changed. © 2023 SPIE.

关键词： Engines

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Comparative Study of Coupled MPTCP Congestion control Algorithms

Comparative Study of Coupled MPTCP Congestion Control Algori...

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International conference on Advanced Electrical Engineering (ICAEE)

作者： Sadjida Lebid Chakib.M.A Zouaoui Ahmed Bouzidi Djebbar TTNS Laboratory Djillali Liabes University Sidi Bel Abbes Algeria RCAM Laboratory Djillali Liabes University Sidi Bel Abbes Algeria

ISBN: (数字)9798350349351

ISBN: (纸本)9798350349368

Multipath TCP (MPTCP) has emerged as a promising protocol for enhancing network performance by utilizing multiple paths simultaneously. In this paper, we focus on measuring the performance of coupled MPTCP congestion control(CC) algorithms, specifically throughput, in the context of delay, loss rate, and bandwidth. We are going to evaluate the main coupled MPTCP congestion control algorithms: LIA, OLIA, BALIA and wVegas. The obtained results demonstrate the effectiveness of the performance analysis of different CC algorithms doing under the same plateform. Our research aims to shed light on the effectiveness of these algorithms under varying network conditions and to provide valuable insights into their suitability for different scenarios.

关键词： Wireless communication Electrical engineering Protocols Bandwidth Throughput Loss measurement Delays Performance analysis MPTCP optimization

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Research on multi-connection network selection algorithm based on SACM-FA

Research on multi-connection network selection algorithm bas...

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Data Science and Computer Application (ICDSCA), IEEE International conference on

作者： Lin Dong Century College Beijing University of Posts and Telecommunications Beijing China

The proposed algorithm in this paper is called the Step-Adaptive Firefly Algorithm (SAFA), which is based on the Cubic Chaotic Mapping and SACM-FA. This algorithm combines the firefly algorithm with chaotic optimization theory. It utilizes chaotic sequences to randomly generate initial positions for fireflies, ensuring the randomness of initial individuals. It also introduces an adaptive search step to enhance the diversity of the population. The algorithm performs optimization operations while satisfying the QoS guarantees of users and obtains the optimal allocation of wireless resources through multiple iterations. The SACM-FA algorithm optimizes bandwidth allocation and power control problems in the uplink environment of ELWA (Enhanced Land Mobile Wireless Access) systems with multiple coexisting service types. It improves user utility and satisfaction. The simulation results demonstrate that the SACM-FA algorithm can improve the throughput of wireless systems and effectively enhance network performance in ELWA systems with multiple coexisting service types. Compared to traditional network selection algorithms, the improved algorithm can effectively balance network load and significantly improve user satisfaction.

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On-line Condition Monitoring of Vibration Sensor Based on Wavelet and Particle Swarm optimization-back Propagation Neural network

On-line Condition Monitoring of Vibration Sensor Based on Wa...

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Electrical Engineering and control Science (IC2ECS), International conference on

作者： Junchang Huang Feitong Zeng Ziyuan Liu Jing Liu Haoliang Hu China Electric Power Research Institute Wuhan People's Republic of China Huazhong University of Science and Technology Wuhan People's Republic of China

The vibration sensor can monitor the vibration of transformers, motors, and other equipment in the power grid. Its measurement accuracy is related to the safe and stable operation of the equipment, so it is necessary to monitor the vibration sensor online. When the vibration sensor fails, the acceleration output value after ADC conversion will also change accordingly. A fault diagnosis method based on wavelet decomposition and PSO-BP neural network is proposed to realize the online monitoring of vibration sensors. Firstly, the wavelet decomposition sensor output data is used to extract the feature quantity and judge whether the fault occurs with the normal state. The BP neural network is used to classify the normal operation of the sensor and various typical faults. At the same time, the PSO algorithm is introduced to optimize the neural network parameters, which is better than the original fault diagnosis method, and the fault diagnosis of the vibration sensor is realized.

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Third International conference on Electronics and Communication;network and Computer Technology, ECNCT 2021

Third International Conference on Electronics and Communicat...

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3rd International conference on Electronics and Communication;network and Computer Technology, ECNCT 2021

ISBN: (纸本)9781510652101

The proceedings contain 119 papers. The topics discussed include: research on error and correction system of electric energy experimental metering device based on configuration design;two applications of machine learning on COVID-19;optimal control of slow traffic at intersections based on green building materials and signal processing technology;design of off-line detection device for spare parts of shipborne satellite communication antenna servo system;a garbage collection method based on integrity and mobile communication technology;mimic honeypot based on dual mimicry mechanism;the application value of deep convolution level set in ABUS image analysis of varicose vein of lower extremity;reliability optimization of distribution network based on the interaction between electric vehicles and distributed generations;and design of meter-reading recognition system for intelligent converter station based on machine vision technology.

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A Robust optimization Model for Optimal Charging and Discharging Coordination of Plug-in Electric Vehicle in Microgrid

A Robust Optimization Model for Optimal Charging and Dischar...

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Smart Technologies for Power, Energy and control (STPEC), IEEE International conference on

作者： Mohd Bilal Arshad Mohammad Farhad Ilahi Bakhsh SND College of Engineering and Research Center Nashik India Aligarh Muslim University Aligarh India National Institite of Technology Srinagar Srinagar (J&K) India

The necessity for developing an alternative ecofriendly transport network has been emphasized by the harmful environmental effects of employing fossil fuel-powered vehicles. Plug-in Electric Vehicle (PEVs) are introduced to reduce the steadily rising energy consumption and carbon emissions of urban transport. However, the potential advantages of electrification as a particular and dependable source may be diminished due to limitations on the electrical grid caused by the rising demand for mobility. A power grid may have severe interruption due to the green energy sources’ such as Photovoltaic (PV) arrays reliance on the weather to produce electricity. In the meanwhile, unregulated PEV charging could result in a load surge on the electrical system. In this regard, this article investigates the charging and discharging of PEVs with the goal of minimizing charging costs. The simulation results for the considered scenario suggest that the given optimization strategies can satisfy the required objective.

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