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TID Controller for Load Frequency Control in Multi-Area Interconnected Systems with High Renewable Energy Penetration Using an Improved Grey Wolf Algorithm

TID Controller for Load Frequency Control in Multi-Area Inte...

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Innovative Research in applied Science, Engineering and Technology (IRASET),conference on

作者： Ikram Znati Mohammed Ferfra Abdessamade Bouaddi Nahla Idrissi Chehaibi Department of Electrical Engineering Mohammadia School of Engineers Mohammed V University Rabat Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

The global energy transition, marked by the strong mix of renewable sources of energy in power grids, brings big challenges to power system stability. This stability gets affected by the changeable and hard-to-predict output of renewable energy sources that are highly dependent on weather conditions. In order to tackle this problem TID controller has been designed for Load Frequency Control LFC. To optimize the TID controller parameters, Improved Grey Wolf Optimizer (I-GWO) is employed utilizing an Integral Time Absolute Error (ITAE) objective function. The proposed controller is tested on a Three-area power system integrated with photovoltaic (PV) panels and wind turbines representing a high penetration of Renewable Energy Sources (RESs) in modern power *** results are compared with those obtained using Proportional-Integral-Derivative (PID). The results are compared with those obtained using Proportional-Integral-Derivative (PID). The comparison between these two controllers was conducted by evaluating their stability, response speed, and robustness under different system settings and different values of load . The study was organized into four separate cases to make sure a full performance evaluation was done. Using MATLAB/Simulink, the simulation output indicates that the TID controller is marked by a quick correction of frequency and tie-line power variations with low cost much better than the PID controller.

关键词： Photovoltaic systems Renewable energy sources Interconnected systems Power system stability Stability analysis Robustness Wind turbines PD control Frequency control optimization

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FEM using projection of physical properties suitable for movement modeling and optimization processes

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COMPEL-THE international JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING 2020年第5期39卷 1185-1199页

作者： Ristagno, Baptiste Giraud, Dominique Fontchastagner, Julien Netter, Denis Takorabet, Noureddine Devornique, Geoffrey Labbe, Nicolas Univ Lorraine GREEN Nancy France Valeo Elect Syst St Quentin Fallavier France

Purpose optimization processes and movement modeling usually require a high number of simulations. The purpose of this paper is to reduce global central processing unit (CPU) time by decreasing each evaluation time. Design Methodology Approach Remeshing the geometry at each iteration is avoided in the proposed method. The idea consists in using a fixed mesh on which functions are projected to represent geometry and supply. Findings Results are very promising. CPU time is reduced for three dimensional problems by almost a factor two, keeping a low relative deviation from usual methods. CPU time saving is performed by avoiding meshing step and also by a better initialization of iterative resolution. optimization, movement modeling and transient-state simulation are very efficient and give same results as usual finite element method. Research Limitations Implications The method is restricted to simple geometry owing to the difficulty of finding spatial mathematical function describing the geometry. Moreover, a compromise between imprecision, caused by the boundary evaluation, and time saving must be found. Originality Value The method can be applied to optimize rotating machines design. Moreover, movement modeling is performed by shifting functions corresponding to moving parts.

关键词： Electrical machine Finite element method Mesh generation

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Multi-region Decomposition-Coordination Robust optimization Model Considering New Energy Uncertainty

Multi-region Decomposition-Coordination Robust Optimization ...

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IEEE international conference on Power and Energy Systems (ICPES)

作者： Chunxiao Liu Quan Yuan Wei Wang Yinsheng Su Xiangyang Su Ziqiang Wang Power Dispatch and Control Center China Southern Power Grid Co. Ltd. Guangzhou China Dept. of Algorithm Beijing Tsintergy Technology Co. Ltd Guangzhou Branch Guangzhou China

With the continuous development of the power system, the multi regional resource optimization resource allocation in large scale and large regions has considerable prospects. In this paper, a framework of regional optimal dispatching model is proposed. Based on the uncertainty of new energy, a two-stage robust optimization model is proposed. The dual theory and column and constraint generation algorithm are used to solve the two-stage robust optimization model. A multi region decomposition and coordination mechanism based on alternating direction method of multipliers (ADMM) framework is proposed, and an engineering ADMM algorithm framework is given. The simulation analysis proves the feasibility of the proposed model.

关键词： Analytical models Uncertainty Computational modeling Systems operation Convex functions Stability analysis Computational efficiency

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optimization of the control system parameters using the genetic algorithm 14

Optimization of the control system parameters using the gene...

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14th international Scientific and Technical conference on applied Mechanics and Systems Dynamics, AMSD 2020

作者： Denisova, L.A. Alekseytsev, D.M. Meshcheryakov, V.A. Denisov, O.V. Omsk State Technical University 11 Pr. Mira Omsk644050 Russia Automatics - Service LLC 51a Neftezavodskaya Str. Omsk644040 Russia Siberian State Automobile and Highway University 5 Pr. Mira Omsk644080 Russia

The method for parametric optimization of an automatic control system is proposed. The criterion for the quality of the functioning of the system includes control accuracy and control costs. The method takes into account the change in the operating conditions of the control object and the influence of random disturbances. A combination of a genetic algorithm procedure in MATLAB and system simulation in Simulink is proposed. Recommendations for choosing the optimal values of the system parameters are passed on to the operator of the technological process. © Published under licence by IOP Publishing Ltd.

关键词： Genetic algorithms

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TriplePlay: Enhancing Federated Learning with CLIP for Non-IID Data and Resource Efficiency

TriplePlay: Enhancing Federated Learning with CLIP for Non-I...

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international conference on Machine Learning and Applications (ICMLA)

作者： Ahmed Imteaj Md Zarif Hossain Saika Zaman Abdur R. Shahid School of Computing Southern Illinois University Carbondale IL USA Security Privacy and Intelligence for Edge Devices Laboratory (SPEED Lab)

ISBN: (数字)9798350374889

ISBN: (纸本)9798350374896

The recent advancement of pretrained models shows great potential as well as challenges for privacy-preserving distributed machine learning technique called Federated Learning (FL). With the growing demands of foundation models, it is now an urgent need to explore the potential of such foundation models in a distributed setting. In this paper, In this paper, we delve into the complexities of leveraging foundation models, like CLIP into FL frameworks to preserve data privacy, and efficiently training distributed network clients across heterogeneous data landscapes. We specifically aim to address the issues related to non-IID data distributions, skewed class representation of FL clients' local dataset, communication overhead and high resource consumption due to large, complex model training in an FL setting. To address these, we propose TriplePlay, a framework that tailors CLIP foundation model as an adapter to strengthen FL model's performance and adaptability across heterogeneous data distributions among the clients. Besides, we address the long-tail distribution problem in an FL environment to maintain fairness and optimize the computational resource demands of the FL clients through quantization and low-rank adaptation techniques. A comprehensive simulations results with two distinct datasets and different FL settings demonstrate that TriplePlay efficiently reduces GPU usage and accelerates the convergence time that ultimately reduces the communication cost.

关键词： Training Adaptation models Quantization (signal) Heavily-tailed distribution Foundation models Federated learning Computational modeling simulation Data models optimization

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Learning to walk with biped robot based on an improved proximal policy optimization algorithm

Learning to walk with biped robot based on an improved proxi...

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international conference on Intelligent Equipment and Special Robots (ICIESR)

作者： Zhang, Chao Zhong, Peisi Liang, Zhongyuan Liu, Mei Wang, Xiao Liu, Jinming Shandong Univ Sci & Technol Adv Mfg Technol Ctr SDUST Qingdao Peoples R China Shandong Univ Sci & Technol Coll Mech & Elect Engn SDUST Qingdao Peoples R China

ISBN: (数字)9781510651319

ISBN: (纸本)9781510651319;9781510651302

In this paper, a queue batch sampling algorithm is proposed to address the problem of deep reinforcement learning in continuous action control tasks that affects the efficiency of the algorithm due to high sampling correlation. The proposed sampling algorithm reduces the sampling correlation while using the forward value of sampling as a measure to ensure the value of sampling. First, the starting sample is randomly selected as the sampling starting point in the memory bank generated by the robot's interaction with the environment. Second, to save computational resources, the samples in the repository are sampled for the first time, the correlation between the sampling starting point and other samples and the forward multi-step reward of all samples except the sampling starting point is calculated, and the score of each sample based on the ranking position is obtained based on the weighted cumulative results. Finally, the samples with the previous minimum sampling batch size are selected based on the scores to train the deep reinforcement learning model. The proposed queueing batch sampling algorithm is fused with the deep proximal policy optimization algorithm and applied to the forward motion task of a bipedal robot. The proposed improved deep proximal optimization algorithm is compared with the original deep proximal optimization algorithm of the actor-critic framework in simulation, and the learning efficiency of the deep neural network is improved due to the queueing than sampling algorithm which reduces the correlation of sampling and ensures the quality of sampling, and the learning effect of the deep proximal policy optimization algorithm based on queueing batch sampling is significantly improved, that is, the proposed queueing batch sampling algorithm can effectively improve the learning efficiency of bipedal robot learning forward.

关键词： deep reinforcement learning batch sampling algorithm biped robot

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Iraqi Academics Syndicate international conference for Pure and applied Sciences, IICPS 2020

Iraqi Academics Syndicate International Conference for Pure ...

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1st Iraqi Academics Syndicate international conference for Pure and applied Sciences, IICPS 2020

The proceedings contain 235 papers. The topics discussed include: designing a rainstorm over AL-Zafran Valley basin and modeling surface runoff using modern geographic techniques;study faraday effect on optical properties for polymers blend doping metal nanoparticles;identification of analogue modulated signal via artificial intelligence;optimization of the database function transactions by using the fireworks algorithm;seismic images interpretation to discover salt domes using deep fully convolutional network;structural characterization of NiO nanoparticles prepared by green chemistry synthesis using Arundo donaxi leaves extract;investigation on μ-opioid receptor in Sera of Iraqi male addiction tramadol or methamphetamine;study of cellular immune response and some of the blood variables in children with celiac disease;and electrochemical performance enhancement zinc cobaltite-reduced graphene oxide for next generation energy storage applications.

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Design and optimization of simultaneous wireless power transfer and near field communication systems

Design and optimization of simultaneous wireless power trans...

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2021 international Exhibition and conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Europe 2021

作者： Merz, Christian Gückelhorn, Daniel Som, Cem Würth Elektronik eiSos GmbH & Co. KG Germany Munich University of Applied Sciences Germany

ISBN: (纸本)9783800755158

Würth Elektronik eiSos (WE) has developed a system that implements inductive wireless power transfer (WPT) along with simultaneous near field communication (NFC). The system uses a new product that combines WPT and NFC with an NFC antenna wrapped around the WPT coil to form a single efficient component. This paper describes the design goals and the optimization steps required for simultaneous operation of the WPT and NFC. This investigation is done by measurement, calculation and simulation. The developed WPT/NFC system is the first published simultaneous operating system delivering up to 190 W output power at a transfer distance of 1 cm and a data rate of 106 kbit/s with an error rate of 0 %. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Near field communication

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Unveiling Designers' Cognitive States in Early Engineering Design Stages: An Autoencoder-DNN Approach based on EEG Data*

Unveiling Designers' Cognitive States in Early Engineering D...

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IEEE international conference on Automation Science and Engineering (CASE)

作者： Mingrui Li Zuoxu Wang Fan Li Jihong Liu School of Mechanical Engineering and Automation Beihang University Beijing China Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Hong Kong Special Administrative Region

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Early engineering product design stages, such as innovative conceptual design and product form design, require intensive thinking by designers. During these tasks, designers experience constantly shifting cognitive states of either Trance, Concentration or Confusion. Accurately recognizing designer’s cognitive states is a prerequisite task to provide assistance, e.g. design knowledge recommendation, to designers timely. Electroencephalogram (EEG) data is the external expression of designers’ cognitive states. However, current research on applying EEG technology in engineering design scenarios lacks automatic selection of significant features from EEG information, and the connection with the design process is also limited. Faced with such issues, this study proposes a cognitive state recognition procedure for engineering design scenarios, including a recognition model and an experiment protocol. The Autoencoder-Deep Neural Network (DNN)-based recognition model can flexibly select significant features to achieve accurate cognitive state recognition, while the two-stage experiment protocol can collect standard cognitive state data and perform validation in the simulation of real design scenarios. The experiment results demonstrate the validity of the proposed recognition procedure, and confirmed that states of Concentration and Confusion can be utilized to determine whether designers need assistance.

关键词： Protocols Face recognition Brain modeling Electroencephalography Data models Reflection Product design Standards Unsupervised learning optimization

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optimization and Design Based on Data Visualization of Enterprise-class Crawler Systems for Shipping 3

Optimization and Design Based on Data Visualization of Enter...

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2020 3rd international conference on modeling, simulation and optimization Technologies and Applications, MSOTA 2020

作者： Wu, Hao School of Computer Science Jluzh Zhuhai China

The designed crawler scheduling system is a JEE application based on Quartz scheduling framework that sends crawler tasks to the crawler control system automatically or manually at regular intervals. The crawler control system visually manages and controls the shipping crawlers. The HttpCilent-centric crawler system crawls the shipping website. The message queue ActiveMQ is used as a message middleware for the crawler control system and the crawler system to achieve asynchronous communication and reduce coupling. In this system, front-end frameworks such as Bootstrap, AngularJS, and SweetAlert are used to implement a visual scheduling system and data visualization system. Change the crawler deployment environment by deploying containers through Docker. Add Selenium dynamic page processing for shipping website. Adding message queues and MongoDB database data storage. By adopting a series of techniques and designing, testing and quality assurance of the system, we aim to make the crawler more stable and efficient, and to achieve security, stability and ease of maintenance of the system. © Published under licence by IOP Publishing Ltd.

关键词： Data visualization

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