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Energy Technologies for Future Grids (ETFG), IEEE International Conference on

作者： Hamza M. Anwar Md Shafiullah M. A. Abido Electrical Engineering Department King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Saudi Arabia Control & Instrumentation Engineering Department KFUPM Dhahran Saudi Arabia IRC for Renewable Energy and Power Systems KFUPM Dhahran Saudi Arabia SDAIA-KFUPM Joint Research Center for Artificial Intelligence (JRCAI) KFUPM Dhahran Saudi Arabia

Faults are common and potentially dangerous problems in low-voltage power system networks, e.g., distribution networks. Upon discovery, they must be dealt with immediately to prevent further damage to the distribution system and quickly return electricity to consumers. This paper proposes a hybrid fault diagnosis method combining a signal processing technique with deep learning models. Faults are applied in a four-node test distribution feeder developed using MATLAB and Simulink. Different measurement noise levels are implemented, along with varying load and fault parameters. The short-time Fourier transform (STFT) is used on the feeder’s current signals as a feature extraction tool. These features are then used to train deep learning models to detect, classify, and locate faults. Various parameters of the models are varied to find the optimum ones, which are used to obtain the results. The findings show that the model performed exceptionally well in fault detection and classification and satisfactorily in fault location.

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Robustness and muliple dominant pole method 21

Robustness and muliple dominant pole method

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21st IEEE International Carpathian control Conference, ICCC 2020

作者： Viteckova, Miluse Vitecek, Antonin Janacova, Dagmar VSB-Technical University of Ostrava Department of Control Systems and Instrumentation Ostrava Czech Republic Tomas Bata University in Zlin Department of Automation and Control Engineering Zlin Czech Republic

The paper is devoted to the determination of robust stability regions for PI and PID controllers for first order plants with time delay and integrating plants with time delay. The multiple dominant pole method is cons... 详细信息

ISBN: (纸本)9781728119519

关键词： Time delay

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Short-Term Wind Speed Prediction for Saudi Arabia via 1D-CNN

Short-Term Wind Speed Prediction for Saudi Arabia via 1D-CNN

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IEEE International Conference on System engineering and Technology

作者： Abdulrahman Katranji Md Shafiullah Shafiqur Rehman Electrical Engineering Department King Fahad University of Petroleum & Minerals (KFUPM) Dhahran Saudi Arabia Control & Instrumentation Engineering IRC for Renewable Energy and Power Systems (IRC-REPS) K.A.CARE Energy Research & Innovation Center (ERIC) KFUPM Dhahran Saudi Arabia IRC for Renewable Energy and Power Systems (IRC-REPS) KFUPM Dhahran Saudi Arabia

As fluctuating wind power is incorporated into the energy mix, grid operators encounter dire challenges. Managing grid operations requires accurate knowledge of available wind power and its variation with time. Wind power can be estimated by providing reliable and fast wind speed prediction at different hub heights. Hence, this study proposes a one-dimensional convolutional neural network (1D-CNN) model for wind speed prediction at different heights and aboveground levels (AGL). The results of the proposed model are compared with three deep learning models to validate its repeatability. The results show a competitive performance between the proposed model and the gated recurrent unit (GRU) network. Furthermore, the study indicates that capturing wind speed at 18m height for training is sufficient for predicting wind speed at higher elevations. Further research could focus on adding exogenous variables to assess their impact on predicting wind speed at different AGL heights.

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Improved vehicle navigation using sensor fusion of inertial, odometeric sensors with global positioning system

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International Journal of Vehicle Autonomous systems 2020年第3-4期15卷 307-318页

作者： Allan Anbu, N. Pinagapani, Arun Kumar Mani, Geetha Chandran, K.R. Department of Instrumentation and Control Systems Engineering PSG College of Technology Tamil Nadu Coimbatore India Vellore Institute of Technology Tamil Nadu Vellore India Department of Information Technology PSG College of Technology Tamil Nadu Coimbatore India

The primary objective of a navigation system is to continuously monitor the trajectory of a vehicle. Navigation for a land vehicle is implemented using different measurement systems, such as Inertial Navigation System (INS), radio navigation system, vision-based navigation and Global Positioning System (GPS). INS provides continuous information of position, velocity and attitude. However, its performance deteriorates with time since the errors tend to accumulate. GPS is an electromagnetic signal which is more accurate when compared to INS but cannot provide continuous and reliable position all the time. The drawbacks of these individual systems have given rise to the need for higher accuracy, integrity and robustness. This has led to the fusion of measurements from these sensors to obtain an improved performance in measuring the position, velocity of a vehicle. This paper discusses the simulation and implementation of an integrated navigation system using inertial, odometric sensors with GPS using scaled unscented Kalman filter. The method discussed involves obtaining a state transition model and a measurement model of the sensors and processing the states using scaled unscented Kalman filter to obtain better estimates of position and velocity. Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Stochastic systems

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Enhanced Voltage Stability for DC Microgrids Integrating Hybrid Electric Vehicles with Virtual Inertia and Damping control

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Transportation Research Procedia 2025年 84卷 571-578页

作者： Hossam Ali Mohamed Zaery Syed Muhammad Amrr S.M. Suhail Hussain Vijay Vital Mohammad A. Abido Department of Electrical Engineering Faculty of Energy Engineering Aswan University 81528 Aswan Egypt School of Electrical Computer and Energy Engineering Arizona State University Tempe AZ 85281 USA K.A.CARE Energy Research & Innovation Center King Fahd University of Petroleum and Minerals (KFUPM) Dhahran 31261 Saudi Arabia Control & Instrumentation Engineering Department KFUPM Dhahran 31261 Saudi Arabia Interdisciplinary Research Center for Sustainable Energy Systems KFUPM Dhahran 31261 Saudi Arabia Electrical Engineering Department King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia SDAIA-KFUPM Joint Research Center for Artificial Intelligence KFUPM Dhahran 31261 Saudi Arabia

DC microgrids (MGs) have experienced swift growth, driven by the expanding integration of energy storage devices(ESD), renewable energy sources (RESs), and localized loads. However, it suffers from insufficient inertia owing to less rotating mass sources, which can lead to poor voltage stability. This paper introduces a control method that emulates both inertia and damping to mitigate fluctuations in DC voltage, enhance system stability, and address the low inertia concern. The proposed virtual inertia and damping (VID) control system is adopted through using hybrid electric vehicle (HEV). The suggested HEV comprises three power sources: a battery, a fuel cell (FC), and a supercapacitor (SC). In this setup, both the battery and the FC are employed to supply virtual damping owing to their high-energy density, and the SC is utilized to support virtual inertial characteristics due to its high-power density. Through this approach, enhancements in the DC voltage stability of an islanded DC MG can be achieved. Simulations demonstrate that the proposed control system significantly outperforms existing works utilizing virtual inertia (VI) based on an EV’s battery only, as well as over systems lacking VI. The proposed control system effectively reduces voltage fluctuations and improves system stability, specifically in terms of the rate of change of voltage (ROCOV) and accelerated settling time.

关键词： Voltage Stability DC Microgrids Virtual Inertia Damping Hybrid Electric Vehicle Renewable Energy Sources

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Breakdown of effective-medium theory by a photonic spin Hall effect

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Science China(Physics,Mechanics & Astronomy) 2023年第11期66卷 145-154页

作者： Shuaijie Yuan Xinxing Zhou Yu Chen Yuhan Zhong Lijuan Sheng Hao Hu Hongsheng Chen Ido Kaminer Xiao Lin Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Synergetic Innovation Center for Quantum Effects and ApplicationsSchool of Physics and ElectronicsHunan Normal UniversityChangsha410081China International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology Engineering Technology Research Center for 2D Material Information Function Devices and Systems of Guangdong ProvinceInstitute of Microscale OptoelectronicsShenzhen UniversityShenzhen518060China Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and InstrumentationZJU-Hangzhou Global Scientific and Technological Innovation CenterZhejiang UniversityHangzhou310027China International Joint Innovation Center Electromagnetics Academy at Zhejiang UniversityZhejiang UniversityHaining314400China School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore639798Singapore Key Laboratory of Radar Imaging and Microwave Photonics Ministry of EducationCollege of Electronic and Information EngineeringNanjing University of Aeronautics and AstronauticsNanjing211106China Key Laboratory of Advanced Micro/Nano Electronic Devices&Smart Systems of Zhejiang Jinhua Institute of Zhejiang UniversityZhejiang UniversityJinhua321099China Shaoxing Institute of Zhejiang University Zhejiang UniversityShaoxing312000China Department of Electrical Engineering Technion-Israel Institute of TechnologyHaifa32000Israel

Effective-medium theory pertains to the theoretical modelling of homogenization,which aims to replace an inhomogeneous structure of subwavelength-scale constituents with a homogeneous effective *** effective-medium theory is fundamental to various realms,including electromagnetics and material science,since it can largely decrease the complexity in the exploration of light-matter interactions by providing simple acceptable ***,the effective-medium theory is thought to be applicable to any all-dielectric system with deep-subwavelength constituents,under the condition that the effective medium does not have a critical angle,at which the total internal reflection *** we reveal a fundamental breakdown of the effective-medium theory that can be applied in very general conditions:showing it for deep-subwavelength all-dielectric multilayers even without a critical *** finding relies on an exotic photonic spin Hall effect,which is shown to be ultrasensitive to the stacking order of deep-subwavelength dielectric layers,since the spin-orbit interaction of light is dependent on slight phase accumulations during the wave *** results indicate that the photonic spin Hall effect could provide a promising and powerful tool for measuring structural defects for all-dielectric systems even in the extreme nanometer scale.

关键词： photonic spin Hall effect effective-medium theory spin-orbit interaction of light

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The Goldilocks Framework: Towards Selecting the Optimal Approach to Conducting AI Projects

The Goldilocks Framework: Towards Selecting the Optimal Appr...

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AI engineering - Software engineering for AI (WAIN), IEEE/ACM Workshop on

作者： Rimman Dzhusupova Jan Bosch Helena Holmströ m Olsson Dept. of Electrical &#x0026 Instrumentation Control &#x0026 Safety Systems McDermott The Hague The Netherlands Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Computer Science and Media Technology Malm&#x00F6 University Malm&#x00F6 Sweden

Artificial intelligence is increasingly becoming important to businesses since many companies have realized the benefits of applying Machine Learning (ML) and Deep Learning (DL) into their operations. Nevertheless, ML/DL technologies’ industrial development and deployment examples are still rare and generally confined within a small cluster of large international companies who are struggling to apply ML more broadly and deploy their use cases at a large scale. Meanwhile, current AI market has started offering various solutions and services. Thus, organizations must understand how to acquire AI technology based on their business strategy and available resources. This paper discusses the industrial experience of developing and deploying ML/DL use cases to support organizations in their transformation towards AI. We identify how various factors, like cost, schedule, and intellectual property, can be affected by the choice of approach towards ML/DL project development and deployment within large international engineering corporations. As a research result, we present a framework that covers the trade-offs between those various factors and can support engineering companies to choose the best approach based on their long-term business strategies and, therefore, would help to accomplish their ML/DL project deployment successfully.

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Challenges in developing and deploying AI in the engineering, procurement and construction industry

Challenges in developing and deploying AI in the engineering...

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Rimma Dzhusupova Jan Bosch Helena Holmströ m Olsson Dept. of Electrical &#x0026 Instrumentation Control &#x0026 Safety Systems McDermott The Hague The Netherlands Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Computer Science and Media Technology Malm&#x00F6 University Malm&#x00F6 Sweden

ISBN: (数字)9781665488105

ISBN: (纸本)9781665488112

AI in the engineering, Procurement and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Several research papers exist describing the potential of AI, and many surveys and white papers have been published indicating the challenges of AI deployment in the EPC industry. However, there is a recognizable shortage of in-depth studies of deployment experience in academic literature, particularly those focusing on the experiences of EPC companies involved in large-scale project execution with high safety standards, such as the petrochemical or energy sector. The novelty of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.

关键词： Industries Procurement Companies Manuals Petrochemicals Software Safety

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基于自解耦三明治结构的横向运动栅场效应晶体管MEMS微力传感器

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engineering 2023年第2期21卷 61-74,M0004页

作者：高文迪乔智霞韩香广王小章 Adnan Shakoor 刘存朗卢德江杨萍赵立波王永录王久洪蒋庄德孙东 State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesOverseas Expertise Introduction Center for Micro/Nano Manufacturing and Nano Measurement Technologies Discipline InnovationXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemSchool of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265503China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150006China Eleventh Research Institute Sixth Academy of China Aerospace Science and Technology Co.Xi’an 710100China Department of Control and Instrumentation Engineering King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia Department of Biomedical Engineering City University of Hong KongHong Kong 999077China

本文介绍了一种基于横向可移动栅极场效应晶体管(LMGFET)的新型微型力传感器的开发。提出了一种精确的电气模型,用于小型LMGFET器件的性能评估,与以前的模型相比,其精度有所提高。采用了一种新型三明治结构,该结构由一个金交叉解耦栅阵... 详细信息

本文介绍了一种基于横向可移动栅极场效应晶体管(LMGFET)的新型微型力传感器的开发。提出了一种精确的电气模型,用于小型LMGFET器件的性能评估,与以前的模型相比,其精度有所提高。采用了一种新型三明治结构,该结构由一个金交叉解耦栅阵列层和两个软光阻层SU-8组成。通过所提出的双差分传感结构,LMGFET横向工作在垂直干扰下的输出电流被大大消除,所提出传感器的相对输出误差从4.53%(传统差分结构)降低到0.01%。提出了一种实用的传感器制造工艺,并对其进行了模拟。基于LMGFET的力传感器的灵敏度为4.65μA·nN^(-1),可与垂直可移动栅极场效应晶体管(VMGFET)器件相媲美,但非线性度提高了0.78%,测量范围扩大了±5.10μN。这些分析为LMGFET器件的电气和结构参数提供了全面的设计优化,并证明了所提出的传感器在生物医学显微操作应用中具有良好的力传感潜力。

关键词：力传感器场效应晶体管横向运动三明治结构电气模型显微操作非线性度双差分

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Distributed Secondary Frequency Regulation in AC Microgrid with Arbitrary Convergence Time control

Distributed Secondary Frequency Regulation in AC Microgrid w...

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Sustainable Power and Energy Conference (iSPEC)

作者： Syed Muhammad Amrr Mohammad Ali Abdullah Abushokor Mohamed Zaery Mujahed Al-Dhaifallah S. M. Suhail Hussain Mohammad A. Abido Control & Instrumentation Engineering Department King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Saudi Arabia Interdisciplinary Research Center for Sustainable Energy Systems (IRC-SES) KFUPM Dhahran Saudi Arabia Department of Electrical Engineering ZHCET Aligarh Muslim University Aligarh India K.A.CARE Energy Research & Innovation Center KFUPM Dhahran Saudi Arabia Electrical Engineering Department KFUPM Dhahran Saudi Arabia SDAIA-KFUPM Joint Research Center for Artificial Intelligence KFUPM Dhahran Saudi Arabia

ISBN: (数字)9798350395075

ISBN: (纸本)9798350395082

This paper presents a new approach for designing the arbitrary time-convergent distributed secondary frequency control for AC microgrid (MG). The proposed controller will regulate the frequencies of distributed generators (DGs) to the desired reference value within the user-defined arbitrarily selected time. In addition to restoring frequency, the designed scheme achieves optimal consensus for incremental costs, i.e., it effectively distributes the power load across all DGs. The convergence analysis of both tracking and consensus error is mathematically proven using the Lyapunov stability theory, ensuring arbitrary time convergence. The simulation analysis with comparative case studies demonstrates the superior performance of the proposed decentralized arbitrary time-convergent algorithm compared to existing fixed-time and finite-time approaches.

关键词： Time-frequency analysis Costs Simulation Microgrids Generators Frequency synchronization Frequency control Convergence Lyapunov methods

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