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2024 International Conference on Artificial Intelligence of Things and systems, AIoTSys 2024

作者： Qiu, Dongmeng Liu, Mengxiang Zhang, Xin University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798331507886

The rapid digitalisation process in power system has greatly benefited the large-scale integration of distributed energy resources (DERs), essentially accelerating the progress towards net zero. However, numerous cyber attacks such as false data injection (FDI) attacks are impeding the normal control and operation activities. This paper aims to establish a real-Time microgrid co-simulation platform to fully study the impacts of realistic attack events on micorgrid's control performance. Although there exist a large number of power-communication co-simulation platforms for the power system, they are designed to mainly provide validation services for control and operation algorithms and little attention has been paid to the cyber security. In the established microgrid platform, power and communication parts are simulated in Typhoon Hardware-in-The-loop(HIL) 602+ and EXata Network Simulator, respectively, and a dedicated synchronisation scheme is developed and embedded in Raspberry Pis to achieve master-slave data exchange between them. Based on the advanced cyber libraries provided by EXata, realistic FDI and packet drop attacks are mounted against the mapped communication links within EXata. The results indicate that these cyber attacks can severely influence the microgrid control performance including destabilising system states and specific state deviations, further demonstrating the necessity of deploying effective cyber-resilience enhancement mechanisms. © 2024 IEEE.

关键词： Cyber attacks

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A Multi-Robot Allocation Scheme for Coverage control Applications with Multiple Areas of Interest 9

A Multi-Robot Allocation Scheme for Coverage Control Applica...

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9th International Conference on control, Decision and Information Technologies, CoDIT 2023

作者： Duca, Rachael N. Bugeja, Marvin K. University of Malta Department of Systems and Control Engineering Malta

ISBN: (纸本)9798350311402

Coverage control with a multi-robot system requires the robot team to be optimally distributed across some environment. This environment may have multiple, distinct areas of interest, each of which associated with a specific task that requires robots with particular capabilities. In such scenarios, the first problem to be solved is that of assigning each robot in the team to one of the importance areas, while accounting for the robots' capabilities and the task/area requirements. This paper investigates this problem and proposes a novel multi-robot task allocation (MRTA) scheme in the context of coverage control. More specifically, the proposed method employs integer linear programming (ILP) to solve the constrained robot-to-task allocation problem. The resulting algorithm allocates each robot in the heterogeneous team to one of the importance areas, subject to a number of realistic constraints such as the tasks' requirements, and the robots' capabilities and energy levels. Our approach introduces elements of fault tolerance and robustness to situational changes, since it can also be executed periodically during the coverage process, to reassign the robots in case of robot faults, changes in the tasks/areas, and other factors that alter the allocation solution. The proposed scheme also has the advantage of being separate from the coverage control algorithm, and therefore supports a modular framework. Finally, a set of realistic simulated scenarios are used to validate the task allocation scheme being proposed. © 2023 IEEE.

关键词： Multipurpose robots

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Learning Input Driven Dynamic Bayesian Networks with Measurement Noise 23

Learning Input Driven Dynamic Bayesian Networks with Measure...

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23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Veres, David Li, Ping Kadirkamanathan, Visakan The University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350374889

Dynamic Bayesian Networks (DBNs) are useful tools for modelling complex systems whose network representations can be elicited a priori or learnt from data. In this paper, a maximum likelihood Doubly-Iterative Expectation Maximization (DI-EM) Algorithm is developed for the identification of grey-box ARMAX state-space model representations of DBNs involving known, noisy measurement processes. The grey-box model incorporates network dependencies among time series variables and exploits time series data of low longitudinal and high cross-sectional dimensions. A network learning procedure is developed using a score-based structure-selection method to find the underlying network of an input-driven dynamical system. By computing a finite data version of the Bayesian Information Criterion (BIC) for small sample sizes, the proposed method's performance is investigated on simulated and real-world data. The algorithm recovers the underlying ground-truth networks of simulated systems under finite data criteria with Jaccard Coefficient values of up to 0.84, and selects structures with improved weighted mean-squared error loss over a baseline black-box model fit on real-world data. © 2024 IEEE.

关键词： Expectation maximization algorithm

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Comprehensive 3E -energetic, economic, and environmental-analysis of a hybrid solar dish-Brayton engine and fuel cell system for green hydrogen and power generation

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International Journal of Hydrogen Energy 2025年 140卷 1062-1077页

作者： Shboul, Bashar Zayed, Mohamed E. Alrbai, Mohammad Kafiah, Feras Almomani, Fares Renewable Energy Engineering Department Faculty of Engineering Al Al-Bayt University Mafraq Jordan Interdisciplinary Research Center for Sustainable Energy Systems King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia Department of Mechanical Engineering School of Engineering University of Jordan Amman11942 Jordan Mechanical Engineering Department Al Hussein Technical University Amman11831 Jordan Department of Chemical Engineering Qatar University Qatar

This work aims to assess the energy, economic, and environmental performance of a novel hybrid solar dish Bryton engine and fuel cell (SDBE-FC) system for generating green hydrogen and electricity. The system includes solar dish units, fuel cells, an electrolyzer, a converter, and a hydrogen storage tank. The study introduces a novel SDBE-FC system, replacing typical photovoltaic/fuel cell setups, to achieve higher efficiency and improved financial and environmental competitiveness. A vigorous energy-enviro-economic analysis is carried out using MATLAB/Simulink® to model system components. Key parameters have been analyzed, including the electrolyzer efficiency, flow rate, power, and the SDBE plant and FC stack's power, area, and efficiency. The total levelized cost of energy (LCOE) and the reduction in CO2 emissions are also calculated. Results showed that using 50 stacked fuel cells achieved an efficiency of 7%, increasing the number of staked fuel cells to 400 increased the efficiency by eightfold achieving a peak power of 297 kW. The efficiency and power output of the fuel cell decreased by 16% and 22.2%, respectively, when the operational temperature increased from 40 °C to 80 °C. Furthermore, LCOE as low as 0.218 US$/kWh was achieved using 25 SDBE units at 1100 °C. At 30 kW, the SDBE system produces 750 kW of power with 18.3% efficiency and occupies 4099.8 m2 as the temperature (Th) reaches to 1100 °C. The SDBE, with a rated power range of 15 kW–30 kW, achieved a 390.8% CO2 emissions reduction, amounting to 34,120.76 tons of CO2, when 25 SDBE units were utilized. © 2024 Hydrogen Energy Publications LLC

关键词： Brayton cycle

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Programming-via-spinning: Electrospun shape memory polymer fibers with simultaneous fabrication and programming

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Smart Materials in Medicine 2024年第4期5卷 477-487页

作者： Gunderson, Avery Ramezani, Maryam Orado, Thalma K. Monroe, Mary Beth B. Department of Biomedical and Chemical Engineering and BioInspired Syracuse: Institute for Material and Living Systems Syracuse University SyracuseNY13244 United States

Porous shape memory polymer (SMP) scaffolds are promising ‘smart’ materials for potential use in a wide range of biomedical applications. Electrospinning provides an approach to produce fibrous SMP scaffolds to enhance their porosity, mass transfer, and flexibility. Here, we studied the effects of electrospinning parameters (rotating collector rotational speed and solvent) on shape memory and mechanical properties of a biostable thermoplastic polyurethane (PUr) SMP. Scanning electron microscopy confirmed that fiber diameter and tortuosity could be tuned using varied collector rotation speeds and/or solvents. Mechanical properties, including modulus, tensile strength, and ultimate elongation, were tuned independently of chemistry based on variations in fiber architectures. All scaffolds demonstrated shape memory properties. Additionally, due to strains that are trapped in the fibers during the electrospinning process, SMP fibers are programmed into a strained, temporary shape during the fabrication step. These fibers can be immediately triggered to recover to a non-strained primary shape after fabrication to reduce sample preparation time and complexity. As a proof-of-concept, bacterial protease-responsive SMPs were electrospun and exposed to S. aureus in programmed secondary shapes. Upon exposure to bacteria, these SMPs underwent shape recovery, which resulted in reduced bacterial attachment and biofilm formation. These materials could be employed as bacteria-responsive wound dressings in future work. Overall, electrospinning provides a valuable tool for tuning mechanical and shape memory properties independently from chemistry and for programming SMPs during fabrication to enable scale-up of electrospun SMP scaffolds. © 2024 The Authors

关键词： Tensile strength

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Analysis on carbon emission reduction intensity of fuel cell vehicles from a life-cycle perspective

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Frontiers in Energy 2024年第1期18卷 16-27页

作者： Ziyuan TENG Chao TAN Peiyuan LIU Minfang HAN Fuel Cell and Energy Storage Center Department of Energy and Power EngineeringState Key Laboratory of Control and Simulation of Power Systems and Generation EquipmentTsinghua UniversityBeijing 100084China

The hydrogen fuel cell vehicle is rapidly developing in China for carbon reduction and *** paper evaluated the life-cycle cost and carbon emission of hydrogen energy via lots of field surveys,including hydrogen production and packing in chlor-alkali plants,transport by tube trailers,storage and refueling in hydrogen refueling stations(HRSs),and application for use in two different *** also conducted a comparative study for battery electric vehicles(BEVs)and internal combustion engine vehicles(ICEVs).The result indicates that hydrogen fuel cell vehicle(FCV)has the best environmental performance but the highest energy ***,a sufficient hydrogen supply can significantly reduce the carbon intensity and FCV energy cost of the current *** carbon emission for FCV application has the potential to decrease by 73.1%in City A and 43.8%in City *** only takes 11.0%–20.1%of the BEV emission and 8.2%–9.8%of the ICEV *** cost of FCV driving can be reduced by 39.1%in City *** improvement can be obtained with an economical and“greener”hydrogen production pathway.

关键词： hydrogen energy life-cycle assessment(LCA) fuel cell vehicle carbon emission energy cost

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A hybrid machine-learning model for solar irradiance forecasting

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Clean Energy 2024年第1期8卷 100-110页

作者： Ameera M.Almarzooqi Maher Maalouf Tarek H.M.El-Fouly Vasileios E.Katzourakis Mohamed S.El Moursi Constantinos V.Chrysikopoulos Department of Industrial and Systems Engineering Khalifa UniversityAbu DhabiPO Box 127788UAE Electrical Engineering and Computer Science Department Khalifa University Abu DhabiUAE Department of Civil Infrastructure and Environmental Engineering Khalifa UniversityAbu DhabiPO Box 127788UAE School of Chemical and Environmental Engineering Technical University of CreteChaniaGreece

Nowcasting and forecasting solar irradiance are vital for the optimal prediction of grid-connected solar photovoltaic(PV)power *** plants face operational challenges and scheduling dispatch difficulties due to the fluctuating nature of their power *** the generation capacity within the electric grid increases,accurately predicting this output becomes increasingly essential,especially given the random and non-linear characteristics of solar irradiance under variable weather *** study presents a novel prediction method for solar irradiance,which is directly in correlation with PV power output,targeting both short-term and medium-term forecast *** proposed hybrid framework employs a fast trainable statistical learning technique based on the truncated-regularized kernel ridge regression *** proposed method excels in forecasting solar irradiance,especially during highly intermittent weather periods.A key strength of our model is the incorporation of multiple historical weather parameters as inputs to generate accurate predictions of future solar irradiance values in its scalable *** evaluated the performance of our model using data sets from both cloudy and sunny days in Seattle and Medford,USA and compared it against three forecasting models:persistence,modified 24-hour persistence and least *** on three widely accepted statistical performance metrics(root mean squared error,mean absolute error and coefficient of determination),our hybrid model demonstrated superior predictive accuracy in varying weather conditions and forecast horizons.

关键词： solar power generation kernel ridge regression hybrid model forecasting

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HKB-YOLO: transmission line fire detection method based on hierarchical feature fusion

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International Journal of Security and Networks 2024年第4期19卷 188-198页

作者： Ying, Zhilei Meng, Yanan Chen, Ruoxi Lou, Jianlou School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin 132022 China Department of Automation Jilin Institute of Chemical Technology Jilin 132022 China School of Computer Engineering Northeast Electric Power University Jilin 132012 China

Timely transmission line fire inspections are vital for power system safety. Although deep learning models are widely used for flame detection, struggle with small target recognition due to background interference and are vulnerable to input data perturbations, posing security risks. This study introduces a hierarchical feature fusion method based on the you only look once Version 8 (YOLOV8) framework. It employs high-performance GPU network version 2 (HGNetV2) to enhance small-target feature extraction while reducing computational complexity. A spatial pyramid pooling-fast module with large separable kernel attention is designed to highlight key features and suppress background noise. The proposed bidirectional slim neck structure (BiSlimneck) reduces feature loss. Adversarial training enhances the model’s robustness. Experimental results show a 1.4% accuracy improvement, with a reduction in parameters and complexity by 18.3% and 21.6%, respectively. After adversarial training, the accuracy of the network in the face of attacks increased by 10% compared to the pre-training. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Premixed flames

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Utilization of Uniform Circular Array for Estimating RF Source Location in Real-time

Utilization of Uniform Circular Array for Estimating RF Sour...

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2024 International Conference on control, Automation and Diagnosis, ICCAD 2024

作者： Alsayegh, Hamad Almuhaihi, Mohammad University of Sheffield Automatic Control and Systems Engineering Department United Kingdom University of Michigan Aerospace Engineering Department United States

ISBN: (纸本)9798350361025

This Radio Frequency (RF) source location estimation scheme utilizes angles of arrival of a signal source acquired from the Multiple Signal Classification (MUSIC) algorithm. In reliance on that as a Maximum Likelihood estimation, the obtained angles are augmented to an adaptive probability distribution function (PDF), which is then employed to estimate the location of the RF emitter by feeding the PDF to an Extended Kalman Filter (EKF). Numerous use cases and theoretical works have been presented in the literature. Some of these papers mention applications regarding implementing DoA algorithms in dynamic platforms like in [9], [10], [11], [12], and [13] mostly all of them use Uniform Linear Array (ULA), four of them working with Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), and one with MUSIC Direction of Arrival (DoA) method. In [14], MUSIC was used with a Uniform Circular Array (UCA). However, less coupling has been incorporated with the covariance of measurement error. In this paper, the dynamic 2D DoA MUSIC algorithm used in a platform, applied together with an EKF estimation and coupled with measurement covariance in a simulation environment to precisely locate an RF emitter and provide high-resolution Line-of-Sight (LOS). © 2024 IEEE.

关键词： Multiple signal classification

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High-Capacity DWDM Transmission System for Free-Space Optical Network 6

High-Capacity DWDM Transmission System for Free-Space Optica...

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6th International Conference on Electrical, control and Instrumentation engineering, ICECIE 2024

作者： Rahman, M.T. Jahid, M.A. Anha, S.Y. Rahman, Md. Shohanur Azmi Orpy, F. Bakibillah, A.S.M. Department of Computer Science and Engineering Bangladesh Tokyo Institute of Technology Department of Systems and Control Engineering Tokyo152-8552 Japan

ISBN: (纸本)9798350380040

This study presents the architecture and performance evaluation of a high-capacity free-space optical (FSO) communication system that makes use of dense wavelength division multiplexing (DWDM) and a 1.28 Tb/s link. The system under consideration comprises 64 individual channels, each of which is capable of transferring data streams at a speed of 20 Gbps. A return-to-zero (RZ) line coding algorithm is incorporated to maximize performance across 2.0 km of FSO link. Important parameters that affect the system's performance, like beam divergence and atmosphere attenuation, are taken into account in the analysis. The signals' bit-error-rate (BER), quality factor (Q), and eye diagrams are calculated and examined to assess the system's performance. For future optical-wireless networks that require significant bandwidth capabilities, cost-effective implementation, and increased flexibility, this novel high-capacity design offers a promising solution. The results aid in the development of dependable and useful high-speed FSO communication systems. © 2024 IEEE.

关键词： Cost effectiveness

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