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Very Short-Term Probabilistic Prediction Method for Wind Speed Based on ALASSO-Nonlinear Quantile Regression and Integrated Criterion

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CSEE Journal of Power and Energy systems 2023年第6期9卷 2121-2129页

作者： Yan Zhou Yonghui Sun Sen Wang Linquan Bai Dongchen Hou Rabea Jamil Mahfoud Peng Wang the College of Energy and Electrical Engineering Hohai UniversityNanjing 210098China Department of Systems Engineering and Engineering Management the University of North CarolinaCharlotte NC 28223USA

To enhance the performance of the prediction intervals (PIs), a novel very short-term probabilistic prediction method for wind speed via nonlinear quantile regression (NQR) based on adaptive least absolute shrinkage and selection operator (ALASSO) and integrated criterion (IC) is proposed. The ALASSO method is studied for shrinkage of output weights and selection of variables. Furthermore, for the better performance of PIs, composite weighted linear programming (CWLP) is proposed to modify the conventional linear programming cost function of quantile regression (QR), by combining it with Bayesian information criterion (BIC) as an IC to optimize the coefficients of PIs. Then, the multiple fold cross model (MFCM) is utilized to improve the PIs performance. Multistep probabilistic prediction of 15-minute wind speed is performed based on the real wind farm data from the northeast of China. The effectiveness of the proposed approach is validated through the performances' comparisons with conventional methods.

关键词： Composite weighted linear programming least absolute shrinkage and selection operator integrated criterion wind speed

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Techno-economic analysis of green hydrogen production by a floating solar photovoltaic system for industrial decarbonization

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Clean Energy 2024年第4期8卷 1-14页

作者： Rahma Muthia Anastasia Segari Putri Pramudya Mochamad Rafly Maulana Widodo Wahyu Purwanto Department of Chemical Engineering Faculty of EngineeringUniversitas IndonesiaDepok16424Indonesia Sustainable Energy Systems and Policy Research Cluster Universitas IndonesiaDepok16424Indonesia Master Program in Energy Systems Engineering Faculty of EngineeringUniversitas IndonesiaDepok16424Indonesia

This study proposes a conceptual design of green hydrogen production via proton exchange membrane electrolysis powered by a floating solar photovoltaic *** system contributes to industrial decarbonization in which hydrogen blending with natural gas is proposed as an approach to smooth the energy *** proposed design addresses the challenge of supplying a continuous flow-rate of green hydrogen,which is typically demanded by industrial end *** study particularly considers a realistic area required for the installation of a floating solar photovoltaic *** enable the green hydrogen production of 7.5 million standard cubic feet per day,the required structure includes the floating solar photovoltaic system and Li-ion batteries with the nominal capacities of 518.4 megawatts and 780.8 *** is equivalent to the requirement for 1524765 photovoltaic modules and 3718 Li-ion *** assessment confirms the technical viability of the proposed concept of green hydrogen production,transportation and *** the present commercialization is hindered by economics due to a high green hydrogen production cost of USD 26.95 per kg,this green hydrogen pathway is expected to be competitive with grey hydrogen produced via coal gasification and via natural gas steam reforming by 2043 and 2047,respectively.

关键词： floating solar photovoltaics gas blending green hydrogen industrial decarbonization lithium-ion battery photon exchange membrane electrolysis

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Stability Analysis on Iterative PID Control Design Algorithm for Maximizing Proportional Gain

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Transactions of the Korean Institute of electrical Engineers 2025年第2期74卷 332-338页

作者： Joo, Youngjun Department of Electrical Engineering Institute of Advanced Materials and Systems Sookmyung Women‘s University Korea Republic of

This paper deals with an iterative proportional-integral-derivative (PID) gain tuning algorithm to maximize the proportional (P) gain while guaranteeing the stability of the closed-loop system. Indeed, by increasing P-gain, the performance of the closed-loop system, such as the steady-state error, disturbance rejection, and transient response, is improved. However, increasing P-gain alone generally destabilizes the closed-loop system, and thus, the control designer also needs to increase the derivative (D) gain. To improve the control performance and guarantee stability simultaneously, P- and D-gains are sequentially increased in an iterative manner. Furthermore, if necessary, the integral (I) gain is selected to achieve the desired steady-state performance with the pre-designed PD controller. With its strong control performance, the proposed algorithm makes it easy to design PID gains and can be applicable to the fine-tuning of PID gains selected by other PID gain tuning algorithms. In addition, the stability conditions of designing PID gains are presented for linear time-invariant systems. Thus, the stability of the closed-loop system is guaranteed while separately increasing each P-, I-, and D-gain. To validate the effectiveness of the proposed algorithm, simulations for a single-link flexible robot manipulator system have been conducted. © The Korean Institute of electrical Engineers.

关键词： Disturbance rejection

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Energy and Exergy Efficiency Analysis of Advanced Adiabatic Compressed Air Energy Storage Based Trigeneration Energy Hub

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CSEE Journal of Power and Energy systems 2023年第6期9卷 2409-2422页

作者： Danman Wu Wei Wei Jiayu Bai Shengwei Mei the State Key Laboratory of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China

With growing public awareness of decarbonization and increasing penetration of renewable generation,energy storage is in great *** adiabatic compressed air energy storage(AA-CAES)is capable of producing power,heating and cooling,making it an ideal choice of an environmental-friendly energy *** paper proposes an energy and exergy efficiency analysis for an AA-CAES based trigeneration energy *** of power storage and heat load supply rates on energy output efficiency and total exergy losses are *** on the proposed model,optimal configuration of power storage and heat load supply rates can be determined under different *** to basic thermodynamic principles,the proposed method calculates trigeneration capability estimates considering energy grade difference and multi-dimension energy distribution,which can demonstrate more energy conversion properties of the *** studies verify that the proposed method can provide various characteristic analyses for an energy hub and its application in actual systems proves computation *** energy efficiency is improved compared to pursuing maximum electricity-to-electricity efficiency.

关键词： AA-CAES energy and exergy efficiency trigeneration

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Exploiting Flexibility of Integrated Demand Response to Alleviate Power Flow Violation During Line Tripping Contingency

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Journal of Modern Power systems and Clean Energy 2023年第6期11卷 1971-1981页

作者： Tong Cheng Zhenfei Tan Haiwang Zhong IEEE State Key Laboratory of Power Systems the Department of Electrical EngineeringTsinghua UniversityBeijingChina

Multi-energy integrations provide great opportunities for economic and efficient resource utilization. In the meantime, power system operation requires enough flexible resources to deal with contingencies such as transmission line tripping. Besides economic benefits, this paper focuses on the security benefits that can be provided by multi-energy integrations. This paper first proposes an operation scheme to coordinate multiple energy production and local system consumption considering transmission networks. The integrated flexibility model, constructed by the feasible region of integrated demand response(IDR), is then formulated to aggregate and describe local flexibility. Combined with system security constraints, a multi-energy system operation model is formulated to schedule multiple energy production, transmission, and consumption. The effects of local system flexibility on alleviating power flow violations during N-1 line tripping contingencies are then analyzed through a multi-energy system case. The results show that local system flexibility can not only reduce the system operation costs, but also reduce the probability of power flow congestion or violations by approximately 68.8% during N-1 line tripping contingencies.

关键词： Multi-energy system integrated flexibility feasible region integrated demand response N-1 security

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Evaluation of Morphological and Optical Properties of Ag, Au, and Ag@Au Nanoparticles Synthesized via Laser Ablation

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Lasers in Manufacturing and Materials Processing 2024年第4期11卷 931-945页

作者： Abass, Noor al-huda A. Jawad, Muslim F. Haider, Adawiya J. Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Baghdad Iraq Applied Sciences Department/ Laser Branch University of Technology Baghdad Iraq

This work concentrates on Ag, Au, Au@ Ag, and Ag@ Au nanoparticles in various configurations produced through pulsed laser ablation at a wavelength of 532 nm, examining various configurations generated at different laser fluences. The characterization of the materials employs several testing methods, including photoluminescence (PL), dynamic light scattering (DLS), transmission electron microscopy (TEM), Energy-dispersive X-ray spectroscopy (EDX) and ultraviolet-visible spectroscopy (UV-Vis). The characterization results indicate that the Au@Ag and Ag@Au nanoparticles exhibit transmission absorption peaks at 500 nm and 400 nm, respectively. Meanwhile, UV-Vis spectroscopy shows peak absorption at 490 nm for Au and 400 nm for Ag. Additionally, TEM reveals average diameters of Ag, Au, Ag@ Au, and Au@ Ag core-shell nanoparticles is based on their average diameters of 14.58 nm, 18.34 nm, and Core-shell (97.31–96.35) nm, respectively. While the particle sizes of the Au NPs, Ag NPs, Ag@ Au, and Au@ Ag measured using DLS were 82 nm, 57.3 nm, 204.6 nm, and 156.8 nm respectively. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Energy dispersive spectroscopy

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An adaptive fractional controller design for automatic voltage regulator system: sigmoid-based fractional-order PID controller

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Neural Computing and Applications 2024年第23期36卷 14409-14431页

作者： Sahin, Ali Kivanc Cavdar, Bora Ayas, Mustafa Sinasi Department of Electrical and Electronics Engineering Erzurum Technical University Erzurum25050 Turkey Department of Energy Systems Engineering Karadeniz Technical University Trabzon61080 Turkey Department of Electrical and Electronics Engineering Karadeniz Technical University Trabzon61080 Turkey

The primary objective of a power system is to provide safe and reliable electrical energy to consumers. This objective is achieved by maintaining the stability of the power system, a multifaceted concept that can be divided into three distinct classes. The focus of this study is on one of these classes, voltage stability. A critical component in maintaining voltage stability is the automatic voltage regulator (AVR) system of synchronous generators. In this paper, a novel control method, the sigmoid-based fractional-order PID (SFOPID), is introduced with the aim of improving the dynamic response and the robustness of the AVR system. The dandelion optimizer (DO), a successful optimization algorithm, is used to optimize the parameters of the proposed SFOPID control strategy. The optimization process for the DO-SFOPID control strategy includes a variety of objective functions, including error-based metrics such as integral of absolute error, integral of squared error, integral of time absolute error, and integral of time squared error, in addition to the user-defined Zwee Lee Gaing’s metric. The effectiveness of the DO-SFOPID control technique on the AVR system has been rigorously investigated through a series of tests and analyses, including aspects such as time domain, robustness, frequency domain, and evaluation of nonlinearity effects. The simulation results are compared between the proposed DO-SFOPID control technique and the fractional-order PID (FOPID) and sigmoid-based PID (SPID) control techniques, both of which have been tuned using different metaheuristic algorithms that have gained significant recognition in recent years. As a result of these comparative analyses, the superiority of the DO-SFOPID control technique is confirmed as it shows an improved performance with respect to the other control techniques. Furthermore, the performance of the proposed DO-SFOPID control technique is validated within an experimental setup for the AVR system. The simulation res

关键词： Three term control systems

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Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment

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Computer Modeling in engineering & Sciences 2024年第2期138卷 1341-1364页

作者： Mohamed Zarouan Ibrahim M.Mehedi Shaikh Abdul Latif Md.Masud Rana Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Electronic Engineering Rajshahi University of Engineering and TechnologyRajshahiBangladesh

Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamlessoperation of the system. Current industrial processes are getting smarter with the emergence of Industry ***, various modernized industrial processes have been equipped with quite a few sensors to collectprocess-based data to find faults arising or prevailing in processes along with monitoring the status of *** diagnosis of rotating machines serves a main role in the engineering field and industrial production. Dueto the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experienceand human knowledge, intellectual fault diagnosis based on deep learning (DL) has attracted the researcher’sinterest. DL reaches the desired fault classification and automatic feature learning. Therefore, this article designs a Gradient Optimizer Algorithm with Hybrid Deep Learning-based Failure Detection and Classification (GOAHDLFDC)in the industrial environment. The presented GOAHDL-FDC technique initially applies continuous wavelettransform (CWT) for preprocessing the actual vibrational signals of the rotating machinery. Next, the residualnetwork (ResNet18) model was exploited for the extraction of features from the vibration signals which are thenfed into theHDLmodel for automated fault detection. Finally, theGOA-based hyperparameter tuning is performedtoadjust the parameter valuesof theHDLmodel *** experimental result analysis of the GOAHDL-FD Calgorithm takes place using a series of simulations and the experimentation outcomes highlight the better resultsof the GOAHDL-FDC technique under different aspects.

关键词： Fault detection Industry 4.0 gradient optimizer algorithm deep learning rotating machineries artificial intelligence

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Oversampling-Enhanced Feature Fusion-Based Hybrid ViT-1DCNN Model for Ransomware Cyber Attack Detection

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Computer Modeling in engineering & Sciences 2025年第2期142卷 1667-1695页

作者： Muhammad Armghan Latif Zohaib Mushtaq Saifur Rahman Saad Arif Salim Nasar Faraj Mursal Muhammad Irfan Haris Aziz Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl Ahsa31982Saudi Arabia Department of Mechanical Industrial and Energy System EngineeringUniversity of SargodhaSargodha40100Pakistan

Ransomware attacks pose a significant threat to critical infrastructures,demanding robust detection *** study introduces a hybrid model that combines vision transformer(ViT)and one-dimensional convolutional neural network(1DCNN)architectures to enhance ransomware detection *** common challenges in ransomware detection,particularly dataset class imbalance,the synthetic minority oversampling technique(SMOTE)is employed to generate synthetic samples for minority class,thereby improving detection *** integration of ViT and 1DCNN through feature fusion enables the model to capture both global contextual and local sequential features,resulting in comprehensive ransomware *** on the UNSW-NB15 dataset,the proposed ViT-1DCNN model achieved 98%detection accuracy with precision,recall,and F1-score metrics surpassing conventional *** approach not only reduces false positives and negatives but also offers scalability and robustness for real-world cybersecurity *** results demonstrate the model’s potential as an effective tool for proactive ransomware detection,especially in environments where evolving threats require adaptable and high-accuracy solutions.

关键词： Ransomware attacks cybersecurity vision transformer convolutional neural network feature fusion encryption threat detection

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Examining the Quality Metrics of a Communication Network with Distributed Software-Defined Networking Architecture

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Computer Modeling in engineering & Sciences 2024年第11期141卷 1673-1708页

作者： Khawaja Tahir Mehmood Shahid Atiq Intisar Ali Sajjad Muhammad Majid Hussain Malik M.Abdul Basit Department of Electrical Engineering Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan Department of Telecommunication Systems Bahauddin Zakariya UniversityMultan60000Pakistan Department of Electrical Engineering University of Engineering and TechnologyTaxila47050Pakistan School of Engineering and Physical Sciences Heriot-Watt UniversityEdinburghEH144ASUK

Software-Defined Networking(SDN),with segregated data and control planes,provides faster data routing,stability,and enhanced quality metrics,such as throughput(Th),maximum available bandwidth(Bd(max)),data transfer(DTransfer),and reduction in end-to-end delay(D(E-E)).This paper explores the critical work of deploying SDN in large-scale Data Center Networks(DCNs)to enhance its Quality of Service(QoS)parameters,using logically distributed control *** is a noticeable increase in Delay(E-E)when adopting SDN with a unified(single)control structure in big DCNs to handle Hypertext Transfer Protocol(HTTP)requests causing a reduction in network quality parameters(Bd(max),Th,DTransfer,D(E-E),etc.).This article examines the network performance in terms of quality matrices(bandwidth,throughput,data transfer,etc.),by establishing a large-scale SDN-based virtual network in the Mininet *** SDN network is simulated in three stages:(1)An SDN network with unitary controller-POX to manage the data traffic flow of the network without the server load management algorithm.(2)An SDN network with only one controller to manage the data traffic flow of the network with a server load management algorithm.(3)Deployment of SDN in proposed control arrangement(logically distributed controlled framework)with multiple controllers managing data traffic flow under the proposed Intelligent Sensing Server Load Management(ISSLM)*** a result of this approach,the network quality parameters in large-scale networks are enhanced.

关键词： Software defined networking quality of service hypertext transfer protocol data transfer rate latency maximum available bandwidth server load management

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