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On the Instability Mechanism of PV-Thermal-Bundled Power system Under Different PV Penetration Ratios

IEEE Transactions on Power Electronics 2025年

作者： Yan, Yiran Ruan, Xinbo He, Yuying Lin, Zhiheng Chen, Yuhang Nanjing University of Aeronautics and Astronautics Center for More Electrical-Aircraft Power System College of Automation Engineering Nanjing211106 China Hohai University College of Electrical and Power Engineering Nanjing211100 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada

In the photovoltaic (PV)-thermal-bundled power system, the increasing PV penetration poses instability risk. Through establishing the small-signal model and solving the eigenvalues of return ratio matrix, the system stability can be evaluated with the generalized Nyquist stability criterion. However, the expressions of eigenvalues are irrational functions, which leads to the complexity of analyzing the system stability and the difficulties to accurately reveal the instability mechanism. To address this issue, the stability analysis method based on the admittance matrix elements is proposed, which does not need to calculate the eigenvalues of return ratio matrix, thus simplifying the stability analysis. In addition, this method can describe the system stability margin clearly. With this stability analysis method, the stability of the PV-thermal-bundled power system is clarified under different renewable penetration ratios, and the causes of the system instability are investigated. Finally, the hardware-in-the-loop results confirm the effectiveness of the proposed stability analysis method and the accuracy of the stability analysis results. © 1986-2012 IEEE.

关键词： Electric power system stability

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Brain inspired iontronic fluidic memristive and memcapacitive device for self-powered electronics

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Microsystems & Nanoengineering 2025年第1期11卷 465-476页

作者： Muhammad Umair Khan Bilal Hassan Anas Alazzam Shimaa Eissa Baker Mohammad Center for Cyber-Physical Systems-System on Chip Lab Khalifa UniversityAbu Dhabi 127788UAE Department of Computer and Information Engineering Khalifa UniversityAbu Dhabi 127788UAE Department of Electrical Engineering Khalifa UniversityAbu Dhabi 127788UAE Division of Engineering New York UniversityAbu Dhabi 129188UAE Department of Mechanical and Nuclear Engineering Khalifa UniversityAbu Dhabi 127788UAE Department of Chemistry Khalifa UniversityAbu Dhabi 127788UAE

Ionic fluidic devices are gaining interest due to their role in enabling self-powered neuromorphic computing *** this study,we present an approach that integrates an iontronic fluidic memristive(IFM)device with low input impedance and a triboelectric nanogenerator(TENG)based on ferrofluid(FF),which has high input *** incorporating contact separation electromagnetic(EMG)signals with low input impedance into our FF TENG device,we enhance the FF TENG’s performance by increasing energy harvesting,thereby enabling the autonomous powering of IFM devices for self-powered ***,replicating neuronal activities using artificial iontronic fluidic systems is key to advancing neuromorphic *** fluidic devices,composed of soft-matter materials,dynamically adjust their conductance by altering the solution *** developed voltage-controlled memristor and memcapacitor memory in polydimethylsiloxane(PDMS)structures,utilising a fluidic interface of FF and polyacrylic acid partial sodium salt(PAA Na^(+)).The confined ion interactions in this system induce hysteresis in ion transport across various frequencies,resulting in significant ion memory *** IFM successfully replicates diverse electric pulse patterns,making it highly suitable for neuromorphic ***,our system demonstrates synapse-like learning functions,storing and retrieving short-term(STM)and long-term memory(LTM).The fluidic memristor exhibits dynamic synapse-like features,making it a promising candidate for the hardware implementation of neural *** TENG/EMG device adaptability and seamless integration with biological systems enable the development of advanced neuromorphic devices using iontronic fluidic materials,further enhanced by intricate chemical designs for self-powered electronics.

关键词： iontronic memristive ionic fluidic devices memcapacitive ff teng s ff teng fluidic triboelectric nanogenerator teng based

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An active power control of DFIG-based wind turbine generators for frequency regulation with expected dynamic performance

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Applied Energy 2025年 391卷

作者： Zhao, Teyang Liu, Hui Wang, Ni Su, Jinshuo Luo, Zhiqiang Ma, Siyu School of Electrical Engineering Guangxi University Nanning530004 China Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi University Nanning530004 China The State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of Macau 519000 China

The escalating wind power penetration presents a substantial challenge in ensuring the system frequency stability. Although wind turbine generators (WTGs) can offer rapid frequency support by the presetting power trajectory response (PPTR), it will result in a secondary frequency dip (SFD) while facing the demand of restoring rotor speed after frequency regulation. Moreover, the frequency overshoot will occur due to the fixed power increment provided by PPTR under minor disturbances. In this paper, an active power control strategy of DFIG-based WTGs is proposed for eliminating frequency overshoot and mitigating SFD while providing power support for the system frequency. A rotor-speed-based power increment and power attenuation trajectory are designed to enhance the primary frequency nadir while ensuring the operation stability of WTGs. After that, SFD will be mitigated by the proposed parabolic-formed compensation power. Moreover, a power increment control mode is proposed to eliminate the frequency overshoot by a membership-function-based global controller, which can smoothly switch the combined inertial response and the improved PPTR to provide a flexible power increment. Finally, the validity of the proposed strategy in improving frequency nadir, eliminating frequency overshoot, and mitigating SFD are verified by simulations under different wind power penetration levels, disturbances, and wind conditions. © 2025

关键词： Frequency stability

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Development and modeling of advanced systems Na2SnBr6-based perovskite solar cells: a comprehensive study on electron transport layers

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Optics Express 2025年第10期33卷 21152-21172页

作者： Dipta Roy Md Selim Reza Avijit Ghosh Anup Kumar Roy Bivash Ranjan Chowdhury Md Aktarujjaman H A Alrafai Abeer A Hassan Department of Electrical and Computer Engineering California State University at Northridge Northridge CA 91330 USA Department of Electrical and Electronic Engineering Begum Rokeya University Rangpur-5400 Bangladesh Phillip M. Drayer Department of Electrical and Computer Engineering Lamar University Beaumont TX 77710 USA Department of Management Information System International American University Los Angeles CA 90010 USA Department of Information Technology Management Webster University St. Louis MO 63119 USA Department of Chemistry Faculty of Science King Khalid University PO Box 9004 Abha 61413 Saudi Arabia

This study simulates a n-i-p planar heterojunction for Na 2 SnBr 6 -based perovskite solar cells (PSCs) , with Na 2 SnBr 6 as the absorber layer, fluorine-doped tin oxide (FTO) as the substrate, and In 2 S 3 , IGZO, and SnS 2 as electron transport layers (ETLs). Gold (Au) is used as the back contact. Na 2 SnBr 6 was chosen for its low cost, non-toxicity, tunable band gap, excellent electrical properties, and stability. The SCAPS-1D simulator was employed to model the solar cell performance under AM 1.5 G light irradiation, focusing on factors like doping concentration, layer thickness, defect density, and interface defects across three device configurations: Device I (Au/Na 2 SnBr 6 / In 2 S 3 /FTO/Al), Device II (Au/ Na 2 SnBr 6 /IGZO/FTO/Al), and Device III (Au/ Na 2 SnBr 6 /SnS 2 /FTO/Al). Device III achieved the highest PCE of 31.35%, FF of 85.95%, V OC of 0.7926 V, and J SC of 46.01 mA/cm 2 2 , making it a promising candidate for high-efficiency, lead-free perovskite solar cells. Devices I and II showed lower efficiencies of 27.47% and 30.98%, respectively. The study also analyzed quantum efficiency (QE), carrier dynamics, and recombination rates, highlighting the potential of Device III in advancing Na 2 SnBr 6 -based hybrid perovskite solar technologies for future solar energy applications.

关键词： Material properties Solar cell efficiency Solar cells Solar energy Thin film solar cells Transparent conducting oxides

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Warped-Compaction: Maximizing GPU Register File Bandwidth Utilization via Operand Compaction

Warped-Compaction: Maximizing GPU Register File Bandwidth Ut...

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IEEE Symposium on High-Performance computer Architecture

作者： Eunbi Jeong Ipoom Jeong Myung Kuk Yoon Nam Sung Kim Department of Computer Science and Engineering Ewha Womans University Seoul Korea Department of System Semiconductor Engineering Yonsei University Seoul Korea Department of Electrical and Electronic Engineering Yonsei University Seoul Korea University of Illinois Urbana-Champaign Urbana U.S.A

ISBN: (数字)9798331506476

ISBN: (纸本)9798331506483

The GPU has been successfully used for diverse emerging compute-intensive applications, including imaging, computer vision, and more recently, deep learning, to name a few. To offer high performance for such applications, it is provisioned with massive Register Files (RFs) to exploit high Thread-Level Parallelism (TLP). As RFs are designed to store thousands of contexts and provide very high bandwidth for uninterrupted supply of operands to hundreds of compute units for high TLP, they have become one of the most power-hungry components in the GPU. Meanwhile, faced with the end of Dennard scaling, it is more important than ever to innovate the microarchitecture of (power-constrained) GPUs to continuously improve the performance of future compute-intensive *** this work, we propose a GPU microarchitecture, WarpedCompaction, designed to utilize given RFs more efficiently, instead of relying on larger-capacity and/or higher-bandwidth RFs to further improve GPU performance. Specifically, first, we reverse-engineer the latest GPU’s RF organization through microbenchmarking. This uncovers that each sub-core within a streaming multiprocessor contains only two dual-ported RF banks, and accesses to these banks are arbitrated solely based on register IDs. We also reveal that, despite the modest configurations, RF banks are largely underutilized, staying inactive for 33.5% of the time. Second, we observe that previously proposed RF optimization techniques, data forwarding and dead register elimination, cannot address this underutilization problem. This is mainly due to the (R1) insufficient RF access requests from a limited number of Operand Collector Units (OCUs) and (R2) inefficient operand distribution by the conventional RF bank arbitration. Third, we present two architectural solutions to tackle the observed inefficiency: (S1) OCU sharing and (S2) skewed arbitrator. Building on enhanced OCU early allocation for partially ready instructions and operand forwardin

关键词： Radio frequency Microarchitecture Graphics processing units Bandwidth Organizations Parallel processing Hardware Energy efficiency Registers Resource management

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Development of LiFx/Al2O3/ITO Multilayer Antireflection Coatings for Reflectance Reduction in Silicon Heterojunction Solar Cells

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Physica Status Solidi (A) Applications and Materials Science 2025年

作者： Aida, Maha Nur Khokhar, Muhammad Quddamah Yousuf, Hasnain Chu, Mengmeng Rahman, Rafi Ur Alamgeer, Khan Bae, Junhan Jang, Seokjin Yi, Junsin Department of Future Energy Engineering Sungkyunkwan University Gyeonggi-Do Suwon16419 Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Gyeonggi-Do Suwon16419 Korea Republic of Interdisciplinary Program in Photovoltaic System Engineering Sungkyunkwan University Gyeonggi-Do Suwon16419 Korea Republic of

This study focuses on the optimization of antireflection coatings (ARCs) to enhance the performance of silicon heterojunction (SHJ) solar cells. SHJ solar cells face a significant challenge in achieving their theoretical efficiency limits due to light reflection at the air–cell interface. This reflection reduces photon absorption, which limits photocurrent generation and hinders the widespread adoption of SHJ technology. To address this, the optimization of ARCs using single, double, and triple-layer designs with a graded refractive index material as the active layer is investigated. The optimization process is simulated by calculating the layer thicknesses using OPAL2 software and validated through experimental deposition. The results demonstrate that a triple-layer ARC structure consisting of 80/50/95 nm of indium tin oxide (ITO), aluminum oxide (Al2O3), and lithium fluoride (LiFx) significantly improves SHJ performance. This configuration leads to a 1.04 mA cm−2 increase in short-circuit current density (Jsc), reaching 39.85 mA cm−2, and an efficiency of 21.62%, compared to a single-layer ARC. This study presents a promising solution to improve SHJ solar cell efficiency by reducing reflection losses and optimizing optical properties, contributing to the advancement of SHJ technology and facilitating the development of more efficient and cost-effective photovoltaic systems for sustainable energy transition. © 2025 Wiley-VCH GmbH.

关键词： Antireflection coatings

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Transfer Learning Trained LSTM Models for Household Load Profile Forecasting

Transfer Learning Trained LSTM Models for Household Load Pro...

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Grid Edge Technologies Conference & Exposition (Grid Edge), IEEE PES

作者： Roshan Klein-Seetharaman Xiangqi Zhu Barry Mather Department of Mathematics Yale University New Haven USA Electrical Engineering and Computer Science Oregon State University Corvallis USA National Renewable Energy Laboratory Power System Engineering Center Golden USA

ISBN: (数字)9798350352528

ISBN: (纸本)9798350352535

Grid edge renewable energy resources, such as rooftop solar photovoltaics, closely interact with consumer load profiles. Therefore, forecasting future electricity demand, ideally at the individual household level, is indispensable. In this paper, we present a transfer learning enhanced household load profile forecasting method. First, we tune a long short-term memory forecasting model to perform day-ahead prediction of household electricity load profiles. Then we improve these individualized models using transfer learning, and we use k-means clustering to create optimal source data sets. We find average improvements of 4.38% (largest improvement of 10.71%) when the entire data set was used to train the source model and 2.45% (largest improvement of 11.57%) in the mean absolute error when households were first clustered and used to train separate source models for each cluster. We find that transfer learning with clustered data can effectively boost the forecasting performance of the LSTM models. We use realistic household power measurements for 148 real residential households in Austin, Texas.

关键词： Photovoltaic systems Renewable energy sources Power measurement Electricity Transfer learning Predictive models Data models Forecasting Long short term memory Load modeling

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Synthesis of Dynamic Virtual-Inertia for Microgrid system Applications

Synthesis of Dynamic Virtual-Inertia for Microgrid System Ap...

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Intelligent Control, Computing and Communications (IC3), International Conference on

作者： Jackson J. Justo Galina Demidova Dmitry Lukichev Nikolai Poliakov Peter Makolo Ramesh C. Bansal Faculty of Control System and Robotics ITMO University Saint-Petersburg Russia Department of Electrical Engineering University of Dar es Salaam Dar es Salaam Tanzania Depatment of Electrical Engineering University of Sharjah Sharjah United Arab Emirates Department of Electric Electronic and Computer Engineering University of Pretoria Pretoria South Africa

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

During the last two decades, interest in grid integrated renewable energy sources (RERs) into the electrical power grids has significantly grown. The motive being a promising strategy to reduce greenhouse gas emissions generated by conventional power plants (CPPs) and hence environmental consequences, decrease losses in distribution lines to improve power system supply efficiency and reliability to consumers. As a result, several CPPs are being replaced by RERs such as solar PV system, wind energy, micro hydro-turbine, fuel cell, and small gas power plants. These are installed close to customers on low-voltage and medium-voltage sites to reduce losses in the network and improve power quality, overall efficiency and reliability. However, grid-connected RERs via inverter decreases system inertia due to decrease in CPPs with rotating mass serving as an immediate natural response to frequency deviations following network disturbances. Therefore, this paper presents the design of dynamic virtual-inertia control (DVIC) scheme. The developed DVIC incorporates the mechanism to adjust active and reactive demand in response to any frequency and voltage variations to ensure system stability. To validate the suitability of the presented technique, MATLAB/Simulink model is developed and simulated under various operating scenarios. Using the results obtained simulation study, it is evidently the proposed DVIC shows improved performance is achieved than when no inertia control system applied.

关键词： Time-frequency analysis Renewable energy sources Power system dynamics Microgrids Power system stability Inverters Power system reliability Reliability Frequency control Power generation

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Decision-Focused Learning for Complex system Identification: HVAC Management system Application

arXiv

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arXiv 2025年

作者： Favaro, Pietro Toubeau, Jean-François Vallée, François Dvorkin, Yury Power Systems and Markets Research Group University of Mons Mons Belgium Ralph O’Connor Sustainable Energy Institute Department of Electrical and Computer Engineering Department of Civil and System Engineering Johns Hopkins University BaltimoreMD United States

As opposed to conventional training methods tailored to minimize a given statistical metric or task-agnostic loss (e.g., mean squared error), Decision-Focused Learning (DFL) trains machine learning models for optimal performance in downstream decision-making tools. We argue that DFL can be leveraged to learn the parameters of system dynamics, expressed as constraint of the convex optimization control policy, while the system control signal is being optimized, thus creating an end-to-end learning framework. This is particularly relevant for systems in which behavior changes once the control policy is applied, hence rendering historical data less applicable. The proposed approach can perform system identification — i.e., determine appropriate parameters for the system analytical model — and control simultaneously to ensure that the model’s accuracy is focused on areas most relevant to control. Furthermore, because black-box systems are non-differentiable, we design a loss function that requires solely to measure the system response. We propose pre-training on historical data and constraint relaxation to stabilize the DFL and deal with potential infeasibilities in learning. We demonstrate the usefulness of the method on a building Heating, Ventilation, and Air Conditioning day-ahead management system for a realistic 15-zone building located in Denver, US. The results show that the conventional RC building model, with the parameters obtained from historical data using supervised learning, underestimates HVAC electrical power consumption. For our case study, the ex-post cost is on average six times higher than the expected one. Meanwhile, the same RC model with parameters obtained via DFL underestimates the ex-post cost only by 3%. © 2025, CC BY-NC-ND.

关键词： Convex optimization

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Transient Stability Analysis and Fault Clearing Angle Estimation of VSG Based on Domain of Attraction Estimated by Trajectory Reversing Method

arXiv

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arXiv 2025年

作者： Lyu, Jiayue Fang, Tianzhi Lin, Zhiheng Han, Jingxue Zhu, Yantao Center for More-Electrical-Aircraft Power System College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada

The virtual synchronous generator (VSG), with the analogous nonlinear power-angle relationship to the synchronous generator (SG), has attracted much attention as a promising solution for converter-based power systems. In this paper, a large signal model of the grid-connected VSG is first established. The trajectory reversing method (TRM) is then introduced to estimate the domain of attraction (DOA) of VSG. Subsequently, the transient instability mechanism is revealed in detail based on the estimated DOA boundary. The impacts of system parameters on the DOA range are further investigated. It is found that loss of synchronization (LOS) occurs if the system trajectory lies outside the post-fault DOA range. In scenarios where no equilibrium points exist after a grid fault, system stability can be reestablished only when the fault clearing angle (FCA) does not exceed the critical clearing angle (CCA). Finally, the CCA derived from the DOA and that from the conventional equal area criteria (EAC) are compared. The results show that CCA obtained by our solution has a higher accuracy. Time-domain simulations are performed to verify the effectiveness of the proposed transient stability analysis method of grid-connected VSG. Copyright © 2025, The Authors. All rights reserved.

关键词： Transient stability

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