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Optimal SOC Headroom of Pump Storage Hydropower for Maximizing Joint Revenue from Day-ahead and Real-time Markets Under Regional Transmission Organization Dispatch

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 238-250页

作者： Yikui Liu Bing Huang Yang Lin Yonghong Chen Lei Wu Electrical and Computer Engineering Department Stevens Institute of TechnologyHobokenNJ 07030USA Midcontinent Independent System Operator Inc.CarmelIN 46032USA

In response to the increasing penetration of volatile and uncertain renewable energy,the regional transmission organizations(RTOs)have been recently focusing on enhancing the models of pump storage hydropower(PSH)plants,which are one of the key flexibility assets in the day-ahead(DA)and real-time(RT)markets,to further boost their flexibility provision *** by the recent research works that explored the potential benefits of excluding PSHs’cost-related terms from the objective functions of the DA market clearing model,this paper completes a rolling RT market scheme that is compatible with the DA ***,with the vision that PSHs could be permitted to submit state-of-charge(SOC)headrooms in the DA market and to release them in the RT market,this paper uncovers that PSHs could increase the total revenues from the two markets by optimizing their SOC headrooms,assisted by the proposed tri-level optimal SOC headroom ***,in the proposed tri-level model,the middle and lower levels respectively mimic the DA and RT scheduling processes of PSHs,and the upper level determines the optimal headrooms to be submitted to the RTO for maximizing the total revenue from the two *** case studies quantify the profitability of the optimal SOC headroom submissions as well as the associated financial risks.

关键词： Pump storage hydropower energy market state-of-charge(SOC) headroom market revenue tri-level problem

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Exploring the trade-off between deep-learning and explainable models for brain-machine interfaces 38

Exploring the trade-off between deep-learning and explainabl...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Cubillos, Luis H. Revach, Guy Mender, Matthew J. Costello, Joseph T. Temmar, Hisham Hite, Aren Zutshi, Diksha Wallace, Dylan M. Ni, Xiaoyong Kelberman, Madison M. Willsey, Matthew S. van Sloun, Ruud J.G. Shlezinger, Nir Patil, Parag Draelos, Anne Chestek, Cynthia A. Departments of Electrical & Computer Engineering Biomedical Engineering Robotics Computational Medicine & Bioinformatics and Neurosurgery University of Michigan United States Biointerfaces Institute Neuroscience Institute University of Michigan United States Department of Information Technology and Electrical Engineering ETH Zürich Switzerland Department of Electrical Engineering Eindhoven University of Technology Netherlands School of Electrical and Computer Engineering Ben-Gurion University Israel

People with brain or spinal cord-related paralysis often need to rely on others for basic tasks, limiting their independence. A potential solution is brain-machine interfaces (BMIs), which could allow them to voluntarily control external devices (e.g., robotic arm) by decoding brain activity to movement commands. In the past decade, deep-learning decoders have achieved state-of-the-art results in most BMI applications, ranging from speech production to finger control. However, the'black-box' nature of deep-learning decoders could lead to unexpected behaviors, resulting in major safety concerns in real-world physical control scenarios. In these applications, explainable but lower-performing decoders, such as the Kalman filter (KF), remain the norm. In this study, we designed a BMI decoder based on KalmanNet, an extension of the KF that augments its operation with recurrent neural networks to compute the Kalman gain. This results in a varying "trust" that shifts between inputs and dynamics. We used this algorithm to predict finger movements from the brain activity of two monkeys. We compared KalmanNet results offline (pre-recorded data, n = 13 days) and online (real-time predictions, n = 5 days) with a simple KF and two recent deep-learning algorithms: tcFNN (non-ReFIT version) and LSTM. KalmanNet achieved comparable or better results than other deep learning models in offline and online modes, relying on the dynamical model for stopping while depending more on neural inputs for initiating movements. We further validated this mechanism by implementing a heteroscedastic KF that used the same strategy, and it also approached state-of-the-art performance while remaining in the explainable domain of standard KFs. However, we also see two downsides to KalmanNet. KalmanNet shares the limited generalization ability of existing deep-learning decoders, and its usage of the KF as an inductive bias limits its performance in the presence of unseen noise distributions. Despite thi

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Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in electrical Networks

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computer Modeling in engineering & Sciences 2024年第8期140卷 1339-1370页

作者： Ali S.Alghamdi Mohamed A.Zohdy Saad Aldoihi Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical and Computer Engineering Department Oakland UniversityRochesterMI48309USA Institute of Earth and Space Science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer Science and Systems Engineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic *** primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization

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Reply to comment on “Ferroelectric composite-based piezoelectric energy harvester for self-powered detection of obstructive sleep” by A. Tkach and O. Okhay

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Journal of Materiomics 2024年第5期10卷 1160-1164页

作者： Swati Panda Hyoju Shin Sugato Hajra Yumi Oh Wonjeong Oh Jeonghyeon Lee P.M.Rajaitha Basanta Kumar Panigrahi Jyoti Shukla Alok Kumar Sahu Perumal Alagarsamy Hoe Joon Kim Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu 42988South Korea Department of Electrical Engineering Siksha‘O’Anusandhan UniversityBhubaneswar 751030India Department of Electrical Engineering Poornima College of EngineeringJaipur 303903India Department of Physics Indian Institute of Technology-GuwahatiAssam 781039India Robotics and Mechatronics Research Center Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu 42988South Korea

In this contribution,we reply to comments made by Tkach et *** our publication *** 2023;9:*** main interest of our work is to synthesize a lead-free material,SrTi_(2)O_(5)(STO),and then utilize it in the formation of composites and finally design the piezoelectric nanogenerator(PENG)for self-powered sensor *** authors have observed the presence of piezoelectric voltage and current output from the *** authors humbly indicate that the PENG devices were poled using a DC poling setup as conditions mentioned in *** 2023;9:609(Panda et al.,2023)[1].The doping of STO into the PDMS increased from 2% to 20%(in mass).In this process,the piezoelectric output of the PENG device was observed to be highest for 15%(in mass)STO-PDMS ***,we agree with the comment raised by Tkach et al.,and further we have addressed the issues in a step-by-step response as follows.

关键词： Ferroelectric Lead-free Piezoelectric Polycrystalline

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RFFI Protocols Using Antenna Mutual Coupling and Power Amplifier Nonlinear Memory Effects

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IEEE Communications Letters 2025年第6期29卷 1250-1254页

作者： Li, Yuepei Podilchak, Symon K. Zhang, Junqing Cotton, Simon L. Ratnarajah, Tharmalingam Ding, Yuan University of Edinburgh Institute of Digital Communications School of Engineering United Kingdom University of Liverpool Department of Electrical Engineering and Electronic United Kingdom Queen's University Department of Electrical Engineering and Computer Science Belfast United Kingdom San Diego State University College of Engineering Electrical and Computer Engineering San Diego United States United Kingdom

This paper presents a radio frequency fingerprinting identification (RFFI) protocol in wireless links with multi-antenna array transmitters. Multi-antenna systems are widely used in wireless communication systems for diversity and/or multiplexing. The mutual coupling (MC) effects arising from electromagnetic interactions between adjacent array elements can influence the RF characteristics of the transmitter and eventually the performance of the established links. In this paper, a novel RFF strategy is proposed to expand the differences in the RFF characteristics among wireless devices from the same vendor, with the goal of massively improving RFF classification accuracy in low to medium signal-to-noise ratio (SNR) channel conditions. Experimental results show that when classifying six power amplifiers (PAs) from the same vendor, 21% to 62% average classification accuracy improvement can be achieved by enlarging the RFF feature differences arising from the PA nonlinearity arising from the array coupling. © 1997-2012 IEEE.

关键词： Power amplifiers

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Ferroelectric composite-based piezoelectric energy harvester for selfpowered detection of obstructive sleep

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Journal of Materiomics 2023年第4期9卷 609-617页

作者： Swati Panda Hyoju Shin Sugato Hajra Yumi Oh Wonjeong Oh Jeonghyeon Lee P.M.Rajaitha Basanta Kumar Panigrahi Jyoti Shukla Alok Kumar Sahu Perumal Alagarsamy Hoe Joon Kim Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu42988South Korea Department of Electrical Engineering Siksha‘O’Anusandhan UniversityBhubaneswar751030India Department of Electrical Engineering Poornima College of EngineeringJaipur303903India Department of Physics Indian Institute of Technology-GuwahatiAssam781039India Robotics and Mechatronics Research Center Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu42988South Korea

Lead-free piezoelectric ceramic is a promising material for energy harvesters,as they have superior electromechanical,ferroelectric,and piezoelectric *** addition,piezoelectric ceramics can be blended with polymer to achieve high-flexibility polymer-ceramic composites,providing mechanical robustness and *** this context,a new lead-free ferroelectric material,having the chemical formula SrTi_(2)O_(5)(STO),was synthesized using a high-temperature solid-state *** analyses of the structural,morphological,and electrical properties of the synthesized material were *** crystallizes with orthorhombic symmetry and space group of *** frequency and temperature-dependent dielectric parameters were evaluated,and impedance spectroscopy shed light on the charge *** PDMS-STO composites at different mass fraction of the STO were prepared using a solvent casting route,and a corresponding piezoelectric nanogenerator(PENG)was *** electrical output of the different PENG by varying massfractions of STO in PDMS and varying force were *** 15%(in mass)PENG device delivered the highest peak-to-peak voltage,current,and power density of 25 V,92 nA,and 0.64 mW@500 MU,*** biomechanical energy harvesting using the PENG device by daily human motions,bending of the device,and attaching the device to laboratory equipment was *** the PENG device was attached to the human throat region,and snoring signals were recorded.A classification model was designed employing the convolutional neural network(CNN)*** have been laid to differentiate between normal and abnormal snores,which could help the patient with screening and early disease detection,contributing to self-powered healthcare applications.

关键词： Lead-free Ferroelectric Nanogenerator Sleepdisorder

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Hyper-Drive: Visible-Short Wave Infrared Hyperspectral Imaging Datasets for Robots in Unstructured Environments 13

Hyper-Drive: Visible-Short Wave Infrared Hyperspectral Imagi...

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13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2023

作者： Hanson, Nathaniel Pyatski, Benjamin Hibbard, Samuel Dimarzio, Charles Padir, Taskin Institute for Experiential Robotics United States Northeastern University Electrical and Computer Engineering Department BostonMA United States

ISBN: (纸本)9798350395570

Hyperspectral sensors have enjoyed widespread use in the realm of remote sensing;however, they require additional considerations for reliable functionality onboard mobile robots. In this work, we introduce a first-of-its-kind system architecture with snapshot hyperspectral cameras and point spectrometers to efficiently generate composite datacubes from a moving robot base. Our system collects and registers datacubes spanning the visible to shortwave infrared (660-1700 nm) spectrum while simultaneously capturing the ambient solar spectrum reflected off a white reference tile. We collect and disseminate a large dataset of more than 500 labeled datacubes from on-road and off-road terrain compliant with the ATLAS ontology to further the integration hyperspectral imaging (HSI). Our analysis of these data demonstrates that HSI is beneficial in terrain class separability and is a significant opportunity to increase understanding of scene composition from a robot-centric context. All code and data are open source online: https://***/hyper_drive_data © 2023 IEEE.

关键词： Hyperspectral imaging

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Joint Frame Drop and Object Detection Task Offloading for Mobile Devices via RL With Lyapunov Optimization

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IEEE Transactions on Mobile Computing 2025年第7期24卷 6168-6182页

作者： Sohn, Vaughn Kim, Suhwan Lee, Hyang-Won Korea Advanced Institute of Science and Technology Department of Electrical Engineering Daejeon34141 Korea Republic of Konkuk University Department of Computer Science and Engineering Seoul05029 Korea Republic of

Object detection has become an increasingly important application for mobile devices. However, state-of-the-art object detection relies heavily on deep neural network, which is often burdensome to compute on mobile devices. To this end, we develop a layering framework for joint video frame drop and object detection task offloading. In the lower layer, by invoking Lyapunov optimization, we devise an algorithm for partitioning and offloading the computation tasks of deep neural networks. This algorithm also specifies the flow control for admitting the application traffic into the network. In the upper layer, we use the flow control as a form of guidance in the action space in order to develop a reinforcement learning (RL) algorithm that selectively drops video frames with object detection performance in consideration. By the nature of design, this Lyapunov-guided RL guarantees the network stability. We show through simulations that our Lyapunov-guided RL drops video frames with reasonable object detection performance and reduced latency while keeping the network stable. We also implemented our algorithm on the remote-controlled (RC) car equipped with microprocessor and GPU, and demonstrate the applicability of our algorithm to real-time object detection tasks from the video stream generated as the RC car moves. © 2002-2012 IEEE.

关键词： Reinforcement learning

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A New Approach to Determine Feasible Operating Region of Unbalanced Distribution Networks With Distributed Photovoltaics

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IEEE Transactions on Power Delivery 2025年第3期40卷 1493-1504页

作者： Prasad, Manorath Rather, Zakir Hussain Razzaghi, Reza Doolla, Suryanarayana Indian Institute of Technology Bombay Department of Energy Science and Engineering Mumbai400076 India Monash University Department of Electrical and Computer Systems Engineering MelbourneVIC3800 Australia

Amidst rising distributed generation and its potential role in grid management, this article presents a new realistic approach to determine the operational space and flexibility potential of an unbalanced active distribution network. The feasible operating region of an active distribution network is constituted by its range of active-reactive power exchanges with the bulk power system without breaching network constraints. This study explores the potential of highly penetrated single- and three-phase distributed photovoltaics and voltage-sensitive loads to determine the feasible operating region at different operating points. The cumulative response of Volt-Var controlled distributed photovoltaics and voltage-sensitive loads determines the power flow at the bulk power system-active distribution network interconnection, ensuring feasibility with respect to voltage magnitude and unbalance constraints. Further, the correspondence of feasible operating region with the tap-settings of substation transformer enables a novel feature to traverse throughout the available operating region and facilitate bulk power system-active distribution network power coordination. Additionally, a nodal sensitivity-based adjustable Volt-Var control scheme is proposed for distributed photovoltaics, improving the feasible operating region. The proposed strategy is validated on bulk power system-active distribution network integrated test system. Bulk power system: IEEE-9 bus system – Active distribution network: (highly unbalanced IEEE-13 bus distribution system (medium voltage) + modified CIGRE low voltage system). © 1986-2012 IEEE.

关键词： Power distribution networks

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Suppression of over voltage in SiC-based inverter fed induction motor

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Australian Journal of electrical and Electronics engineering 2024年第1期21卷 11-28页

作者： Salau, Ayodeji Olalekan Kanchana, Kadirvel Anoop, Kuttichakku Johny Markus, Elisha Didam Braide, Sepiribo Lucky Department of Electrical/Electronics and Computer Engineering Afe Babalola University Ado-Ekiti Nigeria Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu Chennai India Department of Electrical Electronics Engineering Saveetha Engineering College Chennai India Department of Electrical and Electronics Engineering VISAT Engineering College Kerala Ernakulam India Department of Electrical/Electronic and Computer Engineering Central University of Technology Free State Bloemfontein South Africa Department of Electrical/Electronic Engineering University of Port Harcourt Rivers State Choba Nigeria

Silicon carbide (SiC) based inverters are widely used due to their fast switching and ability to withstand high temperatures and Voltage. This helps to increase efficiency and reduces switching losses compared to the silicon-based inverter. However, this fast-switching device causes an increase in the Voltage at the junction of the cable and motor due to the reflected wave. The main causes of overvoltage are cable/motor impedance mismatch, fast-switching inverter devices (IGBT), and inverter-motor separation. To extend the induction motor lifespan, overvoltage reduction is necessary. Passive and active filters solve the problem, but passive filters are bulky and have high power loss. This paper presents a shunt active filter approach for an inverter-fed induction motor to reduce overvoltage. To show the effectiveness of the proposed approach, the findings were compared to the topology of the clamp-type active filter already in use. The shunt active filter used Proportional Integral (PI) and fuzzy controllers to generate reference current according to the Synchronous Reference Frame (SRF) theory. Harmonics in the power system were removed using the SRF theory. The unique aspect of this work is how the reference current is produced in the shunt active filter using the SRF theory. The proposed shunt active filter with a fuzzy controller was added to the hardware implementation to achieve better results than previous active filters. ©, Engineers Australia.

关键词： Silicon carbide

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