检索结果-内蒙古大学图书馆

A Methodology for Estimating Allocation of Electric Vehicle Grid Interfaces in a Distribution System

学校读者我要写书评

暂无评论

A Methodology for Estimating Allocation of Electric Vehicle ...

IEEE Power engineering Society Conference and Exposition in Africa, PowerAfrica

作者： Imanthi Kalanika Subasinghe Ganesh K. Venayagamoorthy Holcombe Department of Electrical and Computer Engineering Clemson University Real-Time Power and Intelligent Systems Laboratory Clemson USA Department of Electrical Electronic and Computer Engineering University of Pretoria South Africa

ISBN: (数字)9798350389388

ISBN: (纸本)9798350389395

The integration of electric vehicles (EVs) into the smart grid has introduced new challenges and opportunities for optimizing power and energy management. This paper presents a simple method using a decision-tree to estimate allocation of electric vehicle grid interfaces (EVGIs) for EV charging/discharging, leveraging the nodal capabilities of a distribution system. The future distribution system will cater for vehicle-to-grid (V2G) transactions in addition to grid-to-vehicle (G2V) transactions, thus EVGIs allowing for bidirectional (G2V/V2G) power flows need to be deployed. The proposed decision-tree method is based on nodal power flow ratings and peak demand at the nodes assuming the nodal voltages are maintained within their stability envelopes by volt-var optimization and other voltage control methods. The allocation of EVGIs in the IEEE 34 test node feeder distribution system using the decision-tree method is illustrated. The EVGI allocation using decision-trees is a simple method that can provide insights of a typical distribution system's capability to support EV integration with emerging smart grid technologies.

关键词： Vehicle-to-grid Electric potential Estimation Power system stability Resource management Voltage control Forecasting Energy management Optimization Load flow

Introduction of hydrogen technologies to mitigate the impact of thermal consumption in a university campus 3

学校读者我要写书评

暂无评论

Introduction of hydrogen technologies to mitigate the impact...

3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Bracho, Jorge Charalambous, Chrysanthos Efthimiou, Venizelos Lagos, Dimitrios Samotyjak, Tomasz Askeland, Magnus Georghiou, George E. University of Cyprus PV Technology Laboratory Department of Electrical and Computer Engineering Nicosia Cyprus Efficient and Sustainable Energy Solutions PHAETHON Centre of Excellence for Intelligent Nicosia Cyprus Energy Systems Analytics Group Barcelona Spain Instytut Energetyki Gdansk Poland SINTEF Energy Research Energy Systems Trondheim Norway

ISBN: (纸本)9798350375923

It is imperative for energy systems to reduce their environmental footprint in a cost-efficient manner, for which renwable energy sources (RES) and complementary technologies become desirable options to achieve said task. This is particularly the case for systems with different energy sources, as they'd be able to either address one specific type of energy demand and/or allow for the coupling of different energy carriers that would allow for technologies that normally don't interact to start complementing each other. Therefore, this paper proposes various scenarios for the UCY campus in which hydrogen technologies would allow for the electrification of thermal demand while harnessing the surplus production coming from a solar park, which is modelled through the Integrate optimization tool and validated through DidSILENT PowerFactory. The results showcased a rise of up to 58% in self-sufficiency while the annual energy costs and CO2 emissions were reduced by 45% and 48% respectively. © 2024 IEEE.

关键词： Clean energy

Volumetric B1+ field homogenization in 7 Tesla brain MRI using metasurface scattering

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Yoon, Gyoungsub Yu, Sunkyu Lee, Jongho Park, Namkyoo Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Intelligent Wave Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Laboratory for Imaging Science and Technology Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of

Ultrahigh field magnetic resonance imaging (UHF MRI) has become an indispensable tool for human brain imaging, offering excellent diagnostic accuracy while avoiding the risks associated with invasive modalities. When the radiofrequency magnetic field of the UHF MRI encounters the multifaceted complexity of the brain—characterized by wavelength-scale, dissipative, and random heterogeneous materials—detrimental mesoscopic challenges such as B1+ field inhomogeneity and local heating arise. Here we develop the metasurface design inspired by scattering theory to achieve the volumetric field homogeneity in the UHF MRI. The method focuses on finding the scattering ansatz systematically and incorporates a pruning technique to achieve the minimum number of participating modes, which guarantees stable practical implementation. Using full-wave analysis of realistic human brain models under a 7 Tesla MRI, we demonstrate more than a twofold improvement in field homogeneity and suppressed local heating, achieving better performance than even the commercial 3 Tesla MRI. The result shows a noninvasive generalization of constant intensity waves in optics, offering a universal methodology applicable to higher Tesla MRI. © 2024, CC BY.

关键词： Magnetic resonance imaging

Programmable photonic unitary circuits for light computing

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Kim, Kyuho Park, Kunwoo Park, Hyungchul Yu, Sunkyu Park, Namkyoo Piao, Xianji Intelligent Wave Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Wave Engineering Laboratory School of Electrical and Computer Engineering University of Seoul Seoul02504 Korea Republic of

Unitarity serves as a fundamental concept for characterizing linear and conservative wave phenomena in both classical and quantum systems. Developing platforms that perform unitary operations on light waves in a universal and programmable manner enables the emulation of complex light-matter interactions and the execution of general-purpose functionalities for wave manipulations, photonic computing, and quantum circuits. Recently, numerous approaches to implementing programmable photonic unitary circuits have been proposed and demonstrated, each employing different design strategies that distinctly impact overall device performance. Here, we review foundational design principles and recent achievements in the implementation of programmable photonic unitary circuits, with a particular focus on integrated photonic platforms. We classify the design strategies based on the dimensionality of nontrivial unit operations in their building blocks: lower-dimensional unitary units, such as SU(2) operations, and higher-dimensional ones, such as Fourier transforms. In each category, recent efforts to leverage alternative physical axes, such as the temporal and frequency domains, to address scalability challenges are also reviewed. We discuss the underlying concepts, design procedures, and trade-offs of each design strategy, especially in relation to light-based computing. © 2024, CC BY.

关键词： Photonic integrated circuits

Computing Riemann zeros with light scattering

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Yu, Sunkyu Piao, Xianji Park, Namkyoo Intelligent Wave Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Wave Engineering Laboratory School of Electrical and Computer Engineering University of Seoul Seoul02504 Korea Republic of Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of

Finding hidden order within disorder is a common interest in material science1,2, wave physics3,4, and mathematics5. The Riemann hypothesis, stating the locations of nontrivial zeros of the Riemann zeta function6, tentatively characterizes statistical order in the seemingly random distribution of prime numbers. This famous conjecture has inspired various connections with different branches of physics7, recently with non-Hermitian physics8,9, quantum field theory10, trapped-ion qubits11, and hyperuniformity12,13. Here we develop the computing platform for the Riemann zeta function by employing classical scattering of light. We show that the Riemann hypothesis suggests the landscape of semi-infinite optical scatterers for the perfect reflectionless condition under the Born approximation. To examine the validity of the scattering-based computation, we investigate the asymptotic behaviours of suppressed reflections with the increasing number of scatterers and the emergence of multiple scattering. The result provides another bridge between classical physics and the Riemann zeros, exhibiting the design of wave devices inspired by number theory. © 2024, CC BY.

关键词： Born approximation

Not so griddy: Internal representations of RNNs path integrating more than one agent 38

学校读者我要写书评

暂无评论

Not so griddy: Internal representations of RNNs path integra...

38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Redman, William T. Acosta, Francisco Acosta-Mendoza, Santiago Miolane, Nina Intelligent Systems Center Johns Hopkins Applied Physics Laboratory United States Department of Physics University of California Santa Barbara United States Dynamical Neuroscience University of California Santa Barbara United States Department of Electrical & Computer Engineering University of California Santa Barbara United States

Success in collaborative and competitive environments, where agents must work with or against each other, requires individuals to encode the position and trajectory of themselves and others. Decades of neurophysiological experiments have shed light on how brain regions [e.g., medial entorhinal cortex (MEC), hippocampus] encode the self's position and trajectory. However, it has only recently been discovered that MEC and hippocampus are modulated by the positions and trajectories of others. To understand how encoding spatial information of multiple agents shapes neural representations, we train a recurrent neural network (RNN) model that captures properties of MEC to path integrate trajectories of two agents simultaneously navigating the same environment. We find significant differences between these RNNs and those trained to path integrate only a single agent. At the individual unit level, RNNs trained to path integrate more than one agent develop weaker grid responses, stronger border responses, and tuning for the relative position of the two agents. At the population level, they develop more distributed and robust representations, with changes in network dynamics and manifold topology. Our results provide testable predictions and open new directions with which to study the neural computations supporting spatial navigation. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

Sequential Transfer with Multi-Objective Genetic Algorithm for Feature Selection of Small, High-Dimensional Datasets

学校读者我要写书评

暂无评论

Sequential Transfer with Multi-Objective Genetic Algorithm f...

Congress on Evolutionary Computation

作者： Parth C. Upadhyay G. N. DeSouza John A. Lory Department of Electrical Engineering and Computer Science (EECS) Vision-Guided and Intelligent Robotics (ViGIR) Laboratory Division of Plant Sciences University of Missouri Columbia MO

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Performing feature selection on a small number of instances with high-dimensional datasets poses a needed challenge in preventing over-fitting. To address this issue, this paper proposes a sequential transfer-learning approach combined with a multi-objective genetic algorithm (STMO-GA) for feature selection. Firstly, for the multi-objective component of our method, we employ a Non-dominated Sorting Genetic Algorithm (NSGA-II) to generate a Pareto front. Then, features are ranked based on their number of appearances in the same Pareto front. Next, during the sequential knowledge transfer process, the ranked features are iteratively selected until a predetermined $n$ number of features remains. This feature subspace is further refined by a k-fold cross-validation operation, starting from the rank-one feature, to determine the cut-off of the $n$ features that will remain. Comparative evaluations against both GA-based as well as traditional feature selection methods demonstrate that the proposed method achieves superior classification accuracy, while retaining the smallest number or a comparable number of features.

关键词： Accuracy Evolutionary computation Feature extraction Genetics Linear programming Robustness Optimization

Power Dispatch Estimation from Electric Vehicles in a Distribution System

学校读者我要写书评

暂无评论

Power Dispatch Estimation from Electric Vehicles in a Distri...

International Conference on Electric Power and Energy Conversion systems (EPECS)

作者： Ganesh K. Venayagamoorthy Imanthi Kalanika Subasinghe Raj Naidoo Holcombe Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory Clemson University Clemson SC USA Department of Electrical Electronic and Computer Engineering University of Pretoria South Africa

ISBN: (数字)9798331516963

ISBN: (纸本)9798331516970

The integration of electric vehicles (EVs) into the electric power distribution system poses numerous challenges and opportunities for optimizing energy management and system operations. Electric vehicle grid interfaces (EVGIs), essentially bidirectional power converters, allow for charging/grid-to-vehicle (G2V) and discharging/vehicle-to-grid (V2G) power transfers. A power dispatch estimation (PDE) model for V2G, based on availability of EVs in a distribution system and capabilities of the distribution system, is needed to assist in grid operations. This paper presents the development of a PDE model based on nodal power flows to capture the complex spatiotemporal dependencies inherent in G2V and V2G patterns. The hierarchical structure of a distribution system, feeder to EVGI node, is taken into consideration for PDE. Typical PDE estimation results are presented for the IEEE 34 test node feeder distribution system allocated with EVGIs.

关键词： Partial discharges Vehicle-to-grid systems operation Estimation Spatiotemporal phenomena Resource management Energy management Voltage control Vehicle dynamics Sustainable development

Hyperbolic Delaunay Geometric Alignment

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Medbouhi, Aniss Aiman Marchetti, Giovanni Luca Polianskii, Vladislav Kravberg, Alexander Poklukar, Petra Varava, Anastasia Kragic, Danica Division of Robotics Perception and Learning Department of Intelligent Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden

Hyperbolic machine learning is an emerging field aimed at representing data with a hierarchical structure. However, there is a lack of tools for evaluation and analysis of the resulting hyperbolic data representations. To this end, we propose Hyperbolic Delaunay Geometric Alignment (HyperDGA) – a similarity score for comparing datasets in a hyperbolic space. The core idea is counting the edges of the hyperbolic Delaunay graph connecting datapoints across the given sets. We provide an empirical investigation on synthetic and real-life biological data and demonstrate that HyperDGA outperforms the hyperbolic version of classical distances between sets. Furthermore, we showcase the potential of HyperDGA for evaluating latent representations inferred by a Hyperbolic Variational Auto-Encoder. © 2024, CC BY.

关键词： Geometry