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Future Trends in Smart Communities (ICFTSC), International Conference on

作者： Previnsha Naidu Poornachendran Renuga Verayiah Department of Electrical and Electronic Engineering College of Graduate Studies Universiti Tenaga Nasional UNITEN Kajang Malaysia

ISBN: (纸本)9798350334555

Transforming from a vertically integrated environment to a liberalized electricity market is not an easy task, and the rationale behind is the pressure to reduce electricity prices by relying on the enhanced efficiency of power plants and stiff competition in the generation sector. The New Enhanced Dispatch Arrangement (NEDA) is an initiative by EC (Energy Commission) to enhance efficiency in the short run electricity generation competition and drive down electricity prices. NEDA serves as a pre-cursor to the creation of an electricity market in Peninsular Malaysia. This paper analyses the impact of NEDA mechanism on the cost efficiency of a Malaysian Representative System. The PLEXOS simulation is done for two network constraints, which are the Southern and Northern constraint, using four types of load profiles to study the cost impact. To obtain the generation cost for each scenario, the methodology implemented will be Security Constrained Economic Dispatch (SCED). The objective function of SCED is to minimize the total system costs within various technical constraints and limitations. For Southern constraint, the results obtained showed an average of 1.3% cost savings per day, when 1000 MW of NEDA generation is injected into the grid. The annual cost savings is RM 226 million, translating to a 471% savings in generation prices. Expensive generators in the system are now being replaced by the generation from NEDA players which are paid at the System Marginal Price (SMP). On the other hand, for Northern constraint, the annual cost savings is approximately RM 191 million, which is equivalent to 366% cost savings. This will benefit the electricity industry by reducing generation cost, and consumers will be able to enjoy lower and cheaper electricity tariff.

关键词： Costs Smart cities Government Switched mode power supplies Tariffs Electricity supply industry Generators

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Non-Hermitian metasurface for asymmetric thermal emission

Non-Hermitian metasurface for asymmetric thermal emission

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Prasad, Ciril S. Everitt, Henry O. Naik, Gururaj V. Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States U.S. Army DEVCOM Army Research Laboratory-South HoustonTX United States

ISBN: (纸本)9781957171258

Non-Hermitian optics provides a unique platform to take advantage of absorption losses in materials and control radiative properties. We demonstrate a non-Hermitian metasurface that exhibit directional suppression of thermal radiation while maintaining transmission in mid-infrared. © Optica Publishing Group 2023 © 2023 The Author(s)

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High Voltage Selective Global Flexible Power Point Tracking for Photovoltaic Systems

High Voltage Selective Global Flexible Power Point Tracking ...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Anusha Kumaresan Hossein Dehghani Tafti Glen G. Farivar Neha Beniwal Naga Brahmendra Yadav Gorla Josep Pou Kai Strunz Energy Research Institute at NTU Interdisciplinary Graduate Programme Nanyang Technological University Singapore Department of Electrical Electronic and Computer Engineering University of Western Australia Australia Department of Electrical and Electronic Engineering The University of Melbourne Victoria Australia GE Global Research New York United States of America Department of Electrical Engineering Indian Institute of Technology Palakkad Kerala India School of Electrical and Electronic Engineering Nanyang Technological University Singapore Chair for Sustainable Electric Networks and Sources of Energy Technische Universität Berlin Germany

To provide frequency support in grid-connected photovoltaic (PV) systems with low inertia, flexible power point tracking (FPPT) control algorithms have been developed in the literature. To achieve this, a power reference obtained from the energy management system is used to control the PV output power. For PV systems to operate with FPPT, the frequent phenomenon of partial shading of PV arrays must be investigated. Among the multiple operating points possible for a given power reference, the one with a high voltage level should be selected in order to minimize the current stress on the semiconductor devices and to reduce the converter thermal stress. This work proposes an improved secant method to achieve this objective, which converges to a voltage reference that is higher than the global maximum power point voltage. The performance of the proposed high voltage selective global FPPT algorithm is validated through simulations in MATLAB-Simulink and experiments conducted on a scaled-down laboratory test setup.

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Analysis of the Brazilian Climate Data Influence on Soybean Pricing by Using Long Short-Term Memory Models

SSRN

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SSRN 2024年

作者： Oliva, Jefferson Tales Martelli, Otávio Pigozzo de Castro Barbosa, Marco Antônio Dal Molin, Viviane Casanova, Dalcimar Teixeira, Marcelo Graduate Program in Electrical and Computer Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Department of Academic Informatics Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Graduate Program in Production and Systems Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil

This work uses machine learning to verify whether the Brazilian climate influences international soybean price prediction. For this, climatic data, dollar quotes, inflation, and annual soybean production were collected from different data sources. Then, the collected data were pre-processed and grouped by Brazilian state. Afterward, data from the five most productive Brazilian states are chosen, such as Mato Grosso (MT), Mato Grosso do Sul (MS), Goiás (GO), Paraná (PR), and Rio Grande do Sul (RS). Afterward, predictive models are built using the long short-term memory (LSTM) method, which is applied in each chosen state dataset considering two different settings: with and without climatic data. Thus, two models were built for each Brazilian state, totaling ten predictors. In the experimental evaluation, when trained with climatic data, the PR model achieved the lowest values of root mean squared error (RMSE) and mean absolute error (MAE). Regarding predictors trained without climate data, the RS and PR obtained the lowest values of RMSE and MAE, respectively. After conducting statistical hypothesis tests, no significant difference was found among models, stating, with 95% certainty, that, in this study, the Brazilian climatic data did not influence the model performance for predicting soybean prices. On the other hand, one of the main contributions of work is conducting an unprecedented study about soybean price prediction using Brazilian climatic data. © 2024, The Authors. All rights reserved.

关键词： Long short-term memory

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Power-based Control for Microgrids and Extreme Fast Charging Stations with Low-Harmonic Current Content in the Medium Voltage Power Grid

Power-based Control for Microgrids and Extreme Fast Charging...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Dener A. De L. Brandão Thiago M. Parreiras João Marcus S. Callegari Igor A. Pires Danilo I. Brandao Braz De J. Cardoso Filho Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Institute of Technological Sciences - Universidade Federal de Itajubá Itabira Minas Gerais Brazil Department of Electronic Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil Department of Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil

The energy and transport sectors are responsible for a large portion of the emission of polluting gases into the atmosphere. Less polluting forms of energy and the electrification of the vehicle fleets are solutions to reduce this emission. In this context, the effect of high penetrion of distributed generation resources (DERs) and extreme fast charging (XFC) stations in the power grid is more evident. This paper proposes the use of the power-based control (PBC) to manage microgrids and XFC stations connected to the medium-voltage (MV) power grid. With the proposed control, the stations can mitigate the effect of the insertion of intermittent sources on the power system. Simulation results show that the active power dispatchability is achieved at the point of common coupling (PCC) with the proposed strategy, smoothing the power demand by 41 %. In such a scenario, the current total demand distortion (TDD) in the XFC stations is 0.19% using the Zero Harmonic Distortion (ZHD) converter.

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Optimized Transmission Strategy for UAV-RIS 2.0 Assisted Communications Using Rate Splitting Multiple Access

arXiv

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arXiv 2023年

作者： Huroon, Aamer Mohamed Huang, Yu-Chih Wang, Li-Chun Department of Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Taiwan Department of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan

In this paper, we study the transmission strategy of a ground-based beyond diagonal reconfigurable intelligent surface (BD-RIS), a.k.a RIS 2.0, in a network where multiple unmanned aerial vehicles (UAVs) simultaneously transmit signals to the respective groups of users. It is assumed that each group is assigned subcarriers orthogonal to those assigned to other groups and rate splitting multiple access (RSMA) is adopted within each group. A corresponding mixed integer nonlinear programming problem (MINLP) is formulated, which aims to jointly optimize 1) allocation of BD-RIS elements to groups, 2) BD-RIS phase rotations, 3) rate allocation in RSMA, and 4) precoders. To solve the problem, we propose using generalized benders decomposition (GBD) augmented with a manifold-based algorithm. GBD splits the MINLP problem into two sub-problems, namely the primal and the relaxed master problem, which are solved alternately and iteratively. In the primal problem, we apply block coordinate descent (BCD) to manage the coupling of variables effectively. Moreover, we recognize the manifold structure in the phase rotation constraint of BD-RIS, enabling the Riemannian conjugate gradient (RCG). Simulation results demonstrate the effectiveness of the proposed approach in maximizing spectral efficiency. Copyright © 2023, The Authors. All rights reserved.

关键词： Iterative methods

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Fast Learning in Spike-Timing-Dependent-Plasticity Using Ga-Sn-O Thin Film

Fast Learning in Spike-Timing-Dependent-Plasticity Using Ga-...

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International Workshop on Active-Matrix Flatpanel Displays and Devices (AM-FPD)

作者： Hidehito Kita Atsushi Horiuchi Tokiyoshi Matsuda Hidenori Kawanishi Mutsumi Kimura Graduate School of Advanced Science and Technology Ryukoku University Shiga Japan Department of Electrical and Electronic Communication Engineering Kindai University Osaka Japan Graduate School of Science and Technology Nara Institute of Science and Technology Takayama Ikoma Japan

ISBN: (数字)9784991216978

ISBN: (纸本)9798350385748

In this study, spike-timing-dependent-plasticity (STDP) was reproduced in devices fabricated using GTO (Ga-Sn-O). GTO was fabricated by sputtering, and the performance of the device was confirmed by I-V characteristics. The previous experiments were performed with a 1Hz voltage waveform, but this time, a 1kHz voltage waveform was used to investigate the possibility of high-speed learning. The experimental results showed a symmetric STDP, indicating the possibility of high-speed learning.

关键词： Performance evaluation Resistance Fabrication Active matrix technology Reviews Conferences Voltage

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Artificial Intelligence-Based Recommendation System for Detecting and Diagnosing Broken Bars in Induction Motors Under Transient Operation

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IFAC-PapersOnLine 2024年第19期58卷 1156-1161页

作者： Narco A.R. Maciejewski Roberto Z. Freire Anderson L. Szejka Thiago P.M. Bazzo Sofia M.A. Lopes Rogério A. Flauzino Department of Electrical Engineering - DAELT-CT Universidade Tecnológica Federal do Paraná - UTFPR Curitiba PR 80230-90 Brazil Production and Systems Engineering - PPGEPS-PB Energy Systems - PPGSE-CT Industrial and Systems Engineering Graduate Program - PPGEPS Pontifical Catholic University of Parana - PUCPR Curitiba PR 80215-901 Brazil Electrical Engineering - PPGEE-SC São Carlos School of Engineering - EESC Universidade de São Paulo - USP São Carlos SP 13566-590 Brazil

Three-phase induction motors are the main elements for converting electrical energy into mechanical energy and are extensively used in industry. Reducing maintenance costs becomes an incentive for developing systems capable of identifying defects. This research proposes a framework for recommending machine learning algorithms that diagnose and detect broken bar defects in three-phase induction motors under transient operation based on artificial intelligence. Employing experimental data, features were extracted and selected based on current, voltage, and vibration. A protocol of insertion of white noise showed that the proposed framework admitted 80% of noise without losing the predictive capacity based on a multicriteria performance measure.

关键词： condition monitoring fault detection fault classification machine learning maintenance engineering smart systems three-phase induction motor

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Soybean Price Prediction by Using Lstm Models Based on Brazilian Climatic Data

SSRN

引用

SSRN 2024年

作者： Oliva, Jefferson Tales Martelli, Otávio Pigozzo de Castro Barbosa, Marco Antônio Molin, Viviane Dal Casanova, Dalcimar Teixeira, Marcelo Graduate Program in Electrical Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Department of Academic Informatics Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Graduate Program in Production and Systems Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil

关键词： Long short-term memory

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Review ofPractical Psychometrics: A Guide for Test Users

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Structural Equation Modeling: A Multidisciplinary Journal 2024年第5期31卷 932-934页

作者： Musyaffa’ Ahmad Muhammad Faisal a Graduate Program Department of Electrical Engineering and Information Technology Faculty of Engineering Universitas Gadjah Mada Jl. Grafika No. 2 UGM Campus Yogyakarta55281 Indonesia b Master of Mathematics Education Program Faculty of Mathematics and Natural Sciences Yogyakarta State University Jl. Colombo 1 Yogyakarta55281 Indonesia

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