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Management of a Microgrid using Deep Learning Techniques

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Management of a Microgrid using Deep Learning Techniques

International Conference on Contemporary Computing and Informatics (IC3I)

作者： Jeidy Panduro-Ramirez Kapil Joshi M. Kalyan Chakravarthi Prabhdeep Singh Naveen Kumar Bind Ayan Banik Universidad Tecnológica del Perú Perú Uttaranchal Institute of Technology Uttaranchal University Dehradun Uttarakhand India School of Electronics Engineering VIT - AP University Amaravati Andhra Pradesh Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Electrical Engineering JSS Academy of Technical Education Sector 62 Noida Uttar Pradesh National Institute of Technical Teachers’ Training & Research (NITTTR) Kolkata West Bengal India

Our power generation grid is experiencing a dramatic modernization as a result of recent developments in smart-grid advancements. By offering a flexible method of sort of technology solar and wind power (RES) into the electricity system, microgrid (MG) plays a significant role in the modernity. Spread RES, like solar and wind, can, nevertheless, be very essentially random and occasional. It is challenging to effectively execute an MG because of these erratic resources, state of charge, and the like but on the sides of the market. This paper addressed this issue and presented a novel strategy for the real-time timetabling of an MG taking into account the adequacy of renewables, energy cost, and utility grid confusion. The suggested solution is studying and therefore does not involve an accurate model of the confusion, in contrast to traditional model-based methods that call for an indicator to estimate the confusion. The goal of the MG power process is to reduce the daily operational expenses, and it is specifically modelled as a Markov Decision Process (MDP). To resolve the MDP, a deep encouragement learning (DRL) strategy has been developed. The deep Q-network (DQN) algorithm is used to find the human brain in the DRL framework, which uses a deep fnn network to measure the ideal response role. The suggested method directly generates real-time creation schedule using the MG’s current state as inputs. Furthermore, case experiments are performed to show the usefulness of the suggested strategy using total power data from the Cal Organization For Standardization (CAISO).

关键词： Schedules Adaptation models Wind Costs Microgrids Predictive models Wind power generation

Frequency Control Impact of Electric Vehicles on Grid-Connected Areas

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Frequency Control Impact of Electric Vehicles on Grid-Connec...

Smart Grids and Energy Systems (SGES), International Conference on

作者： Sareh Agheb Ke Meng Gerard Ledwich Glenn Platt School of Electrical Engineering and Telecommunications University of New South Wales Sydney Australia School of Electrical Engineering and Computer Science Queensland University of Technology Brisbane Australia CSIRO Energy Sector CSIRO Sydney Australia

ISBN: (数字)9781728185507

ISBN: (纸本)9781728185507

This paper presents an emergency frequency control potential of Electric Vehicles (EV)s in a wide area network. Lyapunov energy function is used to maximize the rate of reduction of total kinetic energy in a two-area grid after a contingency event. The effectiveness of the proposed control strategy on damping the oscillations is studied, exploring the locations aspect of the model with the charging stations either in the center of grid-connected areas or in the corners.

关键词： Wide area networks Electric vehicles Batteries Smart grids Power systems Frequency control Oscillators

Integrating Floating Solar PV with Hydroelectric Power Plant: Analysis of Ghazi Barotha Reservoir in Pakistan

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Energy Procedia 2019年 158卷 816-821页

作者： Huzaifa Rauf Muhammad Shuzub Gull Naveed Arshad Department of Electrical Engineering Syed Babar Ali School of Science and Engineering LUMS Sector U DHA Lahore Pakistan Department of Computer Science Syed Babar Ali School of Science and Engineering LUMS Sector U DHA Lahore Pakistan

Renewable energy is built as the future of energy value chain. In particular, solar energy is being utilized at a faster pace than ever. The problem sometimes occurs that large scale Floating Solar PV (FSPV) plants have to be developed, away from the population which adds to the cost of transmission and distribution. Floating Solar PV plants have recently gained traction as a suitable alternative of ground based large scale PV installation. FSPV, not only utilizes the water as real estate, but it has a number of other advantages. For example, FSPV could utilize the existing transmission and distribution infrastructure that is the part of hydroelectric power plant anyways. In this paper, we analyze hydro-FSPV combination on a small dam in Pakistan. Our results show that FSPV could complement the existing hydroelectric production and could provide electricity in conjunction with the existing generators of the hydroelectric plant. Furthermore, we also discuss options of integrating FSPV with the existing electrical infrastructure of Ghazi Barotha Dam.

关键词： Floating Solar PV FSPV Hydro-FSPV Hydroelectric production electrical infrastructure Ghazi Barotha Dam

Using Biological Variables and Social Determinants to Predict Malaria and Anemia among Children in Senegal

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arXiv 2021年

作者： Sow, Boubacar Suguri, Hiroki Mukhtar, Hamid Ahmad, Hafiz Farooq Graduate School of Project Design Miyagi University 1-1 Gakuen Taiwa Cho Kurokawa GunMiyagi Prefecture981-3298 Japan School of Project Design Miyagi University 1-1 Gakuen Taiwa Cho Kurokawa GunMiyagi Prefecture981-3298 Japan School of Electrical Engineering and Computer Science National University of Sciences and Technology NUST Sector H-12 Islamabad44000 Pakistan Department of Computer Science College of Computer Sciences & Information Technology King Faisal University P. O. Box: 400 Al-Hassa 31982 Saudi Arabia

Integrating machine learning techniques in healthcare becomes very common nowadays, and it contributes positively to improving clinical care and health decisions planning. Anemia and malaria are two life-threating diseases in Africa which affect the red blood cells and reduce hemoglobin production. This paper focuses on analyzing child health data in Senegal using four machine learning algorithms in Python: KNN, Random Forests, SVM and Naïve Bayes. Our task aims to investigate large scale data from The Demographic and Health Survey (DHS) and to find out hidden information for anemia and malaria. We present two classification models for the two blood disorders using biological variables and social determinants. The findings of this research will contribute to improving child healthcare in Senegal by eradicating anemia and malaria, and decreasing child mortality rate. © 2021, CC BY.

关键词： Diseases

[Retracted] Automated Detection and Segmentation of Exudates for the Screening of Background Retinopathy

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Journal of Healthcare engineering 2023年第1期2023卷

作者： Jaskirat Kaur Deepti Mittal Sharaf Malebary Soumya Ranjan Nayak Devendra Kumar Manoj Kumar Gagandeep Simrandeep Singh Department of Electronics and Communication Engineering Punjab Engineering College (Deemed to be University) Sector 12 Chandigarh 160012 India Electrical and Instrumentation Engineering Department Thapar Institute of Engineering and Technology Patiala 147004 Indiathapar.edu Department of Information Technology Faculty of Computing and Information Technology in Rabigh King Abdulaziz University Jeddah 21911 Saudi Arabiakau.edu.sa School of Computer Engineering KIIT Deemed to be University Bhubaneswar 751024 Odisha India Department of Computer Science Wachemo University Hosaena Ethiopiawcu.edu.et Faculty of Engineering and Information Sciences University of Wollongong in Dubai Dubai Knowledge Park UAEuowdubai.ac.ae MEU Research Unit Middle East University Amman 11831 Jordanmeu.edu.jo Computer Science Engineering Department Chandigarh Engineering College Mohali *** Electronics and Communication Engineering Department UCRD Chandigarh University Mohali Indiachandigarhuniversity.ac.in

Exudate, an asymptomatic yellow deposit on retina, is among the primary characteristics of background diabetic retinopathy. Background diabetic retinopathy is a retinopathy related to high blood sugar levels which slowly affects all the organs of the body. The early detection of exudates aids doctors in screening the patients suffering from background diabetic retinopathy. A computer-aided method proposed in the present work detects and then segments the exudates in the images of retina acquired using a digital fundus camera by (i) gradient method to trace the contour of exudates, (ii) marking the connected candidate pixels to remove false exudates pixels, and (iii) linking the edge pixels for the boundary extraction of exudates. The method is tested on 1307 retinal fundus images with varying characteristics. Six hundred and forty-nine images were acquired from hospital and the remaining 658 from open-source benchmark databases, namely, STARE, DRIVE MESSIDOR, DiaretDB1, and e-Ophtha. The exudates segmentation method proposed in this research work results in the retinal fundus image-based (i) accuracy of 98.04%, (ii) sensitivity of 95.345%, and (iii) specificity of 98.63%. The segmentation results for a number of exudates-based evaluations depict the average (i) accuracy of 95.68%, (ii) sensitivity of 93.44%, and (iii) specificity of 97.22%. The substantial combined performance at image and exudates-based evaluations proves the contribution of the proposed method in mass screening as well as treatment process of background diabetic retinopathy.

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Detection of Machine Tool Anomalies from Bayesian Changepoint Recurrence Estimation

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Detection of Machine Tool Anomalies from Bayesian Changepoin...

IEEE International Conference on Industrial Informatics (INDIN)

作者： Christian Reich Christina Nicolaou Ahmad Mansour Kristof Van Laerhoven Corporate Sector Research Robert Bosch GmbH Stuttgart Germany Dept. of Electrical Engineering and Computer Science University of Siegen Germany

In this study, we consider the problem of detecting process-related anomalies for machine tools. The similar shape of successive sensor signals, which arises due to the same process step sequence applied to each workpiece, suggests extracting shape-related features. In recent years, shapelets dominated the field of shape-related features. Unfortunately, they involve a high computational burden due to hyperparameter *** introduce alternative shape-related features relying on abrupt signal changes (changepoints) reflecting the changes of process steps. During normal operation, changepoints follow a highly recurrent pattern, i.e., appear at similar locations. Thus, being able to distinguish regular, recurrent from abnormal, non-recurrent changepoints allows detecting process *** changepoint recurrence estimation, we extend the Bayesian Online Changepoint Detection (BOCPD) method. The extension allows distinguishing normal and abnormal changepoints relying on empirical estimates of the changepoint recurrence distribution. Subsequently, changepoint-related features are introduced and compared to shapelets and wavelet-based features in a case study comprising real-world machine tool *** results verify changepoint locations being comparable to shapelet locations found by the FLAG shapelet approach. Furthermore, quantitative results suggest superior classification performance both to shapelets and wavelet-based features.

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Applications of nanomagnets as dynamical systems

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arXiv 2021年

作者： Rana, Bivas Mondal, Amrit Kumar Bandyopadhyay, Supriyo Barman, Anjan Center for Emergent Matter Science RIKEN 2-1 Hirosawa Wako351-0198 Japan Faculty of Physics Adam Mickiewicz University Poznań Uniwersytetu Poznanskiego 2 Poznań61-614 Poland Department of Condensed Matter Physics and Material Sciences S. N. Bose National Centre for Basic Sciences Block JD Sector III Salt Lake Kolkata700 106 India Department of Electrical and Computer Engineering Virginia Commonwealth University RichmondVA23284 United States

When magnets are fashioned into nanoscale elements, they exhibit a wide variety of phenomena replete with rich physics and the lure of tantalizing applications. In this topical review, we discuss some of these phenomena, especially those that have come to light recently, and highlight their potential applications. We emphasize what drives a phenomenon, what undergirds the dynamics of the system that exhibits the phenomenon, how the dynamics can be manipulated, and what specific features can be harnessed for technological advances. For the sake of balance, we point out both advantages and shortcomings of nanomagnet based devices and systems predicated on the phenomena we discuss. Where possible, we chart out paths for future investigations that can shed new light on an intriguing phenomenon and/or facilitate both traditional and non-traditional applications. Copyright © 2021, The Authors. All rights reserved.

关键词： Magnetization reversal

Extreme sub-wavelength magneto-elastic electromagnetic antenna implemented with multiferroic nanomagnets1

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arXiv 2020年

作者： Drobitch, J.L. De, A. Dutta, K. Pal, P. Adhikari, A. Barman, A. Bandyopadhyay, S. Dept. of Electrical and Computer Engineering Virginia Commonwealth University RichmondVA23284 United States Dept. of Condensed Matter Physics and Material Science S. N. Bose National Center for Basic Sciences JD Block Sector III Salt Lake Kolkata700 106 India

Antennas typically have emission/radiation efficiencies bounded by A λ 2 ( A2 ) where A is the emitting area and λ is the wavelength of the emitted wavelength. That makes it challenging to miniaturize antennas to extreme sub-wavelength dimensions. One way to overcome this challenge is to actuate an antenna not at the resonance of the emitted wave, but at the resonance of a different excitation that has a much shorter wavelength at the same frequency. We have actuated an electromagnetic (EM) antenna with a surface acoustic wave (SAW) whose wavelength is about five orders of magnitude smaller than the EM wavelength at the same frequency. This allowed us to implement an extreme sub-wavelength EM antenna, radiating an EM wave of wavelength λ = 2 m, whose emitting area is ~10-8 m2 (A λ 2 = 2.5 x 10-9), and whose measured radiation efficiency exceeded the A λ 2 limit by over 105. The antenna consisted of magnetostrictive nanomagnets deposited on a piezoelectric substrate. A SAW launched in the substrate with an alternating electrical voltage periodically strained the nanomagnets and rotated their magnetizations owing to the Villari effect. The oscillating magnetizations emitted EM waves at the frequency of the SAW. These extreme sub-wavelength antennas, that radiate with efficiencies a few orders of magnitude larger than the A λ 2 limit, allow drastic miniaturization of communication systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Antennas

A Perspective on Quantum Sensors from Basic Research to Commercial Applications

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arXiv 2024年

作者： Oh, Eun Gregoire, Maxwell D. Black, Adam T. Hughes, K. Jeramy Kunz, Paul D. Larsen, Michael Lautier-Gaud, Jean Lee, Jongmin Schwindt, Peter D.D. Mouradian, Sara L. Narducci, Frank A. Sackett, Charles A. Laboratory for Physical Sciences College ParkMD20740 United States Air Force Research Laboratory AlbuquerqueNM87117 United States Naval Research Laboratory WashingtonDC20375 United States Fieldline Inc. BoulderCO80301 United States Army Research Laboratory AdelphiMD20783 United States Northrup Grumman Woodland HillsCA91367 United States Rue François Mitterrand Talence33400 France Sandia National Laboratories AlbuquerqueNM87123 United States AFRL/RVBYT Space Vehicles Directorate Section Head Quantum Optics Optical Sciences Division Fieldline Industries Inc. Quantum Science & Technology Branch Chief DEVCOM Army Research Laboratory Department of Physics The University of Texas at Austin AustinTX78712 United States Quantum Science Architect Mission Systems Sector Emerging Capabilities Development iXblue Quantum Sensors The Technical Staff Atom-Optic Sensing Department The Technical Staff Atom-Optic Sensing Department Electrical and Computer Engineering Department Department of Physics Physics Department University of Washington SeattleWA98105 United States Naval Postgraduate School MontereyCA93943 United States University of Virginia CharlottesvilleVA22904 United States

Quantum sensors represent a new generation of sensors with improved precision, accuracy, stability, and robustness to environmental effects compared to their classical predecessors. After decades of laboratory development, several types of quantum sensors are now commercially available or are part-way through the commercialization process. This article provides a brief description of the operation of a selection of quantum sensors that employ the principles of atom-light interactions and discusses progress toward packaging those sensors into products. This article covers quantum inertial and gravitational sensors, including gyroscopes, accelerometers, gravimeters, and gravity gradiometers that employ atom interferometry, nuclear magnetic resonance gyroscopes, atomic and spin-defect magnetometers, and Rydberg electric field sensors. © 2024, CC BY-NC-ND.

关键词： Gyroscopes