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Smart Electric Billing Management with IoT: Revolutionizing Energy Consumption

Smart Electric Billing Management with IoT: Revolutionizing ...

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international conference on Power, Energy, control and Transmission Systems (ICPECTS)

作者： R. Rengaraj G. R. Venkatakrishnan M. Rajalakshmi K. Mahalakshmi R.S.M. Arini Department of Electrical and Electronics Engineering Sri Sivasubramaniya Nadar College of Engineering Chennai India Department of Computing Technologies SRM Institute of Science and Technology Chennai India

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508852

India is the world's third largest producer and third largest consumer of electricity. Traditional billing systems in India lack real-time monitoring, making it difficult to address peak demand efficiently. They often lead to inaccurate billing due to manual readings. These systems do not incentivize offpeak consumption, hindering efforts to optimize energy usage. Embracing modern approaches like IoT and Time-of-Use pricing can enhance accuracy, promote energy efficiency, and also optimize energy consumption based on the demand requirement. To address the increasing energy demands and environmental concerns, the integration of Internet of Things (IoT) technologies, Time-of-Use (TOU) pricing strategies, and machine learning algorithms presents a transformative approach to revolutionize electric billing management. Developing a comprehensive system that combines real-time data acquisition through IoT devices with dynamic pricing based on TOU can optimize energy consumption patterns. Machine learning models are employed to analyze historical usage data, predict consumption patterns, and dynamically adjust pricing to incentivize efficient energy utilization. This aims to enhance user awareness, encourage responsible energy usage, and contribute to a sustainable and resilient energy ecosystem.

关键词： Training Energy consumption Machine learning algorithms Accuracy Electricity Scalability Pricing Transforms Real-time systems Internet of Things

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On Graph Theory vs. Time-Domain Discrete-Event Simulation for Topology-Informed Assessment of Power Grid Cyber Risk

On Graph Theory vs. Time-Domain Discrete-Event Simulation fo...

引用

IEEE international conference on Smart Grid Communications (SmartGridComm)

作者： Khandaker Akramul Haque Leen Al Homoud Xin Zhuang Mariam Elnour Ana Goulart Katherine Davis Department of Electrical and Computer Engineering Texas A&M University College Station TX USA Department of Engineering Technology and Industrial Distribution Texas A&M University College Station TX USA

ISBN: (数字)9798350318555

ISBN: (纸本)9798350318562

The shift toward more renewable energy sources and distributed generation in smart grids has underscored the significance of modeling and analyzing modern power systems as cyber-physical systems (CPS). This transformation has highlighted the importance of cyber and cyber-physical properties of modern power systems for their reliable operation. Graph theory emerges as a pivotal tool for understanding the complex interactions within these systems, providing a framework for representation and analysis. The challenge is vetting these graph theoretic methods and other estimates of system behavior from mathematical models against reality. High-fidelity emulation and/or simulation can help answer this question, but the comparisons have been understudied. This paper employs graph-theoretic metrics to assess node risk and criticality in three distinct case studies, using a Python-based discrete-event simulation called SimPy. Results for each case study show that combining graph theory and simulation provides a topology-informed security assessment. These tools allow us to identify critical network nodes and evaluate their performance and reliability under a cyber threat such as denial of service threats.

关键词： Measurement Network topology Reliability theory Cyber-physical systems Traffic control Graph theory Smart grids Power system reliability Topology Time-domain analysis

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A Review on Magnetic Resonance Spectroscopy for Clinical Diagnosis of Brain Tumour using Deep Learning 3

A Review on Magnetic Resonance Spectroscopy for Clinical Dia...

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3rd international conference on Advances in computing, Communication control and Networking, ICAC3N 2021

作者： Rajeev, S.K. Rajasekaran, M. Pallikonda Krishna Priya, R. Al Bimani, Ali Kalasalingam Univeristy Department of Electronics Commnication Engineering TamilNadu Madurai India National Univerisity of Science and Technology Department of Electrical Commnication Engineering Oman National Univerisity of Science and Technology Oman

ISBN: (纸本)9781665438117

Medical imaging is a way to analyze the anatomical structure of the body. With the advent of new technologies, more and more sophisticated imaging techniques have been developed such as MRI, CT, PET, X-ray, etc. which have made the non-invasive diagnosis of diseases a lot easier. Magnetic Resonance Spectroscopy (MRS) gives detailed information about the chemical changes occurring in the brain by measuring the change of metabolites. It can be used to diagnose tumors in the brain and other brain-related diseases and disorders. Magnetic resonance spectroscopy is an encouraging tool that can be used for the effective diagnosis and grading of brain tumors but it suffers from many problems such as baseline distortions and artifacts, low resolution, low intensity images which makes its applicability a practical difficulty. The advancements in the field of Deep Learning can be effectively used to tackle the challenges in MRS which in turn can be employed for the brain tumor detection and classification. © 2021 IEEE.

关键词： Magnetic resonance spectroscopy

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Study of Smart Lifting 3D Garage Design Based on the Low-Cost PLC control System 6th

Study of Smart Lifting 3D Garage Design Based on the Low-Cos...

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6th international conference on Advanced Machine Learning Technologies and Applications, AMLTA 2021

作者： Zhang, Rongsheng Chang, Kuo-Chi Chu, Kai-Chun Chang, Fu-Hsiang Wang, Hsiao-Chuan Hsu, Tsui-Lien Lin, Yuh-Chung Sung, Tien-Wen Trong-The, Nguyen Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China School of Information Science and Engineering Fujian University of Technology Fuzhou China School of Management Fujian University of Technology Fuzhou China Department of Tourism Shih-Hsin University Taipei Taiwan Institute of Environmental Engineering National Taiwan University Taipei Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (纸本)9783030697167

As the current computer design level continues to improve, the process equipment and production line management levels are relatively stable. The intelligent and automatic 3D garage-type has shown a diversified development trend. Several garage types are currently in everyday use, including vertical lifting type, vertical lifting type, simple lifting type, horizontal shifting circulation type, channel stacking type, etc. The 3D lifting garage has a simple structure, small floor space, low operating cost, and the most extensive application requirements. However, this study summarizes the application status and development prospects of smart lifting 3D garages first. Then the system analyzes the working principle and mechanical structure characteristics of the smart lifting 3D garage, analyzes the control requirements, and designs the semi-automatic control system of the 3D garage S7–1200—it including the PLC control program and the man-machine interface. Finally, the overall system control effect is verified through simulation. This study meter has superficial operation characteristics, a high degree of automation, fast operation speed, high stability, and has deep development value and application prospects in specific markets. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Automation

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MPPT controller For Grid Tied PV System Based On Improved Sepic Converter

MPPT Controller For Grid Tied PV System Based On Improved Se...

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international conference on Circuit, Power and computing Technologies (ICCPCT)

作者： T. R. Premila S. Mohamed Ibrahim badusha K. Shankar Raja P. Gobinath Department of Electrical and Electronics Engineering Vels Institute of Science Technology Advanced Studies(VISTAS) Pallavaram Chennai

Solar Photovoltaic (PV) systems are becoming more and more popular because they convert solar radiation directly into clean, renewable electricity. Partial shading situations are when a PV module may be partially shadowed, which might result in a reduction in the solar panel's power production. It significantly lowers the system's power output. To address this, continuous duty cycle variation methods that track MPP under partial shade have been proposed. An innovative Type-2 Fuzzy Maximum Power Point Tracking (MPPT) algorithm that can monitor a Supreme Power Point in the presence of numerous local maxima has been incorporated into the proposed system. In these schemes, the proposed Improved Single Ended Primary Inductance Converter (SEPIC) is coupled to PV module to enable the maximum output voltage under any given circumstance. This makes the device more compact. The converter's objective is to deliver input currents with an acceptable harmonic content in a grid interface while maintaining a constant power supply. Finally, several numerical simulated testing of the proposed control utilizing the MATLAB is carried out.

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Improved methodology for estimating specific energy consumption in electric arc furnaces when changing electrical modes

Improved methodology for estimating specific energy consumpt...

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2021 international conference on Industrial engineering, Applications and Manufacturing, ICIEAM 2021

作者： Nikolaev, A.A. Efremov, V.A. Tulupov, P.G. Automated Electric Drive and Mechatronics dept Nosov Magnitogorsk State Technical University Magnitogorsk Russia

ISBN: (纸本)9781728145877

The paper describes a methodology for evaluating the improved electric modes efficiency for arc steel-making furnaces and ladle-furnaces. The technical effect is achieved due to the reduction of specific electricity consumption. It is shown that a direct comparison of electric power consumption in the compared periods before and after the electric regime change of arc furnace cannot be considered as objective assessment, since different technological factors have influenced the plant. Data on time, electrical and process parameters were collected for the two analysed periods. The proposed methodology uses the regression models of electrical consumption for arc steel-making furnace and ladle-furnace plant. The average values of sampling factors are analysed. The authors determine two periods in which it is more difficult to achieve a reduction in specific energy consumption. Furthermore, the technical effect is adjusted to the most severe conditions. The average values of the hardest period factors are substituted in both regression equations. Then the specific electricity consumption is estimated. This methodology is applicable when changing the settings of existing automatic control systems or when replacing old systems with new ones. © 2021 IEEE.

关键词： Regression analysis

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Fractional Order AGC Design for Power Systems via Artificial Gorilla Troops Optimizer

Fractional Order AGC Design for Power Systems via Artificial...

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international conference on Power Electronic Drives

作者： Sneha V Sah Vivek Prakash Pawan Kumar Pathak Anil Kumar Yadav School of Automation Banasthali Vidyapith Rajasthan India Department of Technical Education Government of Rajasthan Government Polytechnic Tonk India Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Department of Electrical Engineering National Institute of Technology Hamirpur Hamirpur (H.P.) India

Due to parameter uncertainty, vague loading behavior, and nonlinearities of the interconnected power system (IPS), various controllers come into the picture to deal with automatic generation control (AGC). The critical role of AGC is to maintain a balance among power demands and generations in IPS. This paper deals with the implementation of fractional order PID (FOPID) controller for AGC in two areas reheat thermal type IPS. To obtain the controller parameters, a recently invented metaheuristic technique named Artificial Gorilla Troops optimizer (GTO) is proposed. To replicate the practical scenarios nonlinearities such as generation rate constraints (GRC) and generation dead band (GDB) are considered in the proposed work. A comparative analysis of four state-of-the-art metaheuristic approaches, as well as the performance evaluation of the proposed controller against parametric uncertainties, have been performed. Finally, the obtained results reveal the superior performance of the proposed control scheme.

关键词： Uncertain systems Renewable energy sources Uncertainty Power demand Metaheuristics automatic generation control Robustness

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Web Data Management Platform Integrating Encryption Algorithms 13

Web Data Management Platform Integrating Encryption Algorith...

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13th international conference on Electronics, Computers and Artificial Intelligence, ECAI 2021

作者： Dinca, Alexandru Angelescu, Nicoleta Popescu, Dan University POLITEHNICA of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Valahia University of Targoviste Faculty of Electrical Engineering Electronics and Information Technology Targoviste Romania

ISBN: (纸本)9781665425346

The development area of web technologies has gained great popularity due to the power with which these new technologies can manage resources and due to developers or experts of various types who can build applications and scale them according to the needs of different application areas or companies which use these types of applications. In this paper we present a modern web platform for data management that includes current web technologies and security standards that ensure the integrity of data in the information flow of the application. © 2021 IEEE.

关键词： Information management

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Modeling, Analysis and Simulation of the Effect of Temperature on Magnetostrictive Actuators

Modeling, Analysis and Simulation of the Effect of Temperatu...

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international conference on Fluid Power and Mechatronics (FPM)

作者： Xinyuan Zhang Shaoping Wang Yu Niu Xiao Wu Xingjian Wang Alex I. Gavrilov School of Automation Science and Electrical Engineering Beihang University Beijing China Tianmushan Laboratory Hangzhou China Ningbo Institute of Technology Beihang University Ningbo China Research Institute of Aero-Engine Beihang University Beijing China Department of Automatic Control Systems Bauman Moscow State Technical University Moscow Russia

ISBN: (数字)9798350304947

ISBN: (纸本)9798350304954

The increased demand for active control of engines has made the study of high-frequency response actuators increasingly important, and actuators based on magnetostrictive materials are promising for a wide range of applications. In this paper, the magnetic field distribution and various thermal losses including Joule heat loss, eddy current loss and hysteresis loss inside the giant magnetostrictive actuator (GMA) are analyzed, and the mathematical model of the current-driven GMA operation is derived, where the new J-A model considering the temperature effect is used to describe the hysteresis nonlinearity of the material. This paper simulates the actuator model under the action of multiple physical fields in COMSOL, focusing on the variation of the output displacement of the actuator when the thermal field and thermal expansion are integrated, and provides the theoretical basis for the design of the GMA control algorithm in the future.

关键词： Actuators Analytical models Thermal expansion Temperature distribution Mechatronics Magnetostriction Magnetic hysteresis

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Dissipative State Estimation for Delayed Discrete-Time Memristive Neural Networks Under Dynamic Event-Triggered Mechanisms and Deception Attacks

Dissipative State Estimation for Delayed Discrete-Time Memri...

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2021 international conference on Neuromorphic computing, ICNC 2021

作者： Tao, Huimin Liu, Hongjian Zhu, Jiali Tan, Hailong School of Electrical Engineering Anhui Polytechnic University Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Ministry of Education Wuhu China School of Mathematics-Physics and Finance Anhui Polytechnic University Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Ministry of Education Wuhu China

ISBN: (纸本)9781665412872

In this paper, the state estimation problem for delayed discrete-time memristive neural networks subject to deception attacks is concerned. The main purpose is to design a state estimator such that the error dynamics of the state estimation is stochastically stable and strict dissipative. The randomness of deception attacks is described via a set of Bernoulli distributed white sequences with known conditional probabilities. In addition, in order to reduce unnecessary resource consumption in the communication channels, a dynamic event-triggering mechanism is introduced. By using the Lyapunov-Krasovskii functional and stochastic analysis method, sufficient conditions for stochastic stability and strict dissipation of the error system are acquired. On this basis, a co-design scheme of estimator parameters and the event-triggered matrix is proposed. Finally, the numerical simulation shows the effectiveness of the proposed state estimation scheme. © 2021 IEEE.

关键词： State estimation

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