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Operational Reliability Modeling and Assessment of Battery Energy Storage Based on Lithium-ion Battery Lifetime Degradation

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Journal of Modern Power Systems and Clean Energy 2022年第6期10卷 1738-1749页

作者： Lin Cheng Yuxiang Wan Yanglin Zhou David Wenzhong Gao State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijingChina Department of Electrical and Computer Engineering University of DenverDenverUSA IEEE

Battery energy storage(BES)systems can effectively meet the diversified needs of power system dispatching and assist in renewable energy *** reliability of energy storage is essential to ensure the operational safety of the power ***,BES systems are composed of battery *** suggests that BES performance depends not only on the configuration but also on the operating state over different lifetime *** lack of safety and reliability is the main bottleneck preventing widespread applications of BES ***,a reliability assessment algorithm and a weak-link analytical method for BES systems are proposed while considering battery lifetime ***,a novel lithium-ion battery model is proposed to identify the degradation rate of solid electrolyte interphase film formation and capacity *** impacts of different operating conditions are considered in stress factor ***,a reliability assessment algorithm for a BES system is introduced based on a universal generating *** innovative weak-link analytical method based on the reliability importance index is proposed that combines the evaluation results of state-oriented and state-change-oriented indexes through an entropy weight *** model,algorithm,indexes,and the usefulness are demonstrated in case studies based on aging test data and actual bus operating *** results demonstrate the effects of the battery status and working conditions on BES ***-link analysis is also used to assist BES systems in avoiding short-board batteries to achieve long lifetimes and efficient operation.

关键词： Battery energy storage lifetime degradation operational reliability capacity plummeting weak-link analysis

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Analysis and Design of the Detection and control System of Authorized and Unauthorized Users using Internet of Things and Machine Learning 9

Analysis and Design of the Detection and Control System of A...

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9th International Conference on control, Instrumentation and Automation, ICCIA 2023

作者： Sarshar, Negar Nasiri, Ali Qom University of Technology Faculty of Electrical & Computer Engineering Department of Electronics Engineering Qom Iran Tarbiat Modares University Faculty of Electrical & Computer Engineering Department of Electronics Engineering Tehran Iran

ISBN: (纸本)9798350366013

In this article, a system has been designed using the Internet of Things and machine learning to detect equipment theft, monitor the entry and exit of people, as well as monitor people's activities to prevent equipment theft and provide security to the environment against possible theft. By using the motion detection sensor and the push buttons installed on the entrance doors, the entry and movement of people are monitored in real-time. Then, with machine vision and image processing algorithms, known and unknown people are cleaned and if necessary, a warning message including the video of the person's presence in the environment along with the person's image is sent to the relevant official. Also, the security doors will be locked until the relevant official confirms the safe situation. © 2023 IEEE.

关键词： Internet of things

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Diagnosis of sleep apnea by optimal fuzzy system based on respiratory signals 10

Diagnosis of sleep apnea by optimal fuzzy system based on re...

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10th International Conference on Artificial Intelligence and Robotics, QICAR 2024

作者： Pouramirarsalani, Shahrzad Maleki, Soozan Etemadi Rajebi, Saman Manaf, Nader Vadhani Roohany, Azade Faculty of Electrical and Computer Engineering university of Tabriz Tabriz Iran Department of Electrical Engineering Seraj Higher Institute Tabriz Iran Department of Computer Engineering Tabriz Branch Islamic Azad University Tabriz Iran

ISBN: (纸本)9798350348873

This Sleep apnea is an important and common disorder that leads to the reduction or interruption of respiratory flow during sleep due to obstruction of the airways. Currently, nocturnal polysomnography (PSG) is the standard approach for diagnosing sleep apnea. This method is expensive, time-consuming and inconvenient due to space limitations and the complexity of recording physiological signals. Today, machine learning algorithms are used to provide more friendly and accessible solutions that help in cost-effective and easy to diagnosis. In this article, a fuzzy network optimized with artificial intelligence algorithms is formed as a classband model for sleep apnea diagnosis. Changes in the acoustic signals caused by breathing sounds during sleep apnea can be used to monitor and diagnose sleep apnea events. The dataset of audio signals recorded from the sound of breathing is collected by a microphone and a mobile phone. The fuzzy classband model was built based on Mamdani's fuzzy inference rules from the extracted features, and the correct classification rate (CCR) was 77.5 by adjusting different parameters of the model. Coefficients were obtained as feature values to increase data resolution by the particle swarm optimization (PSO) optimization algorithm and Fisher's discriminant ratio. By applying these coefficients to the input of the fuzzy network in order to optimize the feature vector, the correct classification rate was obtained equal to 87.5% with the leave one out cross-validation method. ©2024 IEEE.

关键词： Learning algorithms

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Optimizing the Operation of Energy Storage Systems Using Artificial Intelligence for Economic Performance and Energy Transition 14

Optimizing the Operation of Energy Storage Systems Using Art...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Zournatzis, Athanasios C. Kontargyri, Vassiliki T. Nicolopoulou, Eleni P. Christodoulou, Christos A. School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Department of Electrical and Electronics Engineering Faculty of Engineering University of West Attica Athens Greece

ISBN: (纸本)9781837242689

The utilization of energy storage systems (ESS) and the expansion of their installed capacity are crucial steps towards achieving energy neutrality goals. These systems, often integrated with photovoltaic installations, represent an intermediate stage that introduces new challenges for distribution management and financial burdens for consumers and society. To maximize the benefits of ESS, it is necessary to design an optimization system that considers the battery lifecycle, installed capacity, and economic benefits. A key objective is the determination and reduction of the per-unit usage cost of these systems, which represents a significant innovation of this work. This paper proposes an optimization model that incorporates factors such as energy pricing, charging/discharging efficiency, battery lifespan, and renewable energy forecasts. The model leverages artificial intelligence (AI), including machine learning and deep learning, for data analysis and decision-making based on historical data and patterns. This solution is designed to address the needs of both residential and industrial clients, further expanding its applicability. This approach optimizes the economic performance of ESS, minimizes energy transition costs, and fosters favorable conditions for a successful transition. © The Institution of engineering & Technology 2024.

关键词： Energy economics

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Fault-Tolerant controller Design for PMSM Drives with Single-Phase Fault Inverters 4

Fault-Tolerant Controller Design for PMSM Drives with Single...

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4th International Symposium on Instrumentation, control, Artificial Intelligence, and Robotics, ICA-SYMP 2025

作者： Buakaew, Sornchai Pongyart, Witthawas King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (纸本)9798331505400

Permanent magnet synchronous motors (PMSMs) are commonly used in various electrical drive applications due to their high efficiency and performance. However, these systems are susceptible to several types of faults. To ensure uninterrupted operation in the event of a fault, researchers have focused on developing fault-tolerant control systems. This paper presents a fault-tolerant controller design for PMSM drives with single-phase fault inverters. A fault-tolerant inverter is introduced, and an energy-based controller is implemented in the current loop, with a PI-controller governing speed control. The proposed control system is tested under both normal and fault conditions, demonstrating its ability to maintain motor torque and speed while ensuring system stability in both scenarios. © 2025 IEEE.

关键词： Permanent magnets

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Algorithmic Decomposition of Railway Objects for Distributed Interlocking System

Periodica Polytechnica Electrical Engineering and Computer S...

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Periodica Polytechnica electrical engineering and computer Science 2024年第4期68卷 319-326页

作者： Arató, Péter Markovits, Tibor Gergely Rácz, György Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Magyar tudósok krt. 2. BudapestH-1117 Hungary

Railway interlocking systems can be implemented as distributed systems, where each part of a station is handled by a separate logical unit. The logical units of such systems form a network and communicate by interchanging messages. Such distributed architectures are well known in large industrial control systems. There are several design practices and also algorithmic task partitioning methods that are applicable in distributed control systems. Some of such methods can also be adapted in designing of railway interlocking systems as well. In the case of such systems, the communication time between components must be kept low. Namely each separate controller in a given route must be able to exchange their internal state within a limited time in order to permit the train movement authorization. This limitation could cause high traffic load, if every logical unit would be interconnected with each other. Therefore, the main goal of the minimization is to reduce the number of connections between logical units. This can achieved by distributing and assigning the topological railway objects to certain logical units. © 2024 Budapest University of Technology and Economics. All rights reserved.

关键词： Distributed parameter control systems

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Robust Trajectory Tracking control of a Differentially Flat Overhead Crane Using Sliding Mode

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica electrical engineering and computer science 2024年第2期68卷 213-221页

作者： Finta, Barnabás Kiss, Bálint Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics University Műegyetem rkp. 3. BudapestH-1111 Hungary

The control of overhead cranes is a benchmark problem, since it is an underactuated mechanism and its mathematical model is nonlinear. During operation the mass of the load is unknown, representing an uncertainty in the inertial parameters, which requires robustness of the controlled system. Our paper proposes a novel robust control method, that combines the differentially flat property of the dynamics with the robustness of the sliding mode control. The sliding surface is constructed to ensure the tracking of the configuration variables whose accelerations is calculated using the flatness property of the dynamic model. This formulation also allows achieving the matching conditions of the parameter uncertainties. Considering a simplified overhead crane model where the load motion is restricted in a vertical plane, two sliding surfaces are defined for the rope angle and rope length, since the cart position can be calculated from the previous two. The suggested control method is successfully validated in simulations as well as using a reduced-size overhead crane. For the real crane, the rope angle was estimated by utilizing the dynamical model, which uses the estimated cart acceleration. © 2024 Budapest University of Technology and Economics. All rights reserved.

关键词： Acceleration

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Correction of Time-varying PMU Phase Angle Deviation with Unknown Transmission Line Parameters

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CSEE Journal of Power and Energy Systems 2023年第1期9卷 315-325页

作者： Ancheng Xue He Kong Feiyang Xu Junbo Zhao Naichao Chang Joe H.Chow Haiyan Hong State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China Department of Electrical and Computer Engineering University of ConnecticutStorrs06268USA National Electric Power Dispatching and Control Center Beijing 100031China Department of Electrical Computerand Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNY 12180USA

Phasor measurement units(PMUs)provide useful data for real-time monitoring of the smart ***,there may be time-varying deviation in phase angle differences(PADs)between both ends of the transmission line(TL),which may deteriorate application performance based on *** address that,this paper proposes two robust methods of correcting time-varying PAD deviation with unknown parameters of TL(ParTL).First,the phenomena of time-varying PAD deviation observed from field PMU data are *** general formulations for PAD estimation are then *** simplify the formulations,estimation of PADs is converted into the optimal problem with a single ParTL as the variable,yielding a linear estimation of *** latter is used by second-order Taylor series expansion to estimate PADs *** reduce the impact of possible abnormal amplitude data in field data,the IGG(Institute of Geodesy&Geophysics,Chinese Academy of Sciences)weighting function is *** using both simulated and field data verify the effectiveness and robustness of the proposed methods.

关键词： Correction line parameters parameter identification phasor measurement time-varying phase angle difference deviation

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Optimized Deep Learning Approach for Efficient Diabetic Retinopathy Classification Combining VGG16-CNN

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computers, Materials & Continua 2023年第11期77卷 1855-1872页

作者： Heba M.El-Hoseny Heba F.Elsepae Wael A.Mohamed Ayman S.Selmy Department of Computer Science the Higher Future Institute for Specialized Technological StudiesObour11828Egypt Department of Electrical Engineering Benha Faculty of EngineeringBenha UniversityBenha13511Egypt

Diabetic retinopathy is a critical eye condition that,if not treated,can lead to vision *** methods of diagnosing and treating the disease are time-consuming and ***,machine learning and deep transfer learning(DTL)techniques have shown promise in medical applications,including detecting,classifying,and segmenting diabetic *** advanced techniques offer higher accuracy and *** Diagnosis(CAD)is crucial in speeding up classification and providing accurate disease ***,these technological advancements hold great potential for improving the management of diabetic *** study’s objective was to differentiate between different classes of diabetes and verify the model’s capability to distinguish between these *** robustness of the model was evaluated using other metrics such as accuracy(ACC),precision(PRE),recall(REC),and area under the curve(AUC).In this particular study,the researchers utilized data cleansing techniques,transfer learning(TL),and convolutional neural network(CNN)methods to effectively identify and categorize the various diseases associated with diabetic retinopathy(DR).They employed the VGG-16CNN model,incorporating intelligent parameters that enhanced its *** outcomes surpassed the results obtained by the auto enhancement(AE)filter,which had an ACC of over 98%.The manuscript provides visual aids such as graphs,tables,and techniques and frameworks to enhance *** study highlights the significance of optimized deep TL in improving the metrics of the classification of the four separate classes of *** manuscript emphasizes the importance of using the VGG16CNN classification technique in this context.

关键词： No diabetic retinopathy(NDR) convolution layers(CNV layers) transfer learning data cleansing convolutional neural networks a visual geometry group(VGG16)

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Diagnosing Faults in Smart Grids using Liquid Time-Constant Network 9

Diagnosing Faults in Smart Grids using Liquid Time-Constant ...

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9th International Conference on engineering and Emerging Technology, ICEET 2023

作者： Samadi, Mahdieh Kharrati, Hamed Badamchizadeh, Mohammad Ali Hassani, Hossein Nikan, Soodeh University of Tabriz Faculty of Electrical and Computer Engineering Tabriz Iran Western University Department of Electrical and Computer Engineering LondonON Canada

ISBN: (纸本)9798350316926

The adoption of smart grids (SGs) has become increasingly popular due to their ability to deliver automated and decentralized energy distribution to consumers. However, in order to ensure the reliable and secure provision of high-quality power from generation sources to end-users, SGs are required to be equipped with efficient diagnostic systems. This paper introduces an effective data-driven approach for diagnosing faults and failures in SGs. In particular, it is proposed to employ Liquid Time-Constant networks for the sake of diagnosing faults in an experimental power transmission system. To evaluate and verify the effectiveness of the proposed diagnostic scheme, a comprehensive study is conducted on a Three-Bus Two-Line experimental setup. Different scenarios by considering various types of faults and failures have been simulated in this case study, and the attained results verify the feasibility and efficiency of the proposed scheme. © 2023 IEEE.

关键词： Smart power grids

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