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SOC Estimation of an LFP Battery using Extended Kalman Filter with Extracted Prameter

Transactions of the Korean Institute of electrical Engineers 2023年第11期72卷 1372-1379页

作者： Lim, Hee-Sung Lee, Sang-Hyuk Lee, Kyo-Beum Dept. of Electrical and Computer Engineering Ajou University Korea Republic of Dept. of Fuelcell System Perfomance Development K-Fuelcell Korea Republic of Dept. of Research Center IFTech Korea Republic of

This paper proposes a method to estimate SOC(State of charge) by extracting parameters for each circuit element of an LFP(LiFePO4) battery equivalent circuit model and combining the Extended Kalman Filter and coulomb counting method. A lithium battery cell is generally modeled using an equivalent circuit, and parameters for each circuit element of the battery model can be extracted using pulse charging and discharging curves. Those curves are collected experimentally to characterize battery performance at various operating points. Numerical optimization algorithms are repeatedly performed in computer simulation to minimize errors in battery models and experimental data. SOC is estimated using extracted parameters and the Extended Kalman Filter algorithm. Copyright ©The Korean Institute of electrical Engineers.

关键词： Extended Kalman filters

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Ancillary Services Prioritization in Inverters with Virtual Synchronous Generator Functionalities

Ancillary Services Prioritization in Inverters with Virtual ...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Tekki, Eleni Hadjidemetriou, Lenos Barragan-Villarejo, Manuel Matas-Diaz, Francisco Jesus Maza-Ortega, Jose Maria Gomez-Explosito, Antonio Polycarpou, Marios M. KIOS Research Innovation Center of Excellence Dept. of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Dept. of Electrical Engineering Universidad de Sevilla Sevilla Spain

ISBN: (纸本)9798350396782

The massive integration of renewable energy reduces the overall inertia of the grid deteriorating the system stability. Virtual synchronous generator approaches have been recently introduced in the inverter controller to enable distributed resources to improve the power system stability through frequency support. At the same time, ancillary services can be provided by the inverters to compensate reactive power flow and loading asymmetries, improving in this way the efficiency and utilization of distribution grids. This work proposes a novel multifunctional inverter where the virtual synchronous generator mode for frequency support is combined with ancillary services provision capabilities for phase balancing and reactive power compensation. In this context, an algorithm is proposed to prioritize online the provision of each functionality in order to guarantee the overcurrent limits of the inverter under any operating conditions. The inverter performance is validated through simulations, indicating that it can be reliably used to improve the power system operation. © 2023 IEEE.

关键词： Ancillary services inverter phase balancing reactive compensation virtual synchronous generator

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State estimation of LiFePO4 battery using a Linear Regression Analysis

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Transactions of the Korean Institute of electrical Engineers 2022年第2期71卷 366-372页

作者： Lim, Hee-Sung Yun, Jin-Shik Lee, Kyo-Beum Dept. of IT Convergence Engineering Ajou University Korea Republic of Dept. of Battery Research Center CM PARTNER Korea Republic of Dept. of Electrical and Computer Engineering Ajou University Korea Republic of

This paper proposes a SOH Estimation of LiFePO4 battery management systems using a Linear Regression Analysis. Among the methods of machine learning, supervised learning learns the relationship between the input data(battery characteristic) and the output data(failure data) to find a model that is expressed as a rule or function. Unsupervised learning performs failure diagnosis and prediction by discovering patterns inherent in changing battery characteristics data during use. The algorithm estimates DCIR according to the input parameters using linear regression analysis of supervised learning, and clustering of data to confirm association with failure causes. The validity of the proposed machine learning algorithm is verified by experiment. Copyright © 2021 The Korean Institute of electrical Engineers.

关键词： Lithium compounds

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An Improved Fault Current Bypass-Based DC Solid-State Circuit Breaker for DC Microgrid Applications

An Improved Fault Current Bypass-Based DC Solid-State Circui...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Zhou, Jiale Mu, Qiang Sun, Xiuhu Pang, Tiancan Wang, Yao Zhao, Tiefu University of North Carolina at Charlotte Dept. of Electrical and Computer Engineering CharlotteNC United States Hebei University of Technology School of Electrical Engineering Tianjin China Research Center Dept. of Ece CharlotteNC United States

ISBN: (纸本)9798350376067

Solid-state circuit breakers (SSCBs) have gained traction in the protection field due to their fast fault interruption and arcless operation. This paper proposes an improved fault current bypass-based DC SSCB for DC microgrids. The proposed topology features fast fault isolation and cost-effectiveness. Initially, the superiority of the proposed topology is analyzed in comparison to two prior-art fault current bypass-based topologies. Next, the operating principles and key design considerations are presented for the proposed topology. Finally, the effectiveness of the proposed topology is verified through both simulation and experimental results. The proposed topology is the most cost-effective solution, with 99.82% efficiency and a 15% cost reduction for power semiconductor selection compared to the other two traditional fault current bypass-based topologies. Experimental results from a 400 VDC/80 A prototype demonstrate the feasibility of the proposed topology, showing that the clamping voltage of the metal oxide varistor (MOV) is lower than the DC voltage. © 2024 IEEE.

关键词： Short circuit currents

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Smart Agent-Based Direct Load Control of Air Conditioner Populations in Demand Side Management

Smart Agent-Based Direct Load Control of Air Conditioner Pop...

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2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023

作者： Yazdkhastil, Pegah Diduch, Chris P. University of New Brunswick Smart Grid Research Center Dept. of of Electrical & Computer Engineering FrederictonNB Canada

ISBN: (纸本)9798350347074

The rapid fluctuations of renewable resources, such as wind and solar, pose challenges to the reliability of the grid and make it difficult to integrate them into existing power systems. To address this uncertainty and variability in generation, direct load control is a promising method for managing the demand side. Thermostatically controlled appliances, such as air conditioners, can play a significant role in this process. However, to implement direct load control, the system operator needs a reliable estimate of the load's magnitude and the degree to which it can be shifted. This paper introduces a smart-agent architecture that utilizes a mathematical model of the aggregated power consumption of the load to forecast its behavior, even in the presence of changes imposed by the controller. To evaluate the system's performance, a numerical simulator was developed. It was observed that the system can adapt to changes in the system, retrain itself, and develop a new mathematical model to improve its prediction of the aggregated power consumption. © 2023 IEEE.

关键词： Demand side management

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A Study on Optimal Scheduling Model of Digital Twin-based Energy Storage System using Artificial Intelligence

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Transactions of the Korean Institute of electrical Engineers 2022年第6期71卷 819-825页

作者： Park, Hyang-A Byeon, Gil-Sung Kim, Jong-Yul Kim, Sung-Shin Dept. of Electrical and Computer Engineering Pusan National University Korea Republic of Energy Platform Research Center Korea Electrotechnology Research Institute Korea Republic of

Recently, due to the digitalization of power systems, the convergence technology of power systems and ICT has become important, and with the development of operational technologies, the importance of intelligent energy management is increasing. The importance of energy management through intelligent operating technology is emerging. In this paper, a digital twin model simulated by empirical simulation was constructed using the empirical ESS measurement data information collected from the power system. An optimal operation plan model for ESS was established by simulating the state and environment of the system in the virtual space of the digital twin similar to the actual system. It aims to improve the stable operation and efficiency of ESS through rapid situational awareness and correct decision-making by applying a data-based machine learning model rather than an existing optimization-based operation model. Copyright © The Korean Institute of electrical Engineers

关键词： Energy storage

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Slotted ALOHA with Code Combining for IoT Networks 3

Slotted ALOHA with Code Combining for IoT Networks

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3rd IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2023

作者： Tyrovolas, Dimitrios Chrysologou, Athanasios Chondrogiannis, Georgios Tegos, Sotiris Mekikis, Prodromos-Vasileios Diamantoulakis, Panagiotis Ioannidis, Sotiris Liaskos, Christos Chatzidiamantis, Nestor Karagiannidis, George Aristotle University of Thessaloniki Dept. of Electrical and Computer Engineering Thessaloniki Greece Technical University of Chania Dept. of Electrical and Computer Engineering Chania Greece University of Ioannina Computer Science Engineering Department Ioannina Greece Cyber Security Systems and Applied Ai Research Center Lebanon

ISBN: (纸本)9798350333732

Internet of Things (IoT) networks are expected to be a key enabler technology for smart cities, due to their ability to offer real-time monitoring. In this work, we propose a novel medium access control (MAC) protocol, inspired by the synergy of slotted ALOHA and hybrid automatic repeat request with code combining (HARQ-CC), termed as code combining slotted ALOHA (CCSA), to improve the performance of IoT networks with multiple randomly deployed sensors. Specifically, we provide analytical closed-form expressions for the network's outage probability as well as for its average throughput when CCSA is applied. Finally, we provide simulation results that reveal the authenticity of the derived expressions and reveal the capabilities of HARQ-CC to significantly improve the network's performance when the sensors' access is based on a random access scheme. © 2023 IEEE.

关键词： Wireless sensor networks

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The Effect of Pulse Width on Nanosecond Guided Streamer Breakdown

The Effect of Pulse Width on Nanosecond Guided Streamer Brea...

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2023 IEEE Pulsed Power Conference, PPC 2023

作者： Rahman, Md Ziaur Oshin, Edwin A. Jiang, Chunqi Old Dominion University Frank Reidy Research Center for Bioelectrics Dept. of Electrical and Computer Engineering NorfolkVA United States

ISBN: (纸本)9798350332339

Understanding the initiation and development of guided streamers are important for effectively applying these repeatable, transient discharges for various fields. This study compares the streamer initiation and breakdown for positive helium guided streamers powered by 10-ns, 35-ns, and 200-ns voltage pulses using a hollow needle-to-plate electrode configuration at atmospheric pressure. The streamer initiation and breakdown (streamer-to-spark transition) voltage as functions of the interelectrode gap distance are determined based on voltage-current measurements and high-speed spectroscopy. The breakdown voltage for a repetitively pulsed streamer is compared with a single-shot discharge. The dependence of the pulse repetition frequency and pulse width on streamer breakdown are investigated. It is found that the shorter voltage pulses results in higher overvoltage breakdown. In addition, the discharge mode is assessed with the pulsed voltage and current as well as the rotational temperature of the 2nd positive system of N2,. © 2023 IEEE.

关键词： Atmospheric pressure

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Wind Energy Forecasts with Supervised Machine Learning Techniques

Wind Energy Forecasts with Supervised Machine Learning Techn...

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International Conference on Green Energy, Computing and Intelligent Technology 2024, GEn-CITy 2024

作者： Hussain, Mariam Ahammad, Kawsar Noor, Moshiur R. Sharmin, Nusrat Shafiul, Sumayea B. Islam, Shakarul Research of Integrated Green and Holistic Training Center Bogura Bangladesh Dept. of Electrical and Electronic Engineering Eastern University Dhaka Bangladesh Dept. of Computer Science and Engineering University of Science and Technology Chittagong Bangladesh Dept. of Epidemiology Bangladesh University of Health Sciences Dhaka Bangladesh

ISBN: (纸本)9781837242689

United Nations set clean and affordable energy (7th) sustainable development goals. Among renewables, wind energy requires frequent observations. Due to limited finance in developing countries like Bangladesh, accurate and wide observations are one of the major challenges in operation and maintenance for energy harvests. Thus, this paper developed energy forecast models with supervised machine learning (ML) algorithms: support vector regressor (SVR) and random forest (RF) and compared with linear regression (LR) model. With global wind atlas (GWA) datasets (heights: 10 to 200m), training and testing performed with SVR, RF, and LR models. Model performances evaluated with Pearson correlation, coefficient of determinations, mean absolute percentage (MAPE), and root mean square errors (RMSE). During training and testing, ML estimations outperformed LR model as MAPE indicated ≤15% and ≥50% respectively for global and local-scale datasets. For an agricultural land with limited observations, ML predictions were performed for Bogura city with NASA-POWER dataset representing an MAPE of 4.84% (SVR) and 0.91% (RF). At Bogura on average, the final output showed annual energy production of 189 Kilowatt where probability for wind speeds about 70% (3 to 6 m/s at 50m). In conclusion, ML model accuracy is efficient for successful energy operations in Bangladesh and other developing countries with limited observations. © The Institution of engineering & Technology 2024.

关键词： Wind forecasting

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Localization of Dengue Virus Likelihood Using Image Processing Technique 6

Localization of Dengue Virus Likelihood Using Image Processi...

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6th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2024

作者： Hosen, Md. Mahbub Islam, Md. Rahatul Tabassum, Faria Tonni, Syeda Thamina Noor, Malik Mohammad Nafiur Rahman, Shahid Northern University of Bangladesh Dept. of Computer Science and Engineering Dhaka Bangladesh Kyushu Institute of Technology Dept. of Human Intelligence Systems Wakamatsu Kitakyushu Japan Bangladesh University of Engineering and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Bangladesh Advance Robotics Research Center Human Intelligence Lab Dhaka Bangladesh Canadian University of Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350306613

The Aedes mosquito, found in tropical areas, transmits, and causes dengue fever. The spread of the dengue fever virus from an infected Aedes mosquito bite typically takes between three and fifteen days to manifest itself clinically as dengue fever symptoms. Early and automated detection of this illness will reduce the occurrence of outbreaks and facilitate the digitization of the system. Our primary objective is to identify regions at high risk for dengue fever using limited image data through the utilization of sophisticated machine learning and image processing methods. This work showcases the application of transfer learning algorithms for the timely identification of regions at risk for dengue mosquito infestation, particularly in situations where obtaining early data on dengue outbreaks is challenging. The experiments included images of 2150 dengue-positive data sets and 1440 dengue-negative data sets. We used AI and image classifiers Yolo V4 Tin, Tensor Flow, Google Colab, etc. for the training data set, and the system makes predictions with a 99.63% accuracy rate. Our system has some unique attributes;it not only detects the percentage of dengue probability but also the specific dengue-prone location on the submitted image. © 2024 IEEE.

关键词： aedes mosquito dengue-prone image processing yolo v4 tiny

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