IEEE Open Journal of Industry Applications最新文献

{"title":"DC Arc Flash Measurements From a 1000 V Valve Regulated Lead Acid Battery System","authors":"Nicolaus Jennings;David Wetz;Rick Langley;Nancy LaFlair;John Heinzel","doi":"10.1109/OJIA.2024.3400208","DOIUrl":"10.1109/OJIA.2024.3400208","url":null,"abstract":"As the Navy moves forward with implementing electrochemical energy sources in their power systems, a need to understand the hazards present to electric workers comes to light. Understanding the effects these sources have on arc flash hazards drives the need to study relevant energy sources that are deployed on naval platforms. A 1000-V valve regulated lead acid (VRLA) battery system presents the greatest need to study as incident energy models can suggest dramatic personal protective equipment (PPE) especially with the inclusion of scale factors. As a part of a collaborative effort between the Electric Power Research Institute (EPRI) and the University of Texas at Arlington (UTA) arc flash studies of VRLA battery systems at voltages as high as 936 V have been performed. Findings show that below 800 V, the battery sourced incident energy as high as 0.26 cal/cm\u0000²\u0000. Above 800 V, incident energy surpassed 1.2 cal/cm\u0000²\u0000 and approached category 1 PPE (4 cal/cm\u0000²\u0000). A model derived from this work is used to emphasize the impact enclosure based scale factors have on incident energy estimates. This work has also compared relevant dc incident energy models to the measured incident energy sourced from this battery system.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"168-176"},"PeriodicalIF":0.0,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10529540","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bidirectional Hybrid DC Circuit Breaker With Zero Voltage and Current Switching for Radar Power System","authors":"Nandakumar Saminathan;Aditya P;Satish Naik Banavath;Alessandro Lidozzi;Marco Di Benedetto;Vengadarajan A","doi":"10.1109/OJIA.2024.3399603","DOIUrl":"10.1109/OJIA.2024.3399603","url":null,"abstract":"This article proposes a novel zero-voltage switching (ZVS) and zero-current switching (ZCS)-based hybrid dc circuit breaker for a radar power system. Long-range radars demand huge power, in the order of hundreds of kW. Radar's phased array antenna houses a large number of electronic devices and works primarily on a dc power supply. Typically, military systems are required to have the highest operational reliability, as a result, electrical system protection plays a crucial role. A high power 310 V dc electrical power grid in radar carries hundreds of amperes of current under nominal operating conditions, results in significant fault current due to very low impedance, and demands a very fast fault interruption device. This article proposes and demonstrates the complete operation of a hybrid dc circuit breaker topology for radar applications. The proposed dc circuit breaker employs a mechanical switch that carries the entire current during the nominal operating conditions, and a power electronic module (PEM) connected in parallel helps in diverting the fault current from the main path. Fault current transfers to the PEM branch in a fraction of a second (5 \u0000<inline-formula><tex-math>$mu s$</tex-math></inline-formula>\u0000), which ensures faster load-side isolation. During the fault interruption process, mechanical switch contact opening experiences both ZVS and ZCS features, resulting in arcless operation, and also helps in faster contact separation. The ZVS and ZCS features greatly improve the reliability of the mechanical switch. The proposed concept does not involve any capacitors or corresponding precharging circuits for the ZVS/ZCS features. The proposed dc circuit breaker is analyzed theoretically, and also by simulations in LTspice. Additionally, an experimental prototype with a dc system rating of 310 V–10 A is developed to experimentally validate the performance of the proposed breaker topology. The article also presents a detailed design and comparative analysis, along with a discussion on the limitations of the proposed dc circuit breaker, and the scope for improvements.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"224-234"},"PeriodicalIF":0.0,"publicationDate":"2024-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10528799","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust Control of Synchronous Reluctance Motor Based on Automatic Disturbance Rejection","authors":"Angelo Accetta;Maurizio Cirrincione;Filippo D'Ippolito;Marcello Pucci;Antonino Sferlazza","doi":"10.1109/OJIA.2024.3399009","DOIUrl":"10.1109/OJIA.2024.3399009","url":null,"abstract":"This article proposes the theoretical development and experimental application of the active disturbance rejection control (ADRC) to synchronous reluctance motor (SynRM) drives. The ADRC is a robust adaptive extension of the input-output feedback linearization control (FLC). It performs the exact linearization of the SynRM model by a suitable nonlinear transformation of the state based on the online estimation of the corrective term by the so-called extended state observers (ESO). Consequently, any unmodeled dynamics or uncertainty of the parameters are properly addressed. The control strategy has been verified successfully both in numerical simulations and experimentally on a suitably developed test set-up that provides the ADRC robustness versus parameters variations which cannot be obtained with other model-based nonlinear control techniques (e.g., FLC). Simulation results show the capability of the ADRC to maintain its dynamic performance, even in the presence of quick variations of the SynRM dynamic inductances. Experimental results confirm the robustness of the ADRC versus any model parameter uncertainty. The proposed ADRC has been experimentally compared with a previously developed FLC, in both a tuned and detuned working configuration, with the classic rotor oriented control, and with a finite state model predictive control (MPC), where speed control is integrated into the MPC. Experimental results show far better robustness versus any parameter variation.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"209-223"},"PeriodicalIF":0.0,"publicationDate":"2024-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10526420","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable AI for Industry 5.0: Vision, Architecture, and Potential Directions","authors":"Chandan Trivedi;Pronaya Bhattacharya;Vivek Kumar Prasad;Viraj Patel;Arunendra Singh;Sudeep Tanwar;Ravi Sharma;Srinivas Aluvala;Giovanni Pau;Gulshan Sharma","doi":"10.1109/OJIA.2024.3399057","DOIUrl":"10.1109/OJIA.2024.3399057","url":null,"abstract":"The Industrial Revolution has shifted toward Industry 5.0, reinventing the Industry 4.0 operational process by introducing human elements into critical decision processes. Industry 5.0 would present massive customization via transformative technologies, such as cyber-physical systems (CPSs), artificial intelligence (AI), and big data analytics. In Industry 5.0, the AI models must be transparent, valid, and interpretable. AI models employ machine learning and deep learning mechanisms to make the industrial process autonomous, reduce downtime, and improve operational and maintenance costs. However, the models require explainability in the learning process. Thus, explainable AI (EXAI) adds interpretability and improves the diagnosis of critical industrial processes, which augments the machine-to-human explanations and vice versa. Recent surveys of EXAI in industrial applications are mostly oriented toward EXAI models, the underlying assumptions. Still, fewer studies are conducted toward a holistic integration of EXAI with human-centric processes that drives the Industry 5.0 applicative verticals. Thus, to address the gap, we propose a first-of-its-kind survey that systematically untangles EXAI integration and its potential in Industry 5.0 applications. First, we present the background of EXAI in Industry 5.0 and CPSs and a reference EXAI-based Industry 5.0 architecture with insights into large language models. Then, based on the research questions, a solution taxonomy of EXAI in Industry 5.0 is presented, which is ably supported by applicative use cases (cloud, digital twins, smart grids, augmented reality, and unmanned aerial vehicles). Finally, a case study of EXAI in manufacturing cost assessment is discussed, followed by open issues and future directions. The survey is designed to extend novel prototypes and designs to realize EXAI-based real-time Industry 5.0 applications.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"177-208"},"PeriodicalIF":0.0,"publicationDate":"2024-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10526434","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Techniques to Predict Voltage Unbalance in a Power Transmission System","authors":"Jonathan D. Boyd;Donald R. Reising;Anthony M. Murphy;Justin D. Kuhlers;C. Michael McAmis;James B. Rossman","doi":"10.1109/OJIA.2024.3369993","DOIUrl":"10.1109/OJIA.2024.3369993","url":null,"abstract":"Voltage unbalance is a growing issue that, among other things, can impact three-phase motor and drive loads, result in nuisance tripping of generation units and capacitor banks, and prevent optimization of conservative voltage regulation strategies. This difference between the three phases of voltage delivered to customers can damage the equipment of these customers as well as negatively impact the power system itself. This work presents an approach for predicting voltage unbalance using machine learning. Historical megawatt and megavar data–obtained through a Supervisory Control And Data Acquisition (SCADA) system–are used to train an artificial neural network model as a binary classifier with a portion of the data serving to validate the trained model. Voltage unbalance is predicted at an accuracy above 95% for eight substations within the power utility's extra-high voltage transmission network and over 91% for all 42 substations. The trained model is tested in a manner that would be employed using simulated data generated by state estimation software. This simulated data validates the model's capacity to predict the substation buses that would experience voltage unbalance.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"86-93"},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10448538","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140002408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IEEE Industry Applications Society Information","authors":"","doi":"10.1109/OJIA.2024.3354443","DOIUrl":"https://doi.org/10.1109/OJIA.2024.3354443","url":null,"abstract":"","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10444962","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139976195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current–Voltage Unbalanced Distribution AC Optimal Power Flow for Advanced Distribution Management System Applications","authors":"Zahra Soltani;Mojdeh Khorsand;Shanshan Ma","doi":"10.1109/OJIA.2024.3367547","DOIUrl":"10.1109/OJIA.2024.3367547","url":null,"abstract":"Modern distribution systems are changing from passive load serving networks to active load and generation-inclusive networks. Accurate distribution systems modeling is critical for effective distribution system control, operation, and planning. This article proposes novel nonlinear and convex ac optimal power flow (ACOPF) models based on current–voltage (IVACOPF) formulation for an unbalanced distribution system with distributed energy resources (DERs). In the proposed formulation, untransposed distribution lines, shunt elements of distribution lines, distribution transformers, and DERs are modeled. The proposed nonlinear IVACOPF model is linearized and convexified using the Taylor series. The accuracy of the proposed nonlinear and convex IVACOPF approaches for modeling unbalanced distribution systems is compared with OpenDSS and the widely used LinDistFlow method. The proposed accurate convex IVACOPF model has multiple applications for distribution systems management, planning, and operation. Applications of the proposed model on two key parts of advanced distribution management systems (ADMS)—DERs scheduling and state estimation—are presented in this article. The proposed models are tested on the distribution feeder of an electric utility in Arizona with 2100 primary nodes and a large number of rooftop photovoltaic units. The results confirm the accuracy and effectiveness of the proposed IVACOPF for both examined ADMS applications.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"155-167"},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10440561","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139945644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental Validation of Innovative Control Concepts for Powertrain Test Beds in Power Hardware-in-the-Loop Configuration","authors":"Dennis Erdogan;Zhang Peng Du;Stefan Jakubek;Franz Holzinger;Christian Mayr;Christoph Hametner","doi":"10.1109/OJIA.2024.3366524","DOIUrl":"10.1109/OJIA.2024.3366524","url":null,"abstract":"Power hardware-in-the-loop (PHIL) testing has become indispensable for the rapid, modular, and cost-saving development of automotive components. This article focuses on PHIL tests composed of entire powertrains that exchange speed and torque signals with vehicle simulations. Previous studies pointed out the importance of promptly following the references from the virtual simulation environment to replicate realistic driving conditions and introduced control strategies to cope with the challenges associated with this setup. However, a comprehensive comparison of the different control strategies has not yet been carried out. To fill this gap, the concepts are first investigated in-depth in simulations and are then, rigorously validated on a state-of-the-art powertrain test bed under highly dynamic driving scenarios, including full-braking. Furthermore, an improvement of existing shaft torque control approaches, which are mainly based on feedforward control, is proposed to better compete with the other methods. The proposed extension shows higher resilience to low accuracy of torque actuators, while the other concepts exhibit greater robustness against time delays. The results from the direct comparisons are summarized and allow the appropriate selection of control strategies for specific use cases.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"128-142"},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10438857","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139956910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytical Delay Evaluation for FPGA-Based Repetitive Controller in AC Variable Frequency Applications","authors":"Alessandro Faro;Alessandro Lidozzi;Marco di Benedetto;Luca Solero;Stefano Bifaretti","doi":"10.1109/OJIA.2024.3366415","DOIUrl":"10.1109/OJIA.2024.3366415","url":null,"abstract":"Repetitive controller provides a very low third harmonic dimension in the quantities under control. It exhibits an inherent issue when operated to track variable frequency references. The article deals with the analysis of the operating conditions when the controller is executed at variable frequency without any resynchronization with respect to the pulsewidth modulation carrier, which is the most common mode of operation. The delays introduced are then evaluated analytically concerning the sampling and output frequency that must be tracked. The proposed analysis allows obtaining the maximum delay affecting the control chain, which was introduced by the repetitive control desynched operation. The knowledge of the delay introduced in the control loops is at the basis of any control tuning procedure and gains selection, even when adaptive control strategies are used.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"117-127"},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10437987","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139945579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Command Injection Attacks in Smart Grids: A Survey","authors":"Muhammad Usama;Muhammad Naveed Aman","doi":"10.1109/OJIA.2024.3365576","DOIUrl":"10.1109/OJIA.2024.3365576","url":null,"abstract":"Cybersecurity is important in the realization of various smart grid technologies. Several studies have been conducted to discuss different types of cyberattacks and provide their countermeasures. The false command injection attack (FCIA) is considered one of the most critical attacks that have been studied. Various techniques have been proposed in the literature to detect FCIAs on different components of smart grids. The predominant focus of current surveys lies on FCIAs and detection techniques for such attacks. This article presents a survey of existing works on FCIAs and classifies FCIAs in smart grids according to the targeted component. The impacts of FCIAs on smart grids are also discussed. Subsequently, this article provides an extensive review of detection studies, categorizing them based on the type of detection technique employed.","PeriodicalId":100629,"journal":{"name":"IEEE Open Journal of Industry Applications","volume":"5 ","pages":"75-85"},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10433776","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139945611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}