A proximal subgradient algorithm with extrapolation for structured nonconvex nonsmooth problems
- Authors: Pham, Tan , Dao, Minh , Shah, Rakibuzzaman , Sultanova, Nargiz , Li, Guoyin , Islam, Syed
- Date: 2023
- Type: Text , Journal article
- Relation: Numerical Algorithms Vol. 94, no. 4 (2023), p. 1763-1795
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- Description: In this paper, we consider a class of structured nonconvex nonsmooth optimization problems, in which the objective function is formed by the sum of a possibly nonsmooth nonconvex function and a differentiable function with Lipschitz continuous gradient, subtracted by a weakly convex function. This general framework allows us to tackle problems involving nonconvex loss functions and problems with specific nonconvex constraints, and it has many applications such as signal recovery, compressed sensing, and optimal power flow distribution. We develop a proximal subgradient algorithm with extrapolation for solving these problems with guaranteed subsequential convergence to a stationary point. The convergence of the whole sequence generated by our algorithm is also established under the widely used Kurdyka–Łojasiewicz property. To illustrate the promising numerical performance of the proposed algorithm, we conduct numerical experiments on two important nonconvex models. These include a compressed sensing problem with a nonconvex regularization and an optimal power flow problem with distributed energy resources. © 2023, The Author(s).
Domestic load management with coordinated photovoltaics, battery storage and electric vehicle operation
- Authors: Das, Narottam , Haque, Akramul , Zaman, Hasneen , Morsalin, Sayidul , Islam, Syed
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 12075-12087
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- Description: Coordinated power demand management at residential or domestic levels allows energy participants to efficiently manage load profiles, increase energy efficiency and reduce operational cost. In this paper, a hierarchical coordination framework to optimally manage domestic load using photovoltaic (PV) units, battery-energy-storage-systems (BESs) and electric vehicles (EVs) is presented. The bidirectional power flow of EV with vehicle to grid (V2G) operation manages real-time domestic load profile and takes appropriate coordinated action using its controller when necessary. The proposed system has been applied to a real power distribution network and tested with real load patterns and load dynamics. This also includes various test scenarios and prosumer's preferences e.g., with or without EVs, number of EV owners, number of households, and prosumer's daily activities. This is a combined hybrid system for hierarchical coordination that consists of PV units, BES systems and EVs. The system performance was analyzed with different commercial EV types with charging/ discharging constraints and the result shows that the domestic load demand on the distribution grid during the peak period has been reduced significantly. In the end, this proposed system's performance was compared with the prediction-based test techniques and the financial benefits were estimated. © 2013 IEEE.
Forced oscillation management in a microgrid with distributed converter-based resources using hierarchical deep-learning neural network
- Authors: Surinkaew, Tossaporn , Emami, Kianoush , Shah, Rakibuzzaman , Islam, Md Rabiul , Islam, Syed
- Date: 2023
- Type: Text , Journal article
- Relation: Electric Power Systems Research Vol. 222, no. (2023), p.
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- Description: In future microgrids (MGs), increasing penetration of distributed converter-based resources (DCRs) has inevitably resulted in the problem of inertia scarcity. The interaction, combination, and/or resonance among converter control loops of DCRs, forced inputs, grid parameters, parasitic elements in networks, and system dominant modes can lead to major forced oscillations (FOs). Previous research works mostly focused the problem of FOs on large-scale power systems. However, the effects of FOs in MGs may be more severe than large-scale power systems due to the lower system inertia. With different characteristics of each DCR, conventional FO management methods applied in large-scale power systems may be ineffective. In this paper, a unified AI-framework named hierarchical deep-learning neural network (HiDeNN) is proposed to effectively handle the FOs in a MG with DCRs. To properly managing the FOs, the HiDeNN is divided into three levels for FO detection, identification, and mitigation, respectively. By considering big data produced from DCRs, the HiDeNN is used to solve complicated FO management problems with a low computational demand. By comparison to conventional FO management methods, performances of the proposed HiDeNN are verified in the modified IEEE 13-node feeder with DCRs under various operating points and FO conditions. © 2023
Numerical model of cloud-to-ground lightning for pyroCb thunderstorms
- Authors: Barman, Surajit , Shah, Rakibuzzaman , Islam, Syed , Kumar, Apurv
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 16, no. (2023), p. 8689-8701
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- Description: This paper demonstrates a 2-D numerical model to represent two conceptual pyrocumulonimbus (pyroCb) thundercloud structures: i) tilted dipole and ii) tripole structure with enhanced lower positive charge layer, which are hypothesized to explain the occurrence of lightning flashes in pyroCb storms created from severe wildfire events. The presented model considers more realistic thundercloud charge structures to investigate the electrical states and determine surface charge density for identifying potential lightning strike areas on Earth. Simulation results on dipole structure-based pyroCb thunderclouds confirm that the wind-shear extension of its upper positive (UP) charge layer by 2-8 km reduces the electric field and indicates the initiation of negative surface charge density around the earth periphery underneath the anvil cloud. These corresponding lateral extensions have confined the probable striking zone of-CG and +CG lightning within 0-23.5 km and 23.5-30 km in the simulation domain. In contrast, pyroCb thundercloud possessing the tripole structure with enhanced lower positive charge develops a negative electric field at the cloud's bottom part to block the progression of downward negative leader and cause the surface charge density beneath the thundercloud to become negative, which would lead to the formation of +CG flashes. Later, a parametric study is conducted assuming a positive linear correlation between the charge density and aerosol concentration to examine the effect of high aerosol concentration on surface charge density in both pyroCb thunderclouds. The proposed model can be expanded into 3-D to simulate lightning leader movement, aiding wildfire risk management. © 2008-2012 IEEE.
Reverse blocking over current busbar protection scheme based on IEC 61850 architecture
- Authors: Kumar, Shantanu , Abu-Siada, Ahmed , Das, Narottam , Islam, Syed
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Transactions on Industry Applications Vol. 59, no. 2 (2023), p. 2225-2233
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- Description: Substation Automation System (SAS) is currently in a matured state of technology that shall facilitate transformational changes from conventional protection scheme. IEC 61850 protocol is considered as the crux of digital SAS due to its multifunction features that include seamless communication, ability to integrate various intelligent electronic devices, potential for improved real-time condition monitoring, reliable protection, and control of critical electrical assets. Because the application of IEC 61850 in SAS is relatively new and has not fully implemented in many substations yet, further feasibility studies using multivendor equipment to assess its performance under different operating conditions is imperative. In this article, a practical reliable and efficient reverse blocking over current bus bar protection scheme based on IEC 61850 is implemented and tested. Also, a comparison of digital SAS and conventional protection scheme is presented to highlight the superiority of the former one. Experimental results attest the reliability and effectiveness of the proposed digital protection scheme along with the accuracy and security of transmitting data packets using sampled values and generic objective-oriented substation event communication protocols adopted by IEC 61850. © 2022 IEEE.
Review of the legacy and future of IEC 61850 protocols encompassing substation automation system
- Authors: Kumar, Shantanu , Abu-Siada, Ahmed , Das, Narottam , Islam, Syed
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Electronics (Switzerland) Vol. 12, no. 15 (2023), p.
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- Description: Communication protocols play a pivotal role in the substation automation system as they carry critical information related to asset control, automation, protection, and monitoring. Substation legacy protocols run the assets’ bulk data on multiple wires over long distances. These data packets pass through multiple nodes, which makes the identification of the location and type of various malfunctions a challenging and time-consuming task. As downtime of substations is of high importance from a regulatory and compliance point of view, utilities are motivated to revisit the overall scheme and redesign a new system that features flexibility, adaptability, interoperability, and high accuracy. This paper presents a comprehensive review of various legacy protocols and highlights the path forward for a new protocol laid down as per the IEC 61850 standard. The IEC 61850 protocol is expected to be user-friendly, employ fiber optics instead of conventional copper wires, facilitate the application of non-conventional instrument transformers, and connect Ethernet wires to multiple intelligent electronic devices. However, deployment of smart protocols in future substations is not a straightforward process as it requires careful planning, shutdown and foreseeable issues related to interface with proprietary vendor equipment. Along with the technical issues of communication, future smart protocols call for advanced personnel and engineering skills to embrace the new technology. © 2023 by the authors.
False data detection in a clustered smart grid using unscented Kalman filter
- Authors: Rashed, Muhammad , Kamruzzaman, Joarder , Gondal, Iqbal , Islam, Syed
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Access Vol. 10, no. (2022), p. 78548-78556
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- Description: The smart grid accessibility over the Internet of Things (IoT) is becoming attractive to electrical grid operators as it brings considerable operational and cost efficiencies. However, this in return creates significant cyber security challenges, such as fortification of state estimation data such as state variables against false data injection attacks (FDIAs). In this paper, a clustered partitioning state estimation (CPSE) technique is proposed to detect FDIA by using static state estimation, namely, weighted least square (WLS) method in conjunction with dynamic state estimation using minimum variance unscented Kalman filter (MV-UKF) which improves the accuracy of state estimation. The estimates acquired from the MV-UKF do not deviate like WLS as these are purely based on the previous iteration saved in the transition matrix. The deviation between the corresponding estimations of WLS and MV-UKF are utilised to partition the smart grid into smaller sub-systems to detect FDIA and then identify its location. To validate the proposed detection technique, FIDAs are injected into IEEE 14-bus, IEEE 30-bus, IEEE 118-bus, and IEEE 300-bus distribution feeder using MATPOWER simulation platform. Our results clearly demonstrate that the proposed technique can locate the attack area efficiently compared to other techniques such as chi square. © 2013 IEEE.
Overview of power converter control in microgrids - challenges, advances, and future trends
- Authors: Hu, Jiefeng , Shan, Yinghao , Cheng, Ka , Islam, Syed
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Transactions on Power Electronics Vol. 37, no. 8 (2022), p. 9907-9922
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- Description: As the electronic interfaces between distributed energy resources and the electrical network, power converters play a vital role in voltage stabilization and power conversion. So far, various power converter control methods have been developed. Now it is urgently needed to compare and understand these approaches to support the smart microgrid pyramid. This article provides an overview of the state-of-the-art of parallel power converter control in microgrid applications. The most important control schemes to address existing challenges, including concentrated control, master-slave control, droop mechanism, virtual synchronous generators, virtual oscillator control, distributed cooperative control, and model predictive control, are highlighted and analyzed in detail. In addition, the hierarchical control structure, as well as future trends, are reviewed and discussed. © 1986-2012 IEEE.
A unified model predictive voltage and current control for microgrids with distributed fuzzy cooperative secondary control
- Authors: Shan, Yinghao , Hu, Jiefeng , Chan, Ka , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Transactions on Industrial Informatics Vol. 17, no. 12 (DEC 2021), p. 8024-8034
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- Description: A microgrid formed by a cluster of parallel distributed generation (DG) units is capable of operating in either islanded mode or grid-connected mode. Traditionally, by using model predictive control algorithms, these two operation modes can be achieved with two separate and different cost functions, which brings in control complexity and hence, compromises system reliability. In this article, a unified model predictive voltage and current control strategy is proposed for both islanded and grid-connected operations and their smooth transition. The cost function is kept unified with voltage and current taken into account without altering the control architecture. It can be used for high-quality voltage supply at the primary control level and for bidirectional power flow at the tertiary control level. In addition, by only using DGs' own and neighboring information, a distributed fuzzy cooperative algorithm is developed at the secondary layer to mitigate the voltage and frequency deviations inherent from the power droop. The fuzzy controller can optimize the secondary control coefficients for further voltage quality improvement. Comprehensive tests under various scenarios demonstrate the merits of the proposed control strategy over traditional methods.
Assessing trust level of a driverless car using deep learning
- Authors: Karmakar, Gour , Chowdhury, Abdullahi , Das, Rajkumar , Kamruzzaman, Joarder , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Transactions on Intelligent Transportation Systems Vol. 22, no. 7 (2021), p. 4457-4466
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- Description: The increasing adoption of driverless cars already providing a shift to move away from traditional transportation systems to automated ones in many industrial and commercial applications. Recent research has justified that driverless vehicles will considerably reduce traffic congestions, accidents, carbon emissions, and enhance the accessibility of driving to wider cross-section of people and lifestyle choices. However, at present, people's main concerns are about its privacy and security. Since traditional protocol layers based security mechanisms are not so effective for a distributed system, trust value-based security mechanisms, a type of pervasive security, are appearing as popular and promising techniques. A few statistical non-learning based models for measuring the trust level of a driverless are available in the current literature. These are not so effective because of not being able to capture the extremely distributed, dynamic, and complex nature of the traffic systems. To bridge this research gap, in this paper, for the first time, we propose two deep learning-based models that measure the trustworthiness of a driverless car and its major On-Board Unit (OBU) components. The second model also determines its OBU components that were breached during the driving operation. Results produced using real and simulated traffic data demonstrate that our proposed DNN based deep learning models outperform other machine learning models in assessing the trustworthiness of individual car as well as its OBU components. The average precision of detection accuracies for the car, LiDAR, camera, and radar are 0.99, 0.96, 0.81, and 0.83, respectively, which indicates the potential real-life application of our models in assessing the trust level of a driverless car. © 2000-2011 IEEE.
Dissolved gas analysis for power transformers within distributed renewable generation-based systems
- Authors: Cui, Huize , Yang, Liuqing , Zhu, Yuanwei , Li, Shengtao , Abu-Siada, Ahmed , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 28, no. 4 (2021), p. 1349-1356
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- Description: In this paper, a series of laboratory experiments are conducted to investigate the effect of momentary small variations in the transformer operating temperature on the dissolved gas analysis (DGA) measurement. With the increased penetration level of renewable energy sources of intermittent characteristics into electricity grids, operating power transformers are expected to experience frequent temperature variations. Sampling transformer oil during such temperature variation leads to inaccurate diagnosis. Experimental results reveal that gas evolution in transformer oil is greatly affected by the small variations in the operating temperature. Such small variation can be a result of the intermittent generation characteristics of renewable energy sources. Hence, false analysis may be reported if oil is sampled during generation or load fluctuation events. Experimental results are explained through chemical equilibrium constant theory, which indicates that dissolved gases reflect the change in aging rate of the transformer oil-paper insulation system. These results suggest a new paradigm for DGA process through correlating measurements with the transformer operating temperature through the generation and load profiles at the instant of oil sampling. © 1994-2012 IEEE.
Enhanced power extraction from thermoelectric generators considering non-uniform heat distribution
- Authors: Fauzan, Miftah , Muyeen, S. , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: Energy Conversion and Management Vol. 246, no. (2021), p.
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- Description: In this paper, a technique to enhance the performances of the thermoelectric generator under non-uniform heat distribution is developed. A large area of heat source is needed when the thermoelectric generator is used for high power applications such as powering air conditioners, household appliances, and distributed generation systems. Non-uniform heat distribution is a natural phenomenon in large surface of heat source. A model was developed and was validated with a prototype of thermoelectric panel 80 V, 2 A. Results show very good similarities between the model and the prototype outputs under various operating conditions. The error during the tests for the voltage performances was 6.5%, while the current was 1.1%. A method of maximizing power, i.e., developing a specialized maximum power point tracker (MPPT) along with blocking diodes, is proposed to overcome the effects of non-uniform heat distribution. In a typical condition, the output power dropped by 30% when a non-uniform thermal distribution is imposed to the array. The blocking diode can save power by 15%, and the MPPT expands up to 20% power when adopting this method. © 2021
Forced oscillation in power systems with converter controlled-based resources- a survey with case studies
- Authors: Surinkaew, Tossaporn , Emami, Koanoush , Shah, Rakibuzzaman , Islam, Syed , Mithulananthan, N.
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Access Vol. 9, no. (2021), p. 150911-150924
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- Description: In future power systems, conventional synchronous generators will be replaced by converter controlled-based generations (CCGs), i.e., wind and solar generations, and battery energy storage systems. Thus, the paradigm shift in power systems will lead to the inferior system strength and inertia scarcity. Therefore, the problems of forced oscillation (FO) will emerge with new features of the CCGs. The state-of-the-art review in this paper emphasizes previous strategies for FO detection, source identification, and mitigation. Moreover, the effect of FO is investigated in a power system with CCGs. In its conclusion, this paper also highlights important findings and provides suggestions for subsequent research in this important topic of future power systems. © 2013 IEEE.
Interpretation of transformer winding deformation fault by the spectral clustering of FRA signature
- Authors: Zhao, Zhongyong , Tang, Chao , Chen, Yu , Zhou, Qu , Yao, Chenguo , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: International Journal of Electrical Power and Energy Systems Vol. 130, no. (2021), p.
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- Description: Frequency response analysis (FRA) has been accepted as a widely used tool for the power industry. The interpretation of FRA can be achieved by the conventional mathematical indicators-based method, which is mostly used in the past. The newly developing artificial intelligence (AI)-based method also provides an alternative interpretation. However, in most reported AI techniques, the features of FRA signatures are directly input into the AI model to obtain the classification results. Few studies have concentrated on the separability of winding deformation faults. In this context, a spectral clustering algorithm is studied to aid in FRA interpretation. The electrical model simulation and experimental tests are performed. The FRA data processing results verify the feasibility, effectiveness and superiority of the proposed method. © 2021 Elsevier Ltd
Optimal placement of synchronized voltage traveling wave sensors in a radial distribution network
- Authors: Tashakkori, Ali , Abu-Siada, Ahmed , Wolfs, Peter , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Access Vol. 9, no. (2021), p. 65380-65387
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- Description: A transmission line fault generates transient high frequency travelling waves (TWs) that propagate through the entire network. The fault location can be determined by recording the instants at which the incident waves arrive at various points in the network. In single end-based methods, the incident wave arrival time and its subsequent reflections from the fault point are used to identify the fault location. In heavily branched distribution networks, the magnitude of the traveling wave declines rapidly as it passes through multiple junctions that cause reflection and refraction to the signal. Therefore, detecting the first incident wave from a high impedance fault is a significant challenge in the electrical distribution networks, in particular, subsequent reflections from a temporarily fault may not be possible. Therefore, to identify a high impedance or temporary faults in a distribution network with many branches, loads, switching devices and distributed transformers, multiple observers are required to observe the entire network. A fully observable and locatable network requires at least one observer per branch or spur which is not a cost effective solution. This paper proposes a reasonable number of relatively low-cost voltage TW observers with GPS time-synchronization and radio communication to detect and timestamp the TW arrival at several points in the network. In this regard, a method to optimally place a given number of TW detectors to maximize the network observability and locatability is presented. Results show the robustness of the proposed method to detect high impedance and intermittent faults within distribution networks with a minimum number of observers. © 2013 IEEE.
Reduced switch multilevel inverter topologies for renewable energy sources
- Authors: Sarebanzadeh, Maryam , Hosseinzadeh, Mohammad , Garcia, Cristian , Babaei, Ebrahim , Islam, Syed , Rodriguez, Jose
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Access Vol. 9, no. (2021), p. 120580-120595
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- Description: This article proposes two generalized multilevel inverter configurations that reduce the number of switching devices, isolated DC sources, and total standing voltage on power switches, making them suitable for renewable energy sources. The main topology is a multilevel inverter that handles two isolated DC sources with ten power switches to create 25 voltage levels. Based on the main proposed topology, two generalized multilevel inverters are introduced to provide flexibility in the design and to minimize the number of elements. The optimal topologies for both extensive multilevel inverters are derived from different design objectives such as minimizing the number of elements (gate drivers, DC sources), achieving a large number of levels, and minimizing the total standing voltage. The main advantages of the proposed topologies are a reduced number of elements compared to those required by other existing multilevel inverter topologies. The power loss analysis and standalone PV application of the proposed topologies are discussed. Experimental results are presented for the proposed topology to demonstrate its correct operation. © 2013 IEEE.
State estimation within ied based smart grid using kalman estimates
- Authors: Rashed, Muhammad , Gondal, Iqbal , Kamruzzaman, Joarder , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: Electronics (Switzerland) Vol. 10, no. 15 (2021), p.
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- Description: State Estimation is a traditional and reliable technique within power distribution and control systems. It is used for building a topology of the power grid network based on state measurements and current operational state of different nodes & buses. The protection of sensors and measurement units such as Intelligent Electronic Devices (IED) in Central Energy Management System (CEMS) against False Data Injection Attacks (FDIAs) is a big concern to grid operators. These are special kind of cyber-attacks that are directed towards the state & measurement data in such a way that mislead the CEMS into making incorrect decisions and create generation load imbalance. These are known to bypass the traditional bad data detection systems within central estimators. This paper presents the use of an additional novel state estimator based on Kalman filter along with traditional Distributed State Estimation (DSE) which is based on Weighted Least Square (WLS). Kalman filter is a feedback control mechanism that constantly updates itself based on state prediction and state correction technique and shows improvement in the estimates. The additional estimator output is compared with the results of DSE in order to identify anomalies and injection of false data. We evaluated our methodology by simulating proposed technique using MATPOWER over IEEE-14, IEEE-30, IEEE-118, IEEE-300 bus. The results clearly demonstrate the superiority of the proposed method over traditional state estimation. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Toward a substation automation system based on IEC 61850
- Authors: Kumar, Shantanu , Abu-Siada, Ahmed , Das, Narottam , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: Electronics (Switzerland) Vol. 10, no. 3 (2021), p. 1-16
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- Description: With the global trend to digitalize substation automation systems, International Electro technical Commission 61850, a communication protocol defined by the International Electrotechnical Commission, has been given much attention to ensure consistent communication and integration of substation high-voltage primary plant assets such as instrument transformers, circuit breakers and power transformers with various intelligent electronic devices into a hierarchical level. Along with this transition, equipment of primary plants in the switchyard, such as non-conventional instrument transformers, and a secondary system including merging units are expected to play critical roles due to their fast-transient response over a wide bandwidth. While a non-conventional instrument transformer has advantages when compared with the conventional one, extensive and detailed performance investigation and feasibility studies are still required for its full implementation at a large scale within utilities, industries, smart grids and digital substations. This paper is taking one step forward with respect to this aim by employing an optimized network engineering tool to evaluate the performance of an Ethernet-based network and to validate the overall process bus design requirement of a high-voltage non-conventional instrument transformer. Furthermore, the impact of communication delay on the substation automation system during peak traffic is investigated through a detailed simulation analysis. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Trustworthiness of self-driving vehicles for intelligent transportation systems in industry applications
- Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Transactions on Industrial Informatics Vol. 17, no. 2 (2021), p. 961-970
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- Description: To enhance industrial production and automation, rapid and faster transportation of raw materials and finished products to and from distributed factories, warehouses and outlets are essential. To reduce cost with increased efficiency, this will increasingly see the use of connected and self-driving commercial vehicles fitted with industrial grade sensors on roads, shared with normal and self-driving passenger vehicles. For its wide adoption, the trustworthiness of self-driving vehicles in the intelligent transportation system (ITS) is pivotal. In this article, we introduce a novel model to measure the overall trustworthiness of a self-driving vehicle considering on-Board unit (OBU) components, GPS data and safety messages. In calculating the trustworthiness of individual OBU components, CertainLogic and beta distribution function (BDF) are used. Those trust values are fused using both the dempster-Shafer Theory (DST) and a logical operator of CertainLogic. Results of our simulation show that our proposed method can effectively determine the trust of self-driving vehicles. © 2005-2012 IEEE.
A comprehensive analyses of aging characteristics of oil-paper insulation system in HVDC converter transformers
- Authors: Cui, Huize , Yang, Liuqing , Zhu, Yuanwei , Li, Shengtao , Abu-Siada, Ahmed , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 27, no. 5 (2020), p. 1707-1714
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- Description: This paper investigates the dissolved gases evolution in transformer oil under combined DC/AC electrical-Thermal stress. Dissolved gases detected in transformer aged insulation oil reveal that oil under AC electric field combined with thermal stress can produce more dissolved gases than oil under DC electric field with thermal stress but less than the gases produced in oil under distorted AC or combined AC/DC voltage stress. This is attributed to the divergent migration properties of the charged components under different types of electric fields. To further understand this behavior, carrier recombination coefficient is proposed to explain the oil DGA results under various aging stresses. Results show that diagnostic parameters such as breakdown voltage, oil interfacial tension, and moisture content in pressboard should be used along with DGA results in order to accurately diagnose the insulation condition within converter transformers that impose a combined AC/DC voltage stress on the insulation system. © 1994-2012 IEEE.
- Description: This work has been supported by the National Key Research and Development Program of China (2017YFB0902705), State Key Laboratory of Electrical Insulation and Power Equipment (EIPE20210), the National Natural Science Foundation of China (51907148), the Youth Fund of State Key Laboratory of Electrical Insulation and Power Equipment (EIPE19308), the Foundation Project of State Grid in Shaanxi province section, China (SGSNKY00SPJS1900302). The authors thank the Natural Science Basic Research Plan in Shaanxi Province of China (2019JQ-070).