Economic model predictive control for microgrid optimization : a review
- Hu, Jiefeng, Shan, Yinghao, Yang, Yong, Parisio, Alessandra, Li, Yong, Amjady, Nima, Islam, Syed, Cheng, Ka, Guerrero, Josep, Rodriguez, Jose
- Authors: Hu, Jiefeng , Shan, Yinghao , Yang, Yong , Parisio, Alessandra , Li, Yong , Amjady, Nima , Islam, Syed , Cheng, Ka , Guerrero, Josep , Rodriguez, Jose
- Date: 2024
- Type: Text , Journal article
- Relation: IEEE Transactions on Smart Grid Vol. 15, no. 1 (2024), p. 472-484
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- Description: Microgrids have emerged as a promising solution to integrate distributed energy resources (DERs) and supply reliable and efficient electricity. The operation of a microgrid involves the coordination of different DERs and loads. To date, various control methods have been developed to maximize the overall benefit while satisfying various constraints. Now it is urgently needed to understand and comprehend these approaches to further stimulate the deployment of microgrids. This paper presents an overview for researchers on economic model predictive control (EMPC) methods of microgrids to achieve a variety of objectives such as cost minimization and benefit maximization. The fundamental principle of the EMPC theory is explained in detail. The most popular and important strategies applied to stand-alone microgrids, grid-connected microgrids, residential smart homes, as well as networked microgrids are discussed. Future trends are also highlighted. © 2010-2012 IEEE.
- Authors: Hu, Jiefeng , Shan, Yinghao , Yang, Yong , Parisio, Alessandra , Li, Yong , Amjady, Nima , Islam, Syed , Cheng, Ka , Guerrero, Josep , Rodriguez, Jose
- Date: 2024
- Type: Text , Journal article
- Relation: IEEE Transactions on Smart Grid Vol. 15, no. 1 (2024), p. 472-484
- Full Text:
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- Description: Microgrids have emerged as a promising solution to integrate distributed energy resources (DERs) and supply reliable and efficient electricity. The operation of a microgrid involves the coordination of different DERs and loads. To date, various control methods have been developed to maximize the overall benefit while satisfying various constraints. Now it is urgently needed to understand and comprehend these approaches to further stimulate the deployment of microgrids. This paper presents an overview for researchers on economic model predictive control (EMPC) methods of microgrids to achieve a variety of objectives such as cost minimization and benefit maximization. The fundamental principle of the EMPC theory is explained in detail. The most popular and important strategies applied to stand-alone microgrids, grid-connected microgrids, residential smart homes, as well as networked microgrids are discussed. Future trends are also highlighted. © 2010-2012 IEEE.
A proximal subgradient algorithm with extrapolation for structured nonconvex nonsmooth problems
- Pham, Tan, Dao, Minh, Shah, Rakibuzzaman, Sultanova, Nargiz, Li, Guoyin, Islam, Syed
- 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).
- 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
- Das, Narottam, Haque, Akramul, Zaman, Hasneen, Morsalin, Sayidul, Islam, Syed
- 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.
- 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.
Numerical model of cloud-to-ground lightning for pyroCb thunderstorms
- Barman, Surajit, Shah, Rakibuzzaman, Islam, Syed, Kumar, Apurv
- 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.
- 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
- Kumar, Shantanu, Abu-Siada, Ahmed, Das, Narottam, Islam, Syed
- 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.
- 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
- Kumar, Shantanu, Abu-Siada, Ahmed, Das, Narottam, Islam, Syed
- 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.
- 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.
- Full Text:
- Reviewed:
- 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.
Blockchain based smart auction mechanism for distributed peer-to-peer energy trading
- Islam, Md Ezazul, Chetty, Madhu, Lim, Suryani, Chadhar, Mehmood, Islam, Syed
- Authors: Islam, Md Ezazul , Chetty, Madhu , Lim, Suryani , Chadhar, Mehmood , Islam, Syed
- Date: 2022
- Type: Text , Conference paper
- Relation: 55th Annual Hawaii International Conference on System Sciences, HICSS 2022, Virtual, online, 3-7 January 2022, Proceedings of the Annual Hawaii International Conference on System Sciences Vol. 2022-January, p. 6013-6022
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- Description: Blockchain based framework provides data immutability in a distributed network. In this paper, we investigate the application of blockchain for peer-to-peer (P2P) energy trading. Traditional energy trading systems use simple passing mechanisms and basic pricing methods, thus adversely affect the efficiency and buyers' social welfare. We propose a blockchain based energy trading mechanism that uses smart passing of unspent auction reservations to (a) minimise the time taken to settle an auction (convergence time), (b) maximise the number of auction settlement; and (c) incorporate second-price auction pricing to maximise buyers' social welfare in a distributed double auction environment. The entire mechanism is implemented within Hyperledger Fabric, an open-source blockchain framework, to manage the data and provide smart contracts. Experiments show that our approach minimises the convergence time, maximises the number of auction settlement, and increases the social welfare of buyers compared to existing methods. © 2022 IEEE Computer Society. All rights reserved.
- Authors: Islam, Md Ezazul , Chetty, Madhu , Lim, Suryani , Chadhar, Mehmood , Islam, Syed
- Date: 2022
- Type: Text , Conference paper
- Relation: 55th Annual Hawaii International Conference on System Sciences, HICSS 2022, Virtual, online, 3-7 January 2022, Proceedings of the Annual Hawaii International Conference on System Sciences Vol. 2022-January, p. 6013-6022
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- Description: Blockchain based framework provides data immutability in a distributed network. In this paper, we investigate the application of blockchain for peer-to-peer (P2P) energy trading. Traditional energy trading systems use simple passing mechanisms and basic pricing methods, thus adversely affect the efficiency and buyers' social welfare. We propose a blockchain based energy trading mechanism that uses smart passing of unspent auction reservations to (a) minimise the time taken to settle an auction (convergence time), (b) maximise the number of auction settlement; and (c) incorporate second-price auction pricing to maximise buyers' social welfare in a distributed double auction environment. The entire mechanism is implemented within Hyperledger Fabric, an open-source blockchain framework, to manage the data and provide smart contracts. Experiments show that our approach minimises the convergence time, maximises the number of auction settlement, and increases the social welfare of buyers compared to existing methods. © 2022 IEEE Computer Society. All rights reserved.
False data detection in a clustered smart grid using unscented Kalman filter
- Rashed, Muhammad, Kamruzzaman, Joarder, Gondal, Iqbal, Islam, Syed
- 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.
- 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
- Full Text:
- Reviewed:
- 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.
Forced oscillation in power systems with converter controlled-based resources- a survey with case studies
- Surinkaew, Tossaporn, Emami, Koanoush, Shah, Rakibuzzaman, Islam, Syed, Mithulananthan, N.
- 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.
- 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.
Optimal placement of synchronized voltage traveling wave sensors in a radial distribution network
- Tashakkori, Ali, Abu-Siada, Ahmed, Wolfs, Peter, Islam, Syed
- 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.
- 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
- Full Text:
- Reviewed:
- 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
- Sarebanzadeh, Maryam, Hosseinzadeh, Mohammad, Garcia, Cristian, Babaei, Ebrahim, Islam, Syed, Rodriguez, Jose
- 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.
- 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
- Full Text:
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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
- Rashed, Muhammad, Gondal, Iqbal, Kamruzzaman, Joarder, Islam, Syed
- Authors: Rashed, Muhammad , Gondal, Iqbal , Kamruzzaman, Joarder , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: Electronics (Switzerland) Vol. 10, no. 15 (2021), p.
- Full Text:
- Reviewed:
- 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.
- Authors: Rashed, Muhammad , Gondal, Iqbal , Kamruzzaman, Joarder , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: Electronics (Switzerland) Vol. 10, no. 15 (2021), p.
- Full Text:
- Reviewed:
- 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
- Kumar, Shantanu, Abu-Siada, Ahmed, Das, Narottam, Islam, Syed
- 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
- Full Text:
- Reviewed:
- 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.
- 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
- Full Text:
- Reviewed:
- 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.
A new data driven long-term solar yield analysis model of photovoltaic power plants
- Ray, Biplob, Shah, Rakibuzzaman, Islam, Md Rabiul, Islam, Syed
- Authors: Ray, Biplob , Shah, Rakibuzzaman , Islam, Md Rabiul , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 136223-136233
- Full Text:
- Reviewed:
- Description: Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV system) in Australia to obtain the trade-off between accuracy and efficacy. The historical dataset from 1990-2013 in Australian locations (e.g. North Queensland) are used to train the model. The model is developed using the combination of multivariate long and short-term memory (LSTM) and convolutional neural network (CNN). The proposed hybrid deep learning (LSTM-CNN) is compared with the existing neural network ensemble (NNE), random forest, statistical analysis, and artificial neural network (ANN) based techniques to assess the performance. The proposed model could be useful for generation planning and reserve estimation in power systems with high penetration of solar photovoltaics (PVs) or other renewable energy sources (RESs). © 2013 IEEE.
- Authors: Ray, Biplob , Shah, Rakibuzzaman , Islam, Md Rabiul , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 136223-136233
- Full Text:
- Reviewed:
- Description: Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV system) in Australia to obtain the trade-off between accuracy and efficacy. The historical dataset from 1990-2013 in Australian locations (e.g. North Queensland) are used to train the model. The model is developed using the combination of multivariate long and short-term memory (LSTM) and convolutional neural network (CNN). The proposed hybrid deep learning (LSTM-CNN) is compared with the existing neural network ensemble (NNE), random forest, statistical analysis, and artificial neural network (ANN) based techniques to assess the performance. The proposed model could be useful for generation planning and reserve estimation in power systems with high penetration of solar photovoltaics (PVs) or other renewable energy sources (RESs). © 2013 IEEE.
Enhancement of microgrid operation by considering the cascaded impact of communication delay on system stability and power management
- Aghanoori, Navid, Masoum, Mohammad, Abu-Siada, Ahmed, Islam, Syed
- Authors: Aghanoori, Navid , Masoum, Mohammad , Abu-Siada, Ahmed , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: International Journal of Electrical Power and Energy Systems Vol. 120, no. (2020), p.
- Full Text:
- Reviewed:
- Description: Power management, system stability and communication structure are three key aspects of microgrids (MGs) that have been explored in many research studies. However, the cascaded effect of communication structure on system stability followed by the impact of stability on the power management has not been fully explored in the literature yet and needs more attention. This paper not only explores this cascaded impact, but also provides a comprehensive platform to optimally consider three layers of MG design and operation from this perspective. For generation cost minimization and stability assessment, the proposed platform uses an adaptive particle swarm optimization (PSO) while a new class of data exchange scheme based on IEC 61850 protocol is proposed to reduce the communication time delays among the inverters of distributed generations and the MG control center. This paper also considers the system stability using small-signal model of a MG in a real-time manner as an embedded function in the PSO. In this context investigations have been conducted by modeling an isolated MG with solar farm, fuel cell generator and micro-turbine in MATLAB Simulink. Detailed simulation results indicate the proposed power and stability management method effectively reduces the MG generation cost through maximizing the utilization of the available renewable generations while considering system stability. © 2020 Elsevier Ltd
- Authors: Aghanoori, Navid , Masoum, Mohammad , Abu-Siada, Ahmed , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: International Journal of Electrical Power and Energy Systems Vol. 120, no. (2020), p.
- Full Text:
- Reviewed:
- Description: Power management, system stability and communication structure are three key aspects of microgrids (MGs) that have been explored in many research studies. However, the cascaded effect of communication structure on system stability followed by the impact of stability on the power management has not been fully explored in the literature yet and needs more attention. This paper not only explores this cascaded impact, but also provides a comprehensive platform to optimally consider three layers of MG design and operation from this perspective. For generation cost minimization and stability assessment, the proposed platform uses an adaptive particle swarm optimization (PSO) while a new class of data exchange scheme based on IEC 61850 protocol is proposed to reduce the communication time delays among the inverters of distributed generations and the MG control center. This paper also considers the system stability using small-signal model of a MG in a real-time manner as an embedded function in the PSO. In this context investigations have been conducted by modeling an isolated MG with solar farm, fuel cell generator and micro-turbine in MATLAB Simulink. Detailed simulation results indicate the proposed power and stability management method effectively reduces the MG generation cost through maximizing the utilization of the available renewable generations while considering system stability. © 2020 Elsevier Ltd
Low-power wide-area networks : design goals, architecture, suitability to use cases and research challenges
- Buurman, Ben, Kamruzzaman, Joarder, Karmakar, Gour, Islam, Syed
- Authors: Buurman, Ben , Kamruzzaman, Joarder , Karmakar, Gour , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 17179-17220
- Full Text:
- Reviewed:
- Description: Previous survey articles on Low-Powered Wide-Area Networks (LPWANs) lack a systematic analysis of the design goals of LPWAN and the design decisions adopted by various commercially available and emerging LPWAN technologies, and no study has analysed how their design decisions impact their ability to meet design goals. Assessing a technology's ability to meet design goals is essential in determining suitable technologies for a given application. To address these gaps, we have analysed six prominent design goals and identified the design decisions used to meet each goal in the eight LPWAN technologies, ranging from technical consideration to business model, and determined which specific technique in a design decision will help meet each goal to the greatest extent. System architecture and specifications are presented for those LPWAN solutions, and their ability to meet each design goal is evaluated. We outline seventeen use cases across twelve domains that require large low power network infrastructure and prioritise each design goal's importance to those applications as Low, Moderate, or High. Using these priorities and each technology's suitability for meeting design goals, we suggest appropriate LPWAN technologies for each use case. Finally, a number of research challenges are presented for current and future technologies. © 2013 IEEE.
- Authors: Buurman, Ben , Kamruzzaman, Joarder , Karmakar, Gour , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 17179-17220
- Full Text:
- Reviewed:
- Description: Previous survey articles on Low-Powered Wide-Area Networks (LPWANs) lack a systematic analysis of the design goals of LPWAN and the design decisions adopted by various commercially available and emerging LPWAN technologies, and no study has analysed how their design decisions impact their ability to meet design goals. Assessing a technology's ability to meet design goals is essential in determining suitable technologies for a given application. To address these gaps, we have analysed six prominent design goals and identified the design decisions used to meet each goal in the eight LPWAN technologies, ranging from technical consideration to business model, and determined which specific technique in a design decision will help meet each goal to the greatest extent. System architecture and specifications are presented for those LPWAN solutions, and their ability to meet each design goal is evaluated. We outline seventeen use cases across twelve domains that require large low power network infrastructure and prioritise each design goal's importance to those applications as Low, Moderate, or High. Using these priorities and each technology's suitability for meeting design goals, we suggest appropriate LPWAN technologies for each use case. Finally, a number of research challenges are presented for current and future technologies. © 2013 IEEE.
Assessing transformer oil quality using deep convolutional networks
- Alam, Mohammad, Karmakar, Gour, Islam, Syed, Kamruzzaman, Joarder, Chetty, Madhu, Lim, Suryani, Appuhamillage, Gayan, Chattopadhyay, Gopi, Wilcox, Steve, Verheyen, Vincent
- Authors: Alam, Mohammad , Karmakar, Gour , Islam, Syed , Kamruzzaman, Joarder , Chetty, Madhu , Lim, Suryani , Appuhamillage, Gayan , Chattopadhyay, Gopi , Wilcox, Steve , Verheyen, Vincent
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 29th Australasian Universities Power Engineering Conference, AUPEC 2019
- Full Text:
- Reviewed:
- Description: Electrical power grids comprise a significantly large number of transformers that interconnect power generation, transmission and distribution. These transformers having different MVA ratings are critical assets that require proper maintenance to provide long and uninterrupted electrical service. The mineral oil, an essential component of any transformer, not only provides cooling but also acts as an insulating medium within the transformer. The quality and the key dissolved properties of insulating mineral oil for the transformer are critical with its proper and reliable operation. However, traditional chemical diagnostic methods are expensive and time-consuming. A transformer oil image analysis approach, based on the entropy value of oil, which is inexpensive, effective and quick. However, the inability of entropy to estimate the vital transformer oil properties such as equivalent age, Neutralization Number (NN), dissipation factor (tanδ) and power factor (PF); and many intuitively derived constants usage limit its estimation accuracy. To address this issue, in this paper, we introduce an innovative transformer oil analysis using two deep convolutional learning techniques such as Convolutional Neural Network (ConvNet) and Residual Neural Network (ResNet). These two deep neural networks are chosen for this project as they have superior performance in computer vision. After estimating the equivalent aging year of transformer oil from its image by our proposed method, NN, tanδ and PF are computed using that estimated age. Our deep learning based techniques can accurately predict the transformer oil equivalent age, leading to calculate NN, tanδ and PF more accurately. The root means square error of estimated equivalent age produced by entropy, ConvNet and ResNet based methods are 0.718, 0.122 and 0.065, respectively. ConvNet and ResNet based methods have reduced the error of the oil age estimation by 83% and 91%, respectively compared to that of the entropy method. Our proposed oil image analysis can calculate the equivalent age that is very close to the actual age for all images used in the experiment. © 2019 IEEE.
- Description: E1
- Authors: Alam, Mohammad , Karmakar, Gour , Islam, Syed , Kamruzzaman, Joarder , Chetty, Madhu , Lim, Suryani , Appuhamillage, Gayan , Chattopadhyay, Gopi , Wilcox, Steve , Verheyen, Vincent
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 29th Australasian Universities Power Engineering Conference, AUPEC 2019
- Full Text:
- Reviewed:
- Description: Electrical power grids comprise a significantly large number of transformers that interconnect power generation, transmission and distribution. These transformers having different MVA ratings are critical assets that require proper maintenance to provide long and uninterrupted electrical service. The mineral oil, an essential component of any transformer, not only provides cooling but also acts as an insulating medium within the transformer. The quality and the key dissolved properties of insulating mineral oil for the transformer are critical with its proper and reliable operation. However, traditional chemical diagnostic methods are expensive and time-consuming. A transformer oil image analysis approach, based on the entropy value of oil, which is inexpensive, effective and quick. However, the inability of entropy to estimate the vital transformer oil properties such as equivalent age, Neutralization Number (NN), dissipation factor (tanδ) and power factor (PF); and many intuitively derived constants usage limit its estimation accuracy. To address this issue, in this paper, we introduce an innovative transformer oil analysis using two deep convolutional learning techniques such as Convolutional Neural Network (ConvNet) and Residual Neural Network (ResNet). These two deep neural networks are chosen for this project as they have superior performance in computer vision. After estimating the equivalent aging year of transformer oil from its image by our proposed method, NN, tanδ and PF are computed using that estimated age. Our deep learning based techniques can accurately predict the transformer oil equivalent age, leading to calculate NN, tanδ and PF more accurately. The root means square error of estimated equivalent age produced by entropy, ConvNet and ResNet based methods are 0.718, 0.122 and 0.065, respectively. ConvNet and ResNet based methods have reduced the error of the oil age estimation by 83% and 91%, respectively compared to that of the entropy method. Our proposed oil image analysis can calculate the equivalent age that is very close to the actual age for all images used in the experiment. © 2019 IEEE.
- Description: E1
Classifying transformer winding deformation fault types and degrees using FRA based on support vector machine
- Liu, Jiangnan, Zhao, Zhongyong, Tang, Chao, Yao, Chenguo, Li, Chengxiang, Islam, Syed
- Authors: Liu, Jiangnan , Zhao, Zhongyong , Tang, Chao , Yao, Chenguo , Li, Chengxiang , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 112494-112504
- Full Text:
- Reviewed:
- Description: As an important part of power system, power transformer plays an irreplaceable role in the process of power transmission. Diagnosis of transformer's failure is of significance to maintain its safe and stable operation. Frequency response analysis (FRA) has been widely accepted as an effective tool for winding deformation fault diagnosis, which is one of the common failures for power transformers. However, there is no standard and reliable code for FRA interpretation as so far. In this paper, support vector machine (SVM) is combined with FRA to diagnose transformer faults. Furthermore, advanced optimization algorithms are also applied to improve the performance of models. A series of winding fault emulating experiments were carried out on an actual model transformer, the key features are extracted from measured FRA data, and the diagnostic model is trained and obtained, to arrive at an outcome for classifying the fault types and degrees of winding deformation faults with satisfactory accuracy. The diagnostic results indicate that this method has potential to be an intelligent, standardized, accurate and powerful tool.
- Authors: Liu, Jiangnan , Zhao, Zhongyong , Tang, Chao , Yao, Chenguo , Li, Chengxiang , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 112494-112504
- Full Text:
- Reviewed:
- Description: As an important part of power system, power transformer plays an irreplaceable role in the process of power transmission. Diagnosis of transformer's failure is of significance to maintain its safe and stable operation. Frequency response analysis (FRA) has been widely accepted as an effective tool for winding deformation fault diagnosis, which is one of the common failures for power transformers. However, there is no standard and reliable code for FRA interpretation as so far. In this paper, support vector machine (SVM) is combined with FRA to diagnose transformer faults. Furthermore, advanced optimization algorithms are also applied to improve the performance of models. A series of winding fault emulating experiments were carried out on an actual model transformer, the key features are extracted from measured FRA data, and the diagnostic model is trained and obtained, to arrive at an outcome for classifying the fault types and degrees of winding deformation faults with satisfactory accuracy. The diagnostic results indicate that this method has potential to be an intelligent, standardized, accurate and powerful tool.
Diagnosing transformer winding deformation faults based on the analysis of binary image obtained from FRA signature
- Zhao, Zhongyong, Yao, Chenguo, Tang, Chao, Li, Chengxiang, Yan, Fayou, Islam, Syed
- Authors: Zhao, Zhongyong , Yao, Chenguo , Tang, Chao , Li, Chengxiang , Yan, Fayou , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 40463-40474
- Full Text:
- Reviewed:
- Description: Frequency response analysis (FRA) has been widely accepted as a diagnostic tool for power transformer winding deformation faults. Typically, both amplitude-frequency and phase-frequency signatures are obtained by an FRA analyzer. However, most existing FRA analyzers use only the information on amplitude-frequency signature, while phase-frequency information is neglected. It is also found that in some cases, the diagnostic results obtained by FRA amplitude-frequency signatures do not comply with some hard evidence. This paper introduces a winding deformation diagnostic method based on the analysis of binary images obtained from FRA signatures to improve FRA outcomes. The digital image processing technique is used to process the binary image and obtain a diagnostic indicator, to arrive at an outcome for interpreting winding faults with improved accuracy.
- Authors: Zhao, Zhongyong , Yao, Chenguo , Tang, Chao , Li, Chengxiang , Yan, Fayou , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 40463-40474
- Full Text:
- Reviewed:
- Description: Frequency response analysis (FRA) has been widely accepted as a diagnostic tool for power transformer winding deformation faults. Typically, both amplitude-frequency and phase-frequency signatures are obtained by an FRA analyzer. However, most existing FRA analyzers use only the information on amplitude-frequency signature, while phase-frequency information is neglected. It is also found that in some cases, the diagnostic results obtained by FRA amplitude-frequency signatures do not comply with some hard evidence. This paper introduces a winding deformation diagnostic method based on the analysis of binary images obtained from FRA signatures to improve FRA outcomes. The digital image processing technique is used to process the binary image and obtain a diagnostic indicator, to arrive at an outcome for interpreting winding faults with improved accuracy.
Dual mechanical port machine based hybrid electric vehicle using reduced switch converters
- Bizhani, Hamed, Yao, Gang, Muyeen, S., Islam, Syed, Ben-Brahim, Lazhar
- Authors: Bizhani, Hamed , Yao, Gang , Muyeen, S. , Islam, Syed , Ben-Brahim, Lazhar
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 33665-33676
- Full Text:
- Reviewed:
- Description: Due to the increased environmental pollution, hybrid vehicles have attracted enormous attention in today's society. The two most important factors in designing these vehicles are size and weight. For this purpose, some researchers have presented the use of the dual-mechanical-port machine (DMPM) in hybrid electric vehicles (HEVs). This paper presents two modified converter topologies with a reduced number of switching devices for use on DMPM-based HEVs, with the goal of reducing the overall size and weight of the system. Beside the design of the DMPM in the series-parallel HEV structure along with the energy management unit, the conventional back-to-back (BB) converter is replaced with nine-switch (NS) and five-leg (FL) converters. These converters have never been examined for the DMPM-based HEV, and therefore, the objective of this paper is to reveal the operational characteristics and power flow mechanism of this machine using the NS and FL converters. The simulation analysis is carried out using MATLAB/Simulink considering all HEV operational modes. In addition, two proposed and the conventional converters are compared in terms of losses, maximum achievable voltages, required dc-link voltages, the rating of the components, and torque ripple, and finally, a recommendation is made based on the obtained results.
- Authors: Bizhani, Hamed , Yao, Gang , Muyeen, S. , Islam, Syed , Ben-Brahim, Lazhar
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 33665-33676
- Full Text:
- Reviewed:
- Description: Due to the increased environmental pollution, hybrid vehicles have attracted enormous attention in today's society. The two most important factors in designing these vehicles are size and weight. For this purpose, some researchers have presented the use of the dual-mechanical-port machine (DMPM) in hybrid electric vehicles (HEVs). This paper presents two modified converter topologies with a reduced number of switching devices for use on DMPM-based HEVs, with the goal of reducing the overall size and weight of the system. Beside the design of the DMPM in the series-parallel HEV structure along with the energy management unit, the conventional back-to-back (BB) converter is replaced with nine-switch (NS) and five-leg (FL) converters. These converters have never been examined for the DMPM-based HEV, and therefore, the objective of this paper is to reveal the operational characteristics and power flow mechanism of this machine using the NS and FL converters. The simulation analysis is carried out using MATLAB/Simulink considering all HEV operational modes. In addition, two proposed and the conventional converters are compared in terms of losses, maximum achievable voltages, required dc-link voltages, the rating of the components, and torque ripple, and finally, a recommendation is made based on the obtained results.