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Overview of power converter control in microgrids - challenges, advances, and future trends

- Hu, Jiefeng, Shan, Yinghao, Cheng, Ka, Islam, Syed

  • 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 Fast and Reliable Blocked Bus Bar Protection Scheme Leveraging on Sampled Value and GOOSE Protection 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: 2021
  • Type: Text , Conference paper
  • Relation: 31st Australasian Universities Power Engineering Conference, AUPEC 2021, Virtual, Online 26 to 30 September 2021, Proceedings of 2021 31st Australasian Universities Power Engineering Conference, AUPEC 2021
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  • Description: Substation Automation System (SAS) is in a matured state and promises to replace conventional protection scheme. It has created a new paradigm in its application for future smart grids. The multifunction features of IEC 61850 facilitate this technology to reliably monitor, protect and control critical assets. Mostly agree, the intelligent electronic devices (IEDs) and substation automation features have the same effect as 'html' had in developing web technology on IT system in 1990's. However, in order to be acceptable completely, this technology needs to gain confidence of end user, it needs to be researched further using multivendor equipment and experimented in a network comprising of complex secondary protection schemes. In this paper, a practical Blocked Busbar Protection (BBP) scheme have been implemented and tested for a single bus bar scheme, leveraging on Sampled Values (SV) and Generic Object Oriented Substation Event (GOOSE) at laboratory to prove its reliability and improvement in technology. This experiment has been carried out for three scenarios in a simulated substation network related to a process plant industry. Furthermore, this laboratory-based experiment with multivendor IEDs evaluated performance of an Ethernet and FO based process bus network to validate overall performance of BBP protection scheme. It concluded with a comparison between digital and conventional protection scheme with recommendation for future applications. © 2021 IEEE.

A unified model predictive voltage and current control for microgrids with distributed fuzzy cooperative secondary control

- Shan, Yinghao, Hu, Jiefeng, Chan, Ka, Islam, Syed

  • 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 reliability of smart grid against cyberattacks using stability index

- Rashed, Muhammad, Gondal, Iqbal, Kamruzzaman, Joarder, Islam, Syed

  • Authors: Rashed, Muhammad , Gondal, Iqbal , Kamruzzaman, Joarder , Islam, Syed
  • Date: 2021
  • Type: Text , Conference paper
  • Relation: 31st Australasian Universities Power Engineering Conference, AUPEC 2021, Virtual, Online 26 to 30 September 2021, Proceedings of 2021 31st Australasian Universities Power Engineering Conference, AUPEC 2021
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  • Description: The degradation of stability index within smart grid leads to incorrect power generation and poor load balancing. The remote data dependency of the central energy management system (CEMS) causes communication delay that further leads to poor synchronization within the system. This becomes worse in the presence of cyber-attacks such as stealth or false data injection attack (FDIA). We used dynamic estimation to obtain state data after the inception of false data attack and analyzed its impact on the stability index of the smart grid. A lookup table was constructed based on the fluctuations within the voltage estimates of IEEE-Bus system. An index number was assigned to output estimates at the bus that highlights the level of severity within the grid. We used IEEE-57 Bus using MATLAB to capture and plot the results related to voltage estimates, latency, and inception time delay. The results demonstrate a clear relationship between stability index and state estimates especially when the system is under the influence of a cyber-attack. © 2021 IEEE.

Assessing trust level of a driverless car using deep learning

- Karmakar, Gour, Chowdhury, Abdullahi, Das, Rajkumar, Kamruzzaman, Joarder, Islam, Syed

  • 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

- Cui, Huize, Yang, Liuqing, Zhu, Yuanwei, Li, Shengtao, Abu-Siada, A., Islam, Syed

  • Authors: Cui, Huize , Yang, Liuqing , Zhu, Yuanwei , Li, Shengtao , Abu-Siada, A. , 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

- Fauzan, Miftah, Muyeen, S., Islam, Syed

  • 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

- 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.

Interpretation of transformer winding deformation fault by the spectral clustering of FRA signature

- Zhao, Zhongyong, Tang, Chao, Chen, Yu, Zhou, Qu, Yao, Chenguo, Islam, Syed

  • 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

MATLAB/Simulink Modelling of Multi-junction PV Cell for Conversion Efficiency Improvement using Maximum Power Point Tracking Method

- Dave, Malvika, Das, Narottam, Islam, Syed

  • Authors: Dave, Malvika , Das, Narottam , Islam, Syed
  • Date: 2021
  • Type: Text , Conference paper
  • Relation: 2021 IEEE PES Innovative Smart Grid Technologies - Asia, ISGT Asia 2021, Brisbane, 5-8 December 2021
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  • Description: This research focuses the modelling of multi-junction solar cells (MJSCs) for conversion efficiency improvement considering maximum power point tracking (MPPT) utilizing MATLAB/Simulink software. The conversion efficiency of a single-junction photovoltaic (PV) cell is comparatively low than the MJSCs (GaInP/GaInAs/Ge). The cell conversion efficiency is improved by forming MJSCs, where two or more single junctions are stacked, and higher conversion efficiency is achieved using the MPPT method in MATLAB/Simulink environment to maximize the output power of PV panel. This research considered different parameters of MJSCs, such as lattice matching, bandgap matching, current matching to improve the conversion efficiency. The maximum performance of MJSCs also obtained through the I-V and P-V characteristics by varying different environmental factors, such as temperature and irradiance in MATLAB/Simulink environment. perturb and observe (P&O) MPPT algorithm which is the most suitable for PV applications. Finally, two different Pulse Width Modulation techniques are compared and analyzed with respect to Perturb and observe by applying Quasi Z source inverter (QZSI) within the MATLAB/Simulink environment to enhance the conversion efficiency of triple MJSC. © 2021 IEEE

Mitigation of Power Quality Issues with Solar PV Penetration into LV/MV Distribution System

- Patel, Bhoomi, Das, Narottam, Islam, Syed

  • Authors: Patel, Bhoomi , Das, Narottam , Islam, Syed
  • Date: 2021
  • Type: Text , Conference paper
  • Relation: 2021 IEEE PES Innovative Smart Grid Technologies - Asia, ISGT Asia 2021, Brisbane, 5-8 December 2021
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  • Description: Over the last decades, solar photovoltaic (PV) system on the low and medium voltage distribution network is growing dramatically. The power grids are still facing the experience of more penetration to satisfy electricity demand of the consumer. Another reason for solar PV penetration is government subsidies for the customers, decreasing the capital cost of solar PV, feed-in-tariff and to balance the CO2 emission from the atmosphere. The integration of PV system in low voltage or medium voltage ((LV/MV) distribution networks is raising new challenges in terms of power quality (PQ). In the LV/MV distribution networks, PQ problems are voltage sag and swell are the most serious concern, and it occurs when residential renewable energy sources (i.e., solar PV) produce more energy than the local demand. As per the PQ studies, voltage sag/swell issues in the LV/MV power grid considered to be the most common type of PQ issue. Impact of this type of issue on sensitive loads is harsh. Hence, different types of solution have been used to protect sensitive loads from such voltage problems, but the dynamic voltage restorer is to be considered, effective and efficient solution. Dynamic Voltage Restorer (DVR) is a series connected power electronic device which is used to alleviate the voltage sag/swell problem in the distribution system and restore the load voltage to the required value. Therefore, the main objective of this research project is to investigate and understand the impact of PQ issues in LV/MV distribution system and aim is to alleviate them. MATLAB/Simulink software is used to solve the PQ issues by designing battery supported DVR with energy storage systems. The performance of battery supported DVR is designed, simulated in MATLAB/Simulink software environment, and analysed in detail. © 2021 IEEE

Model predictive control for microgrids : from power electronic converters to energy management

- Hu, Jiefeng, Guerrero, Josep, Islam, Syed

  • Authors: Hu, Jiefeng , Guerrero, Josep , Islam, Syed
  • Date: 2021
  • Type: Text , Book
  • Relation: IET Energy Engineering Series, Vol. 199
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  • Description: Microgrids have emerged as a promising solution for accommodating the integration of renewable energy resources. But the intermittency of renewable generation is posing challenges such as voltage/frequency fluctuations, and grid stability issues in grid-connected modes. Model predictive control (MPC) is a method for controlling a process while satisfying a set of constraints. It has been in use for chemical plants and in oil refineries since the 1980s, but in recent years has been deployed for power systems and electronics as well. This concise work for researchers, engineers and graduate students focuses on the use of MPC for distributed renewable power generation in microgrids. Fluctuating outputs from renewable energy sources and variable load demands are covered, as are control design concepts. The authors provide examples and case studies to validate the theory with both simulation and experimental results and review the shortcomings and future developments. Chapters treat power electronic converters and control; modelling and hierarchical control of microgrids; use of MPC for PV and wind power; voltage support; parallel PV-ESS microgrids; secondary restoration capability; and tertiary power flow optimization. © The Institution of Engineering and Technology 2021.

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.

Protection of feeders with high rooftop PV penetration

- Yengejeh, Hadi, Shahnia, Farhad, Islam, Syed

  • Authors: Yengejeh, Hadi , Shahnia, Farhad , Islam, Syed
  • Date: 2021
  • Type: Text , Book chapter
  • Relation: Handbook Of Renewable Energy Technology & Systems Chapter 13 p. 339-381
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  • Description: This chapter focuses on short-circuit fault on the feeders supplying residential customers with rooftop photovoltaic (PV) systems. The chapter discusses the sensitivity of the short-circuit fault level and the corresponding current drawn from the distribution transformer, in addition to the node voltages along the low-voltage feeder, following a short-circuit fault. The chapter also demonstrates that various factors such as the PVs' installation point and rating, as well as the location and type of the fault, impact the study parameters. Furthermore, the chapter illustrates that the time and sequence of the PVs' isolation following the fault will vary depending on the impedance and location of fault, the PV generation-demand ratio, as well as the network's earthing type. © 2022 by World Scientific Publishing Europe Ltd. All rights reserved.

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.

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.
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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

- 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
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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

- Chowdhury, Abdullahi, Karmakar, Gour, Kamruzzaman, Joarder, Islam, Syed

  • 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

- Cui, Huize, Yang, Liuqing, Zhu, Yuanwei, Li, Shengtao, Abu-Siada, A., Islam, Syed

  • Authors: Cui, Huize , Yang, Liuqing , Zhu, Yuanwei , Li, Shengtao , Abu-Siada, A. , 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).

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
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  • 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.