ORCID Profile
0000-0001-9060-4454
Current Organisation
Green University of Bangladesh
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Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2021
Publisher: MDPI AG
Date: 20-12-2022
DOI: 10.3390/EN16010023
Abstract: Real-time battery SOX estimation including the state of charge (SOC), state of energy (SOE), and state of health (SOH) is the crucial evaluation indicator to assess the performance of automotive battery management systems (BMSs). Recently, intelligent models in terms of deep learning (DL) have received massive attention in electric vehicle (EV) BMS applications due to their improved generalization performance and strong computation capability to work under different conditions. However, estimation of accurate and robust SOC, SOH, and SOE in real-time is challenging since they are internal battery parameters and depend on the battery’s materials, chemical reactions, and aging as well as environmental temperature settings. Therefore, the goal of this review is to present a comprehensive explanation of various DL approaches for battery SOX estimation, highlighting features, configurations, datasets, battery chemistries, targets, results, and contributions. Various DL methods are critically discussed, outlining advantages, disadvantages, and research gaps. In addition, various open challenges, issues, and concerns are investigated to identify existing concerns, limitations, and challenges. Finally, future suggestions and guidelines are delivered toward accurate and robust SOX estimation for sustainable operation and management in EV operation.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: MDPI AG
Date: 10-2021
DOI: 10.3390/SU131910943
Abstract: Electric vehicles (EVs) have received massive consideration in the automotive industries due to their improved performance, efficiency and capability to minimize global warming and carbon emission impacts. The utilization of EVs has several potential benefits, such as increased use of renewable energy, less dependency on fossil-fuel-based power generations and energy-storage capability. Although EVs can significantly mitigate global carbon emissions, it is challenging to maintain power balance during charging on-peak hours. Thus, it mandates a comprehensive impact analysis of high-level electric vehicle penetration in utility grids. This paper investigates the impacts of large-scale EV penetration on low voltage distribution, considering the charging time, charging method and characteristics. Several charging scenarios are considered for EVs’ integration into the utility grid regarding power demand, voltage profile, power quality and system adequacy. A lookup-table-based charging approach for EVs is proposed for impact analysis, while considering a large-scale integration. It is observed that the bus voltage and line current are affected during high-level charging and discharging of the EVs. The residential grid voltage sag increases by about 1.96% to 1.77%, 2.21%, 1.96 to 1.521% and 1.93% in four EV-charging profiles, respectively. The finding of this work can be adopted in designing optimal charging/discharging of EVs to minimize the impacts on bus voltage and line current.
Publisher: MDPI AG
Date: 08-08-2021
DOI: 10.3390/EN14164829
Abstract: High-voltage direct current (HVDC) has received considerable attention due to several advantageous features such as minimum transmission losses, enhanced stability, and control operation. An appropriate model of HVDC is necessary to assess the operating conditions as well as to analyze the transient and steady-state stabilities integrated with the AC networks. Nevertheless, the construction of an HVDC model is challenging due to the high computational cost, which needs huge ranges of modeling experience. Therefore, advanced dynamic modeling of HVDC is necessary to improve stability with minimum power loss. This paper presents a comprehensive review of the various dynamic modeling of the HVDC transmission system. In line with this matter, an in-depth investigation of various HVDC mathematical models is carried out including average-value modeling (AVM), voltage source converter (VSC), and line-commutated converter (LCC). Moreover, numerous stability assessment models of HVDC are outlined with regard to stability improvement models, current-source system stability, HVDC link stability, and steady-state rotor angle stability. In addition, the various control schemes of LCC-HVDC systems and modular multilevel converter- multi-terminal direct current (MMC-MTDC) are highlighted. This paper also identifies the key issues, the problems of the existing HVDC models as well as providing some selective suggestions for future improvement. All the highlighted insights in this review will hopefully lead to increased efforts toward the enhancement of the modeling for the HVDC system.
Publisher: MDPI AG
Date: 19-01-2023
DOI: 10.3390/ELECTRONICS12030523
Abstract: A self-regulated phase estimator (SRPE)-based DQ algorithm for a DC-AC converter with dynamic voltage restoring (DVR) ability is presented in this paper. When compared to the conventional phase-locked loop (PLL), the provided controller can significantly reduce phase distortions and low-order harmonics from the load voltage while attaining quicker dynamic response. Furthermore, the fundamental attribute of the load voltage allows the integrated DC-AC converter to operate at a consistent frequency eliminating frequency oscillations. The SRPE is utilized primarily in the DQ control theory as the reference voltage generator which can compensate for the grid voltage. SRPE has good band-pass filtering properties and a mathematically simple structure that can thoroughly attenuate voltage imbalance and has quick dynamic response. The SRPE has been made to be frequency-adaptive using a d ing factor and robust grid frequency estimation. The SRPE can maintain the fundamental frequency at 50 Hz and keep the total harmonic distortions (THD) within the 5% limit even during grid disruptions. The DC-AC converter and SRPE-DQ’s stability are thoroughly examined. The experiment is carried out to show the efficacy of the suggested complete control system. There are also comparative simulation studies to show the benefits of the suggested technique. The results reveal that the suggested approach can immediately identify and correct for any grid voltage imbalance while also assisting in maintaining the constant voltage at the load side despite voltage sag/swell and distortions.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Publisher: MDPI AG
Date: 11-05-2023
DOI: 10.3390/EN16104034
Abstract: Energy generation from renewable sources is a global trend due to the carbon emissions generated by fossil fuels, which cause serious harm to the ecosystem. As per the long-term goals of the ASEAN countries, the Malaysian government established a target of 31% renewable energy generation by 2025 to facilitate ongoing carbon emission reductions. To reach the goal, a large-scale solar auction is one of the most impactful initiatives among the four potential strategies taken by the government. To assist the Malaysian government’s large-scale solar policy as detailed in the national renewable energy roadmap, this article investigated the techno-economic and feasibility aspects of a 10 MW floating solar PV system at UMP Lake. The PVsyst 7.3 software was used to develop and compute energy production and loss estimation. The plant is anticipated to produce 17,960 MWh of energy annually at a levelized cost of energy of USD 0.052/kWh. The facility requires USD 8.94 million in capital costs that would be recovered within a payback period of 9.5 years from the date of operation. The plant is expected to reduce carbon emissions by 11,135.2 tons annually. The proposed facility would ensure optimal usage of UMP Lake and contribute to the Malaysian government’s efforts toward sustainable growth.
Publisher: MDPI AG
Date: 12-11-2019
DOI: 10.3390/ELECTRONICS8111335
Abstract: This paper presents the development of fuzzy-based inverter controller for photovoltaic (PV) application to avoid the nonlinearity characteristic and fluctuations of PV inverter output. The fuzzy-based controller algorithm is employed in the PV inverter control system to optimize the duty cycles of the insulated-gate bipolar transistors (IGBTs) and to enhance the inverter outputs with lower harmonic contents and unity power factor. The developed fuzzy-based PV inverter controller is implemented in the MATLAB/Simulink models and experimentally tested in a dSPACE DS1104 process controller. The obtained simulation result of the developed fuzzy-based PV inverter controller is validated with experimental results under different performance conditions. It is seen that the experimental results of the switching signals, inverter voltage and current, control parameters, and total harmonic distortion (THD) of load current and output voltage of the PV inverter are closely matched with that of the simulation results. To validate the inverter performance, the proposed fuzzy-based PV inverter controller outperforms other studies with a voltage THD of 2.5% and a current THD of 3.5% with unity power factor.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2022
Publisher: MDPI AG
Date: 05-11-2022
Abstract: Electric vehicles (EVs) have received widespread attention in the automotive industry as the most promising solution for lowering CO2 emissions and mitigating worldwide environmental concerns. However, the effectiveness of EVs can be affected due to battery health degradation and performance deterioration with lifespan. Therefore, an advanced and smart battery management technology is essential for accurate state estimation, charge balancing, thermal management, and fault diagnosis in enhancing safety and reliability as well as optimizing an EV’s performance effectively. This paper presents an analytical and technical evaluation of the smart battery management system (BMS) in EVs. The analytical study is based on 110 highly influential articles using the Scopus database from the year 2010 to 2020. The analytical analysis evaluates vital indicators, including current research trends, keyword assessment, publishers, research categorization, country analysis, authorship, and collaboration. The technical assessment examines the key components and functions of BMS technology as well as state-of-the-art methods, algorithms, optimization, and control surgeries used in EVs. Furthermore, various key issues and challenges along with several essential guidelines and suggestions are delivered for future improvement. The analytical analysis can guide future researchers in enhancing the technologies of battery energy storage and management for EV applications toward achieving sustainable development goals.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: MDPI AG
Date: 09-02-2023
DOI: 10.3390/MATH11040886
Abstract: Due to the significant number of distributed generators in the electric power system, islanding detection requirements are becoming an increasingly prominent aspect of the power system. The island detection system depends on accurate threshold determination since an incorrect threshold might result in a hazardous situation. To evaluate the proposed method’s capacity to discriminate between different events, this study examined different unintentional islanding conditions such as under frequency and over frequency. The purpose of this study is to establish the threshold of the under and over frequency island conditions. The under frequency island condition happens when the distributed generator (DG) capacity exceeds the amount of connected load on the other hand, the over frequency island condition happens during a higher connected load compared to the capacity of the DG. The contribution of this research is to propose an unintentional island threshold setting technique based on bus voltage angle difference data of the phasor measurement unit (PMU). In the PowerWorld simulator, the Utility Kerteh (location: Terengganu, Malaysia) bus system has been designed and simulated in this work. The test system has four distinct islanding scenarios under two conditions, and the performance of the proposed methods demonstrates that for the under frequency islanding conditions the scenario’s threshold can be taken at a minimum of 40 milliseconds (ms) and a maximum of 60 ms, while the over frequency condition island threshold can be placed at a minimum of 60 ms and a maximum of 80 ms depending on the scenarios. Therefore, the proposed technique will be contributed to increase the reliability of the overall distribution grid so the unintentional island can be detected faster in terms of time.
Publisher: Elsevier BV
Date: 03-2023
Publisher: Elsevier BV
Date: 12-2018
Publisher: MDPI AG
Date: 25-04-2023
DOI: 10.3390/SU15097157
Abstract: Fuel cells have drawn a lot of interest in recent years as one of the most promising alternative green power sources in microgrid systems. The operating conditions and the integrated components greatly impact the quality of the fuel cell’s voltage. Energy management techniques are required in this regard to regulate the fuel cell’s power in a microgrid. The active/reactive power in the microgrid should be adjusted in line with US Energy Star’s regulations whereas the grid current needs to follow the standard set by IEEE 519 2014 to enhance the power quality of the electrical energy injected into the microgrid. Uncontrolled energy injection from the fuel cell can have serious impacts including superfluous energy demand, overloading, and power losses, especially in high power and medium voltage systems. Although fuel cells have many advantages, they cannot yet produce high voltages in idually to compensate for the demand of a microgrid system. Due to these reasons, the fuel cell must be interfaced with a DC-DC converter. This research proposes a novel high voltage gain converter integrated 1.26 kW fuel cell for microgrid power management that can boost the fuel cell’s voltage up to 20 times. Due to this high voltage gain, the voltage and current ripple of the fuel cell is also reduced substantially. According to the analysis, the proposed converter demonstrated optimal performance when compared to the other converters due to its high voltage gain and extremely low voltage ripple. As a result, the harmonic profile of the microgrid current persists with a reduced THD of 3.22% and a very low voltage ripple of 4 V. To validate the converter’s performance, along with extensive simulation, a hardware prototype was also built. The voltage of the fuel cell is regulated using a simplified proportional integral controller. The operating principle of the converter integrated fuel cell along with its application in microgrid power management is demonstrated. A comparative analysis is also shown to verify how the proposed converter is improving the system’s performance when compared against other converters.
Publisher: Elsevier BV
Date: 08-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: MDPI AG
Date: 21-07-2022
DOI: 10.3390/SU14148921
Abstract: To meet the zero-carbon electricity generation target as part of the sustainable development goals (SDG7), remote industrial microgrids worldwide are considering the uptake of more and more renewable energy resources, especially solar PV systems. Estimating the grid PV hosting capacity plays an essential role in designing and planning such microgrids. PV hosting capacity assessment determines the maximum PV capacity suitable for the grid and the appropriate electrical location for PV placement. This research reveals that conventional static criteria to assess the PV hosting capacity fail to ensure the grid’s operational robustness. It hence demands a reduction in the theoretical hosting capacity estimation to ensure grid compatible post-fault voltage and frequency recovery. Energy storage technologies, particularly fast-responsive batteries, can potentially prevent such undesirable scenarios nevertheless, careful integration is required to ensure an affordable cost of energy. This study proposes a novel methodical techno-economic approach for an off-grid remote industrial microgrid to enhance the PV hosting capacity by integrating battery energy storage considering grid disturbance and recovery scenarios. The method has been validated in an industrial microgrid with a 2.6 MW peak demand in a ready-made garment (RMG) factory having a distinctive demand pattern and unique constraints in remote Bangladesh. According to the analysis, integrating 2.5 MW of PV capacity and a 1.2 MVA battery bank to offset existing diesel and grid consumption would result in an energy cost of BDT 14.60 per kWh (USD 0.1719 per kWh). For high PV penetration scenarios, the application of this method offers higher system robustness, and the financial analysis indicates that the industries would not only benefit from positive environmental impact but also make an economic profit.
Publisher: MDPI AG
Date: 07-09-2022
Abstract: Recently, electric vehicle (EV) technology has received massive attention worldwide due to its improved performance efficiency and significant contributions to addressing carbon emission problems. In line with that, EVs could play a vital role in achieving sustainable development goals (SDGs). However, EVs face some challenges such as battery health degradation, battery management complexities, power electronics integration, and appropriate charging strategies. Therefore, further investigation is essential to select appropriate battery storage and management system, technologies, algorithms, controllers, and optimization schemes. Although numerous studies have been carried out on EV technology, the state-of-the-art technology, progress, limitations, and their impacts on achieving SDGs have not yet been examined. Hence, this review paper comprehensively and critically describes the various technological advancements of EVs, focusing on key aspects such as storage technology, battery management system, power electronics technology, charging strategies, methods, algorithms, and optimizations. Moreover, numerous open issues, challenges, and concerns are discussed to identify the existing research gaps. Furthermore, this paper develops the relationship between EVs benefits and SDGs concerning social, economic, and environmental impacts. The analysis reveals that EVs have a substantial influence on various goals of sustainable development, such as affordable and clean energy, sustainable cities and communities, industry, economic growth, and climate actions. Lastly, this review delivers fruitful and effective suggestions for future enhancement of EV technology that would be beneficial to the EV engineers and industrialists to develop efficient battery storage, charging approaches, converters, controllers, and optimizations toward targeting SDGs.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Publisher: MDPI AG
Date: 21-09-2021
DOI: 10.3390/MI12091133
Abstract: This research proposes a three-phase six-level multilevel inverter depending on twelve-switch three-phase Bridge and multilevel DC-link. The proposed architecture increases the number of voltage levels with less power components than conventional inverters such as the flying capacitor, cascaded H-bridge, diode-cl ed and other recently established multilevel inverter topologies. The multilevel DC-link circuit is constructed by connecting three distinct DC voltage supplies, such as single DC supply, half-bridge and full-bridge cells. The purpose of both full-bridge and half-bridge cells is to provide a variable DC voltage with a common voltage step to the three-phase bridge’s mid-point. A vector modulation technique is also employed to achieve the desired output voltage waveforms. The proposed inverter can operate as a six-level or two-level inverter, depending on the magnitude of the modulation indexes. To guarantee the feasibility of the proposed configuration, the proposed inverter’s prototype is developed, and the experimental results are provided. The proposed inverter showed good performance with high efficiency of 97.59% following the IEEE 1547 standard. The current harmonics of the proposed inverter was also minimized to only 5.8%.
Publisher: Elsevier BV
Date: 04-2022
Publisher: Elsevier BV
Date: 04-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: MDPI AG
Date: 13-02-2022
DOI: 10.3390/ELECTRONICS11040562
Abstract: Globally, the research on electric vehicles (EVs) has become increasingly popular due to their capacity to reduce carbon emissions and global warming impacts. The effectiveness of EVs depends on appropriate functionality and management of battery energy storage. Nevertheless, the battery energy storage in EVs provides an unregulated, unstable power supply and has significant voltage drops. To address these concerns, power electronics converter technology in EVs is necessary to achieve a stable and reliable power transmission. Although various EV converters provide significant contributions, they have limitations with regard to high components, high switching loss, high current stress, computational complexity, and slow dynamic response. Thus, this paper presents the emerging trends in analytical assessment of power electronics converter technology incorporated energy storage management in EVs. Hundreds (100) of the most significant and highly prominent articles on power converters for EVs are studied and investigated, employing the Scopus database under predetermined factors to explore the emerging trends. The results reveal that 57% of articles emphasize modeling, experimental work, and performance evaluation. In comparison, 13% of papers are based on problem formulation and simulation analysis, and 8% of articles are survey, case studies, and review-based. Besides, four countries, including China, India, the United States, and Canada, are dominant to publish the maximum articles, indicating 33, 17, 14, and 13, respectively. This review adopts the analytical assessment that outlines various power converters, energy storage, controller, optimization, energy efficiency, energy management, and energy transfer, emphasizing various schemes, key contributions, and research gaps. Besides, this paper discusses the drawbacks and issues of the various power converters and highlights future research opportunities to address the existing limitations. This analytical assessment could be useful to EV engineers and automobile companies towards the development of advanced energy storage management interfacing power electronics for sustainable EV applications.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: MDPI AG
Date: 19-11-2021
DOI: 10.3390/SU132212800
Abstract: Concerns over growing greenhouse gas (GHG) emissions and fuel prices have prompted researchers to look into alternative energy sources, notably in the transportation sector, accounting for more than 70% of carbon emissions. An increasing amount of research on electric vehicles (EVs) and their energy management schemes (EMSs) has been undertaken extensively in recent years to address these concerns. This article aims to offer a bibliometric analysis and investigation of optimized EMSs for EV applications. Hundreds (100) of the most relevant and highly influential manuscripts on EMSs for EV applications are explored and examined utilizing the Scopus database under predetermined parameters to identify the most impacting articles in this specific field of research. This bibliometric analysis provides a survey on EMSs related to EV applications focusing on the different battery storages, models, algorithms, frameworks, optimizations, converters, controllers, and power transmission systems. According to the findings, more articles were published in 2020, with a total of 22, as compared to other years. The authors with the highest number of manuscripts come from four nations, including China, the United States, France, and the United Kingdom, and five research institutions, with these nations and institutions accounting for the publication of 72 papers. According to the comprehensive review, the current technologies are more or less capable of performing effectively nevertheless, dependability and intelligent systems are still lacking. Therefore, this study highlights the existing difficulties and challenges related to EMSs for EV applications and some brief ideas, discussions, and potential suggestions for future research. This bibliometric research could be helpful to EV engineers and to automobile industries in terms of the development of cost-effective, longer-lasting, hydrogen-compatible electrical interfaces and well-performing EMSs for sustainable EV operations.
Publisher: MDPI AG
Date: 22-05-2023
DOI: 10.3390/SU15108405
Abstract: Boost converters and multilevel inverters (MLI) are frequently included in low-voltage solar photovoltaic (PV) systems for grid integration. However, the use of an inductor-based boost converter makes the system bulky and increases control complexity. Therefore, the switched-capacitor-based MLI emerges as an efficient DC/AC voltage convertor with boosting capability. To make classical topologies more efficient and cost-effective for sustainable power generation, newer topologies and control techniques are continually evolving. This paper proposes a reduced-component-count five-level inverter design for generating stable AC voltages for sustainable grid-integrated solar photovoltaic applications. The proposed topology uses seven switching devices of lower total standing voltage (TSV), three diodes, and two DC-link capacitors to generate five-level outputs. By charging and discharging cycles, the DC capacitor voltages are automatically balanced. Thus, no additional sensors or control circuitry is required. It has inherent voltage-boosting capability without any input boost converter. A low-frequency-based half-height (HH) modulation technique is employed in the standalone system for better voltage quality. Extensive simulations are performed in a MATLAB/Simulink environment to estimate the performance of the proposed topology, and 17.58% THDs are obtained in the phase voltages. Using a small inductor in series or an inductive load, the current THD reduces to 8.23%. Better dynamic performance is also observed with different loading conditions. A miniature five-level single-phase laboratory prototype is developed to verify the accuracy of the simulation results and the viability of the proposed topology.
Publisher: MDPI AG
Date: 27-11-2021
DOI: 10.3390/MI12121466
Abstract: In this paper, the performance of an active neutral point cl ed (ANPC) inverter is evaluated, which is developed utilizing both silicon (Si) and gallium trioxide (Ga2O3) devices. The hybridization of semiconductor devices is performed since the production volume and fabrication of ultra-wide bandgap (UWBG) semiconductors are still in the early-stage, and they are highly expensive. In the proposed ANPC topology, the Si devices are operated at a low switching frequency, while the Ga2O3 switches are operated at a higher switching frequency. The proposed ANPC mitigates the fault current in the switching devices which are prevalent in conventional ANPCs. The proposed ANPC is developed by applying a specified modulation technique and an intelligent switching arrangement, which has further improved its performance by optimizing the loss distribution among the Si/Ga2O3 devices and thus effectively increases the overall efficiency of the inverter. It profoundly reduces the common mode current stress on the switches and thus generates a lower common-mode voltage on the output. It can also operate at a broad range of power factors. The paper extensively analyzed the switching performance of UWBG semiconductor (Ga2O3) devices using double pulse testing (DPT) and proper simulation results. The proposed inverter reduced the fault current to 52 A and achieved a maximum efficiency of 99.1%.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2020
Publisher: ACTAPRESS
Date: 2012
Publisher: Elsevier BV
Date: 11-2022
Publisher: Elsevier BV
Date: 06-2023
Publisher: Springer Science and Business Media LLC
Date: 10-2021
DOI: 10.1038/S41598-021-98915-8
Abstract: Accurate state of charge (SOC) estimation of lithium-ion (Li-ion) batteries is crucial in prolonging cell lifespan and ensuring its safe operation for electric vehicle applications. In this article, we propose the deep learning-based transformer model trained with self-supervised learning (SSL) for end-to-end SOC estimation without the requirements of feature engineering or adaptive filtering. We demonstrate that with the SSL framework, the proposed deep learning transformer model achieves the lowest root-mean-square-error (RMSE) of 0.90% and a mean-absolute-error (MAE) of 0.44% at constant ambient temperature, and RMSE of 1.19% and a MAE of 0.7% at varying ambient temperature. With SSL, the proposed model can be trained with as few as 5 epochs using only 20% of the total training data and still achieves less than 1.9% RMSE on the test data. Finally, we also demonstrate that the learning weights during the SSL training can be transferred to a new Li-ion cell with different chemistry and still achieve on-par performance compared to the models trained from scratch on the new cell.
No related grants have been discovered for Dr Molla Shahadat Hossain Lipu.