Browsing by Author "Islam, Md. Kamrul"

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A systematic review of the nexus between climate change and social media: present status, trends, and future challenges
(Scopus, 2024-10-14) Sultana, Bebe Chand; Prodhan, Md. Tabiur Rahman; Alam, Edris; Sohel, Md. Salman; Bari, A. B. M. Mainul; Pal, Subodh Chandra; Islam, Abu Reza Md. Towfiqul; Islam, Md. Kamrul
: Social media and climate change are some of the most controversial issues of the 21st century. Despite numerous studies, our understanding of current social media trends, popular hot topics, and future challenges related to climate change remains significantly limited. This research presents a systematic review of climate change and social media for the first time. Review the studies published between 2009 and 2022 in places like Google Scholar, Science Direct, Web-of-Science, Scopus, ResearchGate, and others. For this systematic review, we found 1,057 articles. Forty-five articles were the most relevant according to our goals and study design, which followed the PRISMA framework. The results of this review demonstrate that Twitter is the most popular platform. Every year, we identify rising trends in the number of publications. Past studies often focused on just one social media site, like Twitter (n = 26) or Facebook (n = 5). Although most studies focus on the United States, the study area is primarily “all over the world.” This study offers a theoretical framework by examining the relationship between social media platforms and the discourse surrounding climate change. It looked into how social media trends influence public perception, raise awareness, and spur action on climate change. In practical terms, the study focuses on important and trending topics like nonbelievers and climate change. The contribution consists of synthesizing the body of research, providing insights into the state of the digital world, and suggesting future lines of inquiry for the field of social media and climate change studies. We highlighted the studies’ quality assessment result of “moderate quality.” This systematic review provides information about how climate change is now portrayed on social media and lays the groundwork for further study in this area.
A systematic review of the nexus between climate change and social media: present status, trends, and future challenges
(Scopus, 2024-10-14) Sultana, Bebe Chand; Prodhan, Md. Tabiur Rahman; Alam, Edris; Sohel, Md. Salman; Bari, A. B. M. Mainul; Pal, Subodh Chandra; Islam, Md. Kamrul; Islam, Abu Reza Md. Towfiqul
Social media and climate change are some of the most controversial issues of the 21st century. Despite numerous studies, our understanding of current social media trends, popular hot topics, and future challenges related to climate change remains significantly limited. This research presents a systematic review of climate change and social media for the first time. Review the studies published between 2009 and 2022 in places like Google Scholar, Science Direct, Web-of-Science, Scopus, ResearchGate, and others. For this systematic review, we found 1,057 articles. Forty-five articles were the most relevant according to our goals and study design, which followed the PRISMA framework. The results of this review demonstrate that Twitter is the most popular platform. Every year, we identify rising trends in the number of publications. Past studies often focused on just one social media site, like Twitter (n = 26) or Facebook (n = 5). Although most studies focus on the United States, the study area is primarily “all over the world.” This study offers a theoretical framework by examining the relationship between social media platforms and the discourse surrounding climate change. It looked into how social media trends influence public perception, raise awareness, and spur action on climate change. In practical terms, the study focuses on important and trending topics like nonbelievers and climate change. The contribution consists of synthesizing the body of research, providing insights into the state of the digital world, and suggesting future lines of inquiry for the field of social media and climate change studies. We highlighted the studies’ quality assessment result of “moderate quality.” This systematic review provides information about how climate change is now portrayed on social media and lays the groundwork for further study in this area.
Design and Cost Analysis of a Solar PV Storage System
(Daffodil International University, 2021) Islam, Md. Kamrul; Islam, Md. Azizul
When solar system was not invented there was no idea about renewable energy. But still that time scientist are try to discover something which is related to renewable energy. At the very first time French physicist Edmond Becquerel in 1839 invented the photovoltaic effect when he research with a cell made of metal electrodes in a conducting solution. He saw that the cell provides electrical energy when its exposed on light. Later in 1873 Willoughby Smith saw that selenium have a function of photoconductor. In 1883, American inventor Charles Fritz first time discovered modern solar system. From that time until now every researcher try to implement modern solar system. Solar energy has brought a massive change with us. Previously solar (PV) technologies were divided into smaller parts. It currently produces a large amount of electricity as it is connected to the grid. The price of solar technology is slowly coming down a lot compared to the previous 30 years. For example, the cost of high power band solar modules has decreased from about $27,000/kW in 1982 to about $4,000/kW in 2006. The installed cost of a PV system declined from $16,000/kW in 1992 to around $6,000/kW in 2008 (IEA-PVPS, 2007; Solarbuzz, 2006, Lazard 2009). The rapid expansion of the solar energy market can be attributed to a number of supportive policy instruments, the increased volatility of fossil fuel prices and the environmental externalities of fossil fuels, particularly greenhouse gas (GHG) emissions.
Design and development of web based e-learning and teacher assistant system for TVET (technical and vocational education and training) in Bangladesh
(Department of Technical and Vocational Education (TVE), Islamic University of Technology (IUT), 2014-11-15) Islam, Rezwanul; Islam, Md. Kamrul
The System will provide a best communication way for teaching learning system to need for our TVET (Technical and Vocational Education and Training) institutions. Especially the teachers and students can able to develop a good relationship between them. Teacher can make schedule of their class and teaching related activities and student also communicate with teachers and themselves by using chatting, blogging, emailing, collecting and sharing knowledge and others facilities. There have some other facilities like Project showcasing system for show the projects, innovation through this system. Student can download video tutorial, Project showcasing, other educational contents without any cost. Student can submit their valuable opinion about the tutorials
Dynamic Analysis of Grid-Connected Hybrid Wind Farm
(Institute of Advanced Engineering and Science (IAES), 2023-06) Akanto, Jannatul Mawa; Islam, Md. Kamrul; Jahan, Effat; Hazari, Md. Rifat; Mannan, Mohammad Abdul; Rahman, Md. Abdur
Since the last couple of years, the expansion of grid-connected wind farms (WFs) has increased dramatically. The wind turbine might be a fixed-speed squirrel cage induction generator (FSWT-SCIG) or a variable speed wind turbine with a doubly-fed induction generator (VSWT-DFIG). The main disadvantage of FSWT-SCIG is its lack of ability to adjust power quality. Inversely, the VSWT-DFIG is a competitive wind turbine technology that allows for the effective management of both active and reactive power outputs. Moreover, it has some extraordinary functionaries rather than FSWTSCIG. However, the major downside to this system is that it only has a partial rating AC/DC/AC power converter, which is extremely expensive. Hence, to reduce the overall cost combining the implementation of VSWT-DFIG and FSWT-SCIG in a WF could be a feasible alternative. Therefore, a novel DFIG control technique is proposed in this article, which can keep the connection point voltage of the hybrid WF stable during dynamic analysis. To evaluate the proposed controller responses PSCAD/EMTDC software has been used.
Effect of Shade Depth on Lea Strength, Weight Loss and Wash Fastness Properties of Reactive Dyed Cotton Yarn
(Daffodil International University, 2020-01) Disha, Fatima Binta Satter; Akter, Sharmin; Hossain, Md Arafat; Khatun, Murshida; Islam, Md. Kamrul; Farzana, Nawshin; Khatun, Mahmuda
Analysis of the change in lea strength, weight loss percentage and wash fastness properties of 100 percent cotton reactive dyed yarn with various shade depth (1% to 4%) is carried out to represent correlation between the specified yarn properties with shade depth change in two different yarn counts. It is observed that increase in shade depth increases the yarn lea strength but shows a decreasing rate in wash fastness and weight loss (%). Finer yarn shows wash fastness rating of 4/5 whereas coarser yarn shows higher value in weight loss (%) and yarn lea strength.
Enhancement of Polyester Dyeing Performance Integrating Ecological and Cost-Effective Auxiliaries
(Scopus, 2024-05-21) Islam, Md. Kamrul; Uddin, Zulhash; Repon, Md. Reazuddin
Disperse dyes, primarily used for dyeing synthetic fibres like polyester, are characterized by their poor solubility in water, which necessitates the use of dispersing agents; however, environmental concerns arise due to their low biodegradability and potential toxicity, thus posing significant challenges in waste management and pollution control. This study explores the dyeing performance of knitted polyester with dispersed dyes, employing natural auxiliaries as substitutes for conventional commercial chemicals to promote an environmentally friendly approach. Citric acid (derived from lemon), sodium citrate (prepared from citric acid and sodium bicarbonate), and glucose (extracted from date fruits) replace commercial acetic acid, dispersing agent, and hydrolyze. Dyeing is conducted using the high-temperature and high-pressure methods with consistent parameters. A comparative study of the dyeing performance of the natural auxiliaries with the existing commercial chemicals was assessed concerning colour strength, different fastness properties, and the FT-IR diagram. Proton NMR is utilized for the structural determination of date fruit and lemon components. UV-Vis spectral data show that adding sodium citrate to the dispersed dye solution drops the absorbance value from 1.1457 to 0.58916, confirming sodium citrate’s efficacy as a dispersing agent. With lower recipe costs, the environmentally friendly approach using natural auxiliaries exhibits comparable dyeing performance and excellent fastness properties, providing a sustainable alternative to traditional methods.
Fault Ride-Through and Transient Stability Augmentation of Grid-Connected PV Station Using Virtual Synchronous Generator
(AIUB Journal of Science and Engineering (AJSE), 2021-12-30) Islam, Md. Kamrul; Mannan, Mohammad Abdul; Hazari, Md. Rifat
Due to the extensive integration of renewable energy sources (RESs), i.e., photovoltaic (PV) system, the future power system is developing into an inverter-based system from a dominated alternator-based power system. This massive penetration of inverter-based PV system reduced the system inertia and damping characteristics of the power grid, impacting the fault ride-through (FRT) capability and causes frequency instability. Modern grid codes require that PV systems should work in the same way as conventional power plants and assist the system during transient state. However, most of the conventional inverter control mechanisms failed to fulfill the requirements of grid codes, especially when the penetration ratio of the PV system is close to the conventional unit. Therefore, this paper proposes a virtual synchronous generator (VSG) control mechanism of PV system inverter to augment FRT competency and frequency stability. The proposed VSG control system mimics the behavior of conventional power plants. To observe and evaluate the proposed controller behavior, simulation analyses were executed in the PSCAD/EMTDC software for both proposed and conventional controllers. The simulation results clearly indicate that the proposed VSG control system has sufficient damping characteristics to ensure FRT capability and frequency stability.
FRT and Transient Stability Augmentation of Grid-Connected PV Station Using Virtual Synchronous Generator
(American International University-Bangladesh (AIUB), 2021-12) Islam, Md. Kamrul; Mannan, Mohammad Abdul; Hazari, Md. Rifat
Due to the extensive integration of renewable energy sources (RESs), i.e., photovoltaic (PV) system, the future power system is developing into an inverter-based system from a dominated alternator-based power system. This massive penetration of inverter-based PV system reduced the system inertia and damping characteristics of the power grid, impacting the fault ride-through (FRT) capability and causes frequency instability. Modern grid codes require that PV systems should work in the same way as conventional power plants and assist the system during transient state. However, most of the conventional inverter control mechanisms failed to fulfill the requirements of grid codes, especially when the penetration ratio of the PV system is close to the conventional unit. Therefore, this paper proposes a virtual synchronous generator (VSG) control mechanism of PV system inverter to augment FRT competency and frequency stability. The proposed VSG control system mimics the behavior of conventional power plants. To observe and evaluate the proposed controller behavior, simulation analyses were executed in the PSCAD/EMTDC software for both proposed and conventional controllers. The simulation results clearly indicate that the proposed VSG control system has sufficient damping characteristics to ensure FRT capability and frequency stability.
Hydro-chemical Based Assessment of Groundwater Vulnerability in the Holocene Multi-aquifers of Ganges Delta
(Springer Nature, 2024-01-02) Saha, Asish; Pal, Subodh Chandra; Islam, Abu Reza Md. Towfiqul; Islam, Aznarul; Alam, Edris; Islam, Md. Kamrul
Determining the degree of high groundwater arsenic (As) and fluoride (F−) risk is crucial for successful groundwater management and protection of public health, as elevated contamination in groundwater poses a risk to the environment and human health. It is a fact that several non-point sources of pollutants contaminate the groundwater of the multi-aquifers of the Ganges delta. This study used logistic regression (LR), random forest (RF) and artificial neural network (ANN) machine learning algorithm to evaluate groundwater vulnerability in the Holocene multi-layered aquifers of Ganges delta, which is part of the Indo-Bangladesh region. Fifteen hydro-chemical data were used for modelling purposes and sophisticated statistical tests were carried out to check the dataset regarding their dependent relationships. ANN performed best with an AUC of 0.902 in the validation dataset and prepared a groundwater vulnerability map accordingly. The spatial distribution of the vulnerability map indicates that eastern and some isolated south-eastern and central middle portions are very vulnerable in terms of As and F− concentration. The overall prediction demonstrates that 29% of the areal coverage of the Ganges delta is very vulnerable to As and F− contents. Finally, this study discusses major contamination categories, rising security issues, and problems related to groundwater quality globally. Henceforth, groundwater quality monitoring must be significantly improved to successfully detect and reduce hazards to groundwater from past, present, and future contamination.
Outdoor performance analysis and prediction of photovoltaic modules using machine learning algorithm
(BRAC University, 2020-06) Islam, Md. Kamrul; Shawon, Md. Mehedi Hasan; Akter, Sumaiya; Ahmed, Sabbir; Rahman, Md. Mosaddequr
The objective of this study is to inspect the performance of the photovoltaic (PV) modules in different environmental conditions and to apply a machine learning algorithm for prediction analysis. Photovoltaic modules are very sensitive to weather conditions such as cloudy, rainy, sunny days. Hence, weather parameters, for example, Irradiance, temperature, humidity, air-pressure have an impact on PV modules performance. Two Mono-Silicon PV modules have been set up on a seven-storied building in Gabtoli, Dhaka to collect the environmental data. Among two PV modules, one module is cleaned regularly and the other module is not cleaned to observe the dust effect on PV modules performance. A weather station is designed using Raspberry Pi 3B+ modules where different sensors are used to collect both modules short circuit current as well as temperature, humidity, wind speed and air-pressure data. The data of the PV modules and the environmental parameters are being collected from the end of October 2019. Data from November 2019 to February 2020, are used to analyze the performance of these PV modules. Furthermore, a theoretical calculation is done to calculate the solar irradiance (Ideal and Experimental), PV modules power output and energy output. Moreover, one of the segments of machine learning that is neural network which is used to train the model based on the collected data so that a fruitful prediction can be done. An algorithm named Multi-Layer Perceptron (MLP) using Artificial Neural Network has been developed which can provide us with the PV modules energy output of a particular day or time based on the training dataset. The accuracy of the output depends on the training dataset but most importantly it depends on the correct parameters which have been shown in this study.
Production of Liquid Fuel from Rice Husk and Sawdust
(Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh, 2019-05) Islam, Md. Kamrul; Rahman, Prof. Dr. A. N. M. Mizanur
Energy is the key input to economic growth of a nation and there is a close relation between accessibility of energy and escalation in the quality of nation. As conventional energy sources are limited and will diminish in future after complete consumption, so it is the high time to deal with the renewable and non-conventional energy sources. The necessity of liquid fuel is not only in the transport sector rather it is required in industrial and power sector. Production of liquid fuel from ligno-cellulosic material is one of the sources of renewable energy. As Bangladesh is an agricultural country, rice husk and sawdust are the common sources among all sources of cellulosic material available in the country. In the present study, fermentation method is used to produce liquid fuel from rice husk and sawdust. For fermentation process simultaneous saccharification and fermentation (SSF) process being used. In the process, husk and sawdust was pretreated to neutralize it and then saccharification was carried out with cellulase enzyme with different proportion where temperature was maintained at around 37oC for 84 hours. Fermentation reagents were prepared by adding yeast, peptone and dextrose for yeast inoculums. Saccharified slurry was clutched to fermentation in a mixture of reagents and fermentation medium. The process was carried out for one day in aerobic condition and then next three days in anaerobic condition at a temperature of 35oC. After fermenting clear supernatant is obtained from centrifugation and then gas chromatography (GC) was performed on the product for estimation of ethanol. In the experimentation rice husk and enzyme mixture was added at the ratios of 2.5:1, 3:1 and 3.5:1 respectively. The yields of ethanol are respectively 9.55% (v/w), 8.73% (v/w) and 6.74% (v/w) from respective fermented liquid broth. Sawdust and enzyme ratio of 2.5:1 provide a very low about 1.23% (v/w) of ethanol. This shows that sawdust not prospective but rice husk is a prospective source of extraction of liquid fuel by fermentation.
Rabies control in Bangladesh and prediction of human rabies cases by 2030: a One Health approach
(Scopus, 2024-08) Ghosha, Sumon; Hasan, Mohammad Nayeem Hasan; Nathd, Nirmalendu Deb; Haidere, Najmul; Higgins, Daleniece; Islam, Md. Kamrul
Background Bangladesh is making progress toward achieving zero dog-mediated rabies deaths by 2030, a global goal set in 2015. Methods Drawing from multiple datasets, including patient immunisation record books and mass dog vaccination (MDV) databases, we conducted a comprehensive analysis between 2011 and 2023 to understand the effectiveness of rabies control programmes and predict human rabies cases in Bangladesh by 2030 using time-series forecasting models. We also compared rabies virus sequences from GenBank in Bangladesh and other South Asian countries. Findings The estimated dog population in Bangladesh was determined to be 1,668,140, with an average dog population density of 12.83 dogs/km2 (95% CI 11.14–14.53) and a human-to-dog ratio of 86.70 (95% CI 76.60–96.80). The MDV campaign has led to the vaccination of an average of 21,295 dogs (95% CI 18,654–23,935) per district annually out of an estimated 26,065 dogs (95% CI 22,898–29,230). A declining trend in predicted and observed human rabies cases has been identified, suggesting that Bangladesh is poised to make substantial progress towards achieving the ‘Zero by 30’ goal, provided the current trajectory continues. The phylogenetic analysis shows that rabies viruses in Bangladesh belong to the Arctic-like-1 group, which differs from those in Bhutan despite sharing a common ancestor. Interpretation Bangladesh's One Health approach demonstrated that an increase in MDV and anti-rabies vaccine (ARV) resulted in a decline in the relative risk of human rabies cases, indicating that eliminating dog-mediated human rabies could be achievable.
Rabies Control in Bangladesh and Prediction of Human Rabies Cases by 2030: A One Health Approach
(Wolters Kluwer Health, 2024-08-27) Ghosh, Sumon; Hasan, Mohammad Nayeem; Nath, Nirmalendu Deb; Haider, Najmul; Jones, Daleniece Higgins; Islam, Md. Kamrul; Rahaman, M. Mujibur; Mursalin, Hasan Sayedul; Mahmud, Nadim; Kamruzzaman, Md.; Rabby, Md. Fazlay; Kar, Shotabdi; Ullah, Sayed Mohammed; Shah, Md. Rashed Ali; Jahan, Afsana Akter; Rana, Sohel; Chowdhury, Sukanta; Uddin, Md. Jamal; Sunil, Thankam S.; Ahmed, Be-Nazir; Siddiqui, Umme Ruman; Kaisar, S. M. Golam; Islam, Md. Nazmul
Background Bangladesh is making progress toward achieving zero dog-mediated rabies deaths by 2030, a global goal set in 2015. Methods Drawing from multiple datasets, including patient immunisation record books and mass dog vaccination (MDV) databases, we conducted a comprehensive analysis between 2011 and 2023 to understand the effectiveness of rabies control programmes and predict human rabies cases in Bangladesh by 2030 using time-series forecasting models. We also compared rabies virus sequences from GenBank in Bangladesh and other South Asian countries. Findings The estimated dog population in Bangladesh was determined to be 1,668,140, with an average dog population density of 12.83 dogs/km2 (95% CI 11.14–14.53) and a human-to-dog ratio of 86.70 (95% CI 76.60–96.80). The MDV campaign has led to the vaccination of an average of 21,295 dogs (95% CI 18,654–23,935) per district annually out of an estimated 26,065 dogs (95% CI 22,898–29,230). A declining trend in predicted and observed human rabies cases has been identified, suggesting that Bangladesh is poised to make substantial progress towards achieving the ‘Zero by 30’ goal, provided the current trajectory continues. The phylogenetic analysis shows that rabies viruses in Bangladesh belong to the Arctic-like-1 group, which differs from those in Bhutan despite sharing a common ancestor. Interpretation Bangladesh's One Health approach demonstrated that an increase in MDV and anti-rabies vaccine (ARV) resulted in a decline in the relative risk of human rabies cases, indicating that eliminating dog-mediated human rabies could be achievable. Funding The study was supported by the Communicable Disease Control (CDC) Division of the Directorate General of Health Services (DGHS) of the People's Republic of Bangladesh.
Rabies Control in Bangladesh and Prediction of Human Rabies Cases by 2030: A One Health Approach
(Elsevier, 2024-07-23) Ghosha, Sumon; Hasan, Mohammad Nayeem; Nath, Nirmalendu Deb; Haider, Najmul; Jones, Daleniece Higgins; Islam, Md. Kamrul; Rahaman, M. Mujibur; Mursalin, Hasan Sayedul; Mahmud, Nadim; Kamruzzaman, Md.; Rabby, Md. Fazlay; Kar, Shotabdi; Ullah, Sayed Mohammed; Shah, Md. Rashed Ali; Jahan, Afsana Akter; Rana, Md. Sohel; Chowdhury, Sukanta; Uddin, Md. Jamal; Sunil, Thankam S.; Ahmed, Be-Nazir; Siddiqui, Umme Ruman; Kaisar, M. Golam; Islam
Background Bangladesh is making progress toward achieving zero dog-mediated rabies deaths by 2030, a global goal set in 2015. Methods Drawing from multiple datasets, including patient immunisation record books and mass dog vaccination (MDV) databases, we conducted a comprehensive analysis between 2011 and 2023 to understand the effectiveness of rabies control programmes and predict human rabies cases in Bangladesh by 2030 using time-series forecasting models. We also compared rabies virus sequences from GenBank in Bangladesh and other South Asian countries. Findings The estimated dog population in Bangladesh was determined to be 1,668,140, with an average dog population density of 12.83 dogs/km2 (95% CI 11.14–14.53) and a human-to-dog ratio of 86.70 (95% CI 76.60–96.80). The MDV campaign has led to the vaccination of an average of 21,295 dogs (95% CI 18,654–23,935) per district annually out of an estimated 26,065 dogs (95% CI 22,898–29,230). A declining trend in predicted and observed human rabies cases has been identified, suggesting that Bangladesh is poised to make substantial progress towards achieving the ‘Zero by 30’ goal, provided the current trajectory continues. The phylogenetic analysis shows that rabies viruses in Bangladesh belong to the Arctic-like-1 group, which differs from those in Bhutan despite sharing a common ancestor. Interpretation Bangladesh's One Health approach demonstrated that an increase in MDV and anti-rabies vaccine (ARV) resulted in a decline in the relative risk of human rabies cases, indicating that eliminating dog-mediated human rabies could be achievable. Funding The study was supported by the Communicable Disease Control (CDC) Division of the Directorate General of Health Services (DGHS) of the People's Republic of Bangladesh.
Spatiotemporal Analysis and Predicting Rainfall Trends in a Tropical Monsoon-Dominated Country Using Makesens and Machine Learning Techniques
(Springer Nature, 2023-08-25) Monir, Md. Moniruzzaman; Rokonuzzaman, Md.; Sarker, Subaran Chandra; Alam, Edris; Islam, Md. Kamrul; Islam, Abu Reza Md. Towfiqul
Spatiotemporal rainfall trend analysis as an indicator of climatic change provides critical information for improved water resource planning. However, the spatiotemporal changing behavior of rainfall is much less understood in a tropical monsoon-dominated country like Bangladesh. To this end, this research aims to analyze spatiotemporal variations in rainfall for the period 1980–2020 over Bangladesh at seasonal and monthly scales using MAKESENS, the Pettitt test, and innovative trend analysis. Multilayer Perception (MLP) neural network was used to predict the next 8 years' rainfall changes nationally in Bangladesh. To investigate the spatial pattern of rainfall trends, the inverse distance weighting model was adopted within the ArcGIS environment. Results show that mean annual rainfall is 2432.6 mm, of which 57.6% was recorded from July to August. The Mann–Kendall trend test reveals that 77% of stations are declining, and 23% have a rising trend in the monthly rainfall. More than 80% of stations face a declining trend from November to March and August. There is a declining trend for seasonal rainfall at 82% of stations during the pre-monsoon, 75% during the monsoon, and 100% during the post-monsoon. A significant decline trend was identified in the north-center during the pre-monsoon, the northern part during the monsoon, and the southern and northwestern portions during the post-monsoon season. Predicted rainfall by MLP till 2030 suggests that there will be little rain from November to February, and the maximum fluctuating rainfall will occur in 2025 and 2027–2029. The ECMWF ERA5 reanalysis data findings suggested that changing rainfall patterns in Bangladesh may have been driven by rising or reducing convective precipitation rates, low cloud cover, and inadequate vertically integrated moisture divergence. Given the shortage of water resources and the anticipated rise in water demand, the study's findings have some implications for managing water resources in Bangladesh.
Virtual Synchronous Generator Control of Stand-Alone PV Station to Enhance Voltage Stability
(IEEE, 2021-10-04) Islam, Md. Kamrul; Mannan, Mohammad Abdul; Hazari, Md.Rifat
With the increasing integration of renewable energy resources (RESs) like photovoltaic (PV) systems to the rural consumer may affect the voltage stability during network disturbance situations. This is due to the fact that the conventional inverter system of the PV station cannot inject sufficient reactive power at a transient state. Therefore, to solve this issue, this paper proposes a virtual synchronous generator (VSG) control mechanism of the PV system to enhance voltage stability. The proposed VSG emulates the behavior of conventional power plants and control the reactive power more effectively during the network disturbance event. To justify the validity of the proposed VSG control PV system, simulation analysis, and comparison study has been done with the conventional control mechanism of the PV system.
Virtual Synchronous Generator Control of Stand-Alone PV Station to Enhance Voltage Stability
(IEEE, 2021-10) Islam, Md. Kamrul; Mannan, Mohammad Abdul; Hazari, Md. Rifat
With the increasing integration of renewable energy resources (RESs) like photovoltaic (PV) systems to the rural consumer may affect the voltage stability during network disturbance situations. This is due to the fact that the conventional inverter system of the PV station cannot inject sufficient reactive power at a transient state. Therefore, to solve this issue, this paper proposes a virtual synchronous generator (VSG) control mechanism of the PV system to enhance voltage stability. The proposed VSG emulates the behavior of conventional power plants and control the reactive power more effectively during the network disturbance event. To justify the validity of the proposed VSG control PV system, simulation analysis, and comparison study has been done with the conventional control mechanism of the PV system.