Publications
publications by categories in reversed chronological order.
2024
- Techno-Economic Assessment and Environmental Impact Analysis of Hybrid Storage System Integrated MicrogridArafat Ibne Ikram, Md Shafiullah, Md. Rashidul Islam, and 1 more authorArabian Journal for Science and Engineering, 2024
Microgrids are designed to utilize renewable energy resources (RER) that are revolutionary choices in reducing the environmental effect while producing electricity. The RER intermittency poses technical and economic challenges for the microgrid systems that can be overcome by utilizing the full potential of hybrid energy storage systems (HESS). A microgrid comprising of a solar photovoltaic panel, wind turbine, lead-acid battery, electrolyzer, fuel cell, and hydrogen (H ) tank is considered for techno-economic feasibility and environmental impact assessment on a grid integration scenario. Mathematical functions are utilized to model the components for estimating annual hourly renewable generation and energy storage behavior. The load consumption model for 50 homes is generated using Gaussian distribution to incorporate the uncertainty. Optimal sizing of the microgrid components is determined using the particle swarm optimization (PSO) algorithm to minimize the upfront installation cost and levelized cost of energy (LCOE). Different energy storage penetration scenarios, e.g., 25%, 50%, 75%, and 100% for the microgrid system, are considered where 100% penetration level stands for maintaining the load demand using the available resources without depending on the grid energy supply. The lowest LCOE is found between 0.06 /kWh and 0.11 /kWh, and the highest annual GHG is reduced to half compared to the grid emission. GHG is imposed around 62.14 (tCO2e/yr) - 73.57 (tCO2e/yr) for Madrid and Seville, respectively.
@article{ikram2024techno, title = {Techno-Economic Assessment and Environmental Impact Analysis of Hybrid Storage System Integrated Microgrid}, author = {Ikram, Arafat Ibne and Shafiullah, Md and Islam, Md. Rashidul and Rocky, Md. Kamruzzaman}, journal = {Arabian Journal for Science and Engineering}, publisher = {Springer Science and Business Media LLC}, url = {http://dx.doi.org/10.1007/s13369-024-08735-x}, doi = {10.1007/s13369-024-08735-x}, issn = {2193-567X}, number = {12}, volume = {49}, pages = {15917--15934}, year = {2024}, } - Optimizing energy consumption in smart homes: Load scheduling approachesArafat Ibne Ikram, Aasim Ullah, Durjoy Datta, and 2 more authorsIET Power Electronics, 2024
Rising fuel prices, global warming, and environmental damage are leading to increased demand for rooftop solar energy systems connected to the power grid. The development of smart grids, modern metering systems, and energy management could promote energy conservation in households. In this study, two different meta-heuristic optimization techniques were employed to schedule the shiftable load in suitable hours for decreasing electricity costs and minimizing peak to average ratio in a smart home while maintaining optimum user comfort. For power generation and storing energy, a grid-connected residential load with rooftop solar panels, a battery, and an inverter is considered. First, the problem is theoretically described using a load model and an objective function, with the primary goal of reducing power costs by moving the time of usage for certain home appliances. Simulations validate the proposed strategies, which effectively reduce power costs by 4.5% by shifting the time of use, with both optimization algorithms showing similar output. The residential electricity cost before optimization was 507.12 BDT/day, which decreased to 484.33 BDT/day after optimization without compromising load turn-off.
@article{ikram2024optimizing, title = {Optimizing energy consumption in smart homes: Load scheduling approaches}, author = {Ikram, Arafat Ibne and Ullah, Aasim and Datta, Durjoy and Islam, Ashraful and Ahmed, Tanvir}, journal = {IET Power Electronics}, publisher = {Institution of Engineering and Technology (IET)}, language = {en}, url = {http://dx.doi.org/10.1049/pel2.12663}, doi = {10.1049/pel2.12663}, issn = {1755-4535}, volume = {17}, number = {16}, pages = {2656-2668}, date = {2024-01-30}, year = {2024}, eprint = {https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/pel2.12663}, } - Performance Analysis of Machine Learning-Based Traditional and Ensemble Techniques for Smart Grid Stability PredictionMd Shakib Hassan, Arafat Ibne Ikram, MD Adnan Siddique, and 1 more authorIn 2024 6th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT), 2024
This Paper received the Top-10 Best Student Paper Award IEEE-ICEEICT 24 for the novel apporach of using ensemble-learning method to forecast the smart grid stability using historical datasets.*
A smart grid is integral to the digitalized transformation of the electricity sector, employing self-sufficient systems that integrate information, telecommunication, and advanced power technologies. Artificial Intelligence (AI), particularly Machine Learning (ML), plays a crucial role in overcoming the limitations of traditional modeling techniques. ML enables intelligent decision-making in response to dynamic factors like changing customer energy demands or disruptions in power supply within smart grids. This paper compares Machine Learning-Based Traditional and Ensemble techniques for predicting smart grid stability, utilizing an augmented dataset from Kaggle. For optimization, various classifiers and Ensemble Techniques, including Bagging, Boosting, Stacking, and Voting, were implemented with hyperparameter tuning. The experimental study highlights that ML-based Ensemble Techniques, with optimized parameters, outperform individual traditional techniques, showcasing higher accuracy and overall superior performance. A comprehensive comparative analysis based on evaluation metrics such as accuracy, precision, recall, F1-score, and ROC emphasizes the potential of these techniques to enhance the efficiency of predicting smart grid stability.
@inproceedings{hassan2024performance, title = {Performance Analysis of Machine Learning-Based Traditional and Ensemble Techniques for Smart Grid Stability Prediction}, author = {Hassan, Md Shakib and Ikram, Arafat Ibne and Siddique, MD Adnan and Mohammad, Nur}, booktitle = {2024 6th International Conference on Electrical Engineering and Information \& Communication Technology (ICEEICT)}, pages = {1020--1025}, year = {2024}, organization = {IEEE}, doi = {10.1109/ICEEICT62016.2024.10534560}, url = {https://doi.org/10.1109/ICEEICT62016.2024.10534560}, } - A Highly Efficient Wide-Angle Symmetric Meta-Absorber in Visible to Near-InfraredMd Raihan, SEA Himu, Kazi Mohammed Abdullah, and 4 more authorsIn 2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems (iCACCESS), 2024
Absorber working in optical wavelength draws significant attraction due to its vast field of application. A high-efficiency metamaterial absorber (MMA) is proposed in this study to utilize solar radiation perfectly. The MMA achieves 97.5% of total average absorption for the wavelength 375 nm to 1000 nm. From 375 to 700 nm (visible band) it achieves 97.47% average absorption. This symmetrical meta-structure is polarization insensitive along with the independence of angular sensitivity up to 70°. Recent developments are discussed on the attainment of several desired absorber characteristics, including flexibility, tunability, polarization and angle independence, and broadband and multiband operation. Additionally, recommendations for future lines of inquiry are provided.
@inproceedings{raihan2024highly, title = {A Highly Efficient Wide-Angle Symmetric Meta-Absorber in Visible to Near-Infrared}, author = {Raihan, Md and Himu, SEA and Abdullah, Kazi Mohammed and Parves, Md Shahazan and Tabassum, Tasneem and Ashaduzzaman, Kazi and Ikram, Arafat Ibne}, booktitle = {2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems (iCACCESS)}, pages = {1--5}, year = {2024}, organization = {IEEE}, doi = {10.1109/iCACCESS61735.2024.10499621}, url = {https://doi.org/10.1109/iCACCESS61735.2024.10499621}, } - Electrical Power Quality Disturbances Detection in Transmission Lines Using Machine Learning-Enabled ClassifierArafat Ibne Ikram, Md Shakib Hassan, and Nurjahan AkterIn 2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems (iCACCESS), 2024
There are increasing concerns about power quality disturbances (PQDs) at many phases of energy generation, transformation, distribution, and consumption due to the increasing interconnection of various energy systems. The basis for addressing PQDs is the automatic categorization of voltage or phase angle disturbances. According to a usual standpoint, the three distinct steps of signal analysis, feature selection, and classification should be used to separate the detection of issues with power quality. Nevertheless, signal analysis possesses several inherent deficiencies, mostly stemming from the laborious and inaccurate process of human feature selection. Consequently, this results in diminished classification accuracy when dealing with many disturbances and a compromised ability to withstand disruptive interference. This study focuses on the identification and categorization of PQD using a machine learning-based classifier, taking into account the features of the power quality problems problem, eight different features are taken from the voltage data and used to figure out what caused each PQD. Various types of machine learning models are employed to analyze the dataset, and the effectiveness of the machine learning classifier is assessed by validating its performance using a separate test dataset. Once the machine learning classifier model can classify the disturbances types with 96% accuracy. The proposed classifiers can effectively detect disturbances in the transmission line.
@inproceedings{ikram2024electrical, title = {Electrical Power Quality Disturbances Detection in Transmission Lines Using Machine Learning-Enabled Classifier}, author = {Ikram, Arafat Ibne and Hassan, Md Shakib and Akter, Nurjahan}, booktitle = {2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems (iCACCESS)}, pages = {1--6}, year = {2024}, organization = {IEEE}, doi = {10.1109/iCACCESS61735.2024.10499454}, url = {https://doi.org/10.1109/iCACCESS61735.2024.10499454}, }
2023
- Revolutionizing Consumer Power Management: Unveiling Power Grid Feasibility Analysis Using Machine LearningMinhazur Rahman, Sheik Erfan Ahmed Himu, Abdullah Al Shahid Chowdhury, and 4 more authorsIn 2023 10th IEEE International Conference on Power Systems (ICPS), 2023
As distributed energy sources become more prevalent, maintaining power grid stability is increasingly challenging. By integrating machine intelligence and communication technologies, traditional power networks could transform into smart grids. Through machine learning and artificial intelligence, these smart grids can adeptly respond to unexpected changes in consumer demand, power interruptions, surges in renewable energy production, and other crucial situations. Variations in power generation and loads, along with changes in the power system’s structure, lead to varying shifts in the entire network’s active power. Detecting these fluctuations through manual analysis is laborious, but machine learning can be highly impactful in this regard. This study aims to collect comprehensive data for analyzing grid stability, utilizing machine learning tools to thoroughly examine the data, and adopting a multimodal approach to compare model outcomes for an improved solution strategy. Our analysis reveals an accuracy exceeding 97%, indicating strong potential for practical application and implications.
@inproceedings{rahman2023revolutionizing, title = {Revolutionizing Consumer Power Management: Unveiling Power Grid Feasibility Analysis Using Machine Learning}, author = {Rahman, Minhazur and Himu, Sheik Erfan Ahmed and Chowdhury, Abdullah Al Shahid and Ikram, Arafat Ibne and Kashfi, Samiul Hoque and Uddin, Md Imtiaz and Faisal, MD}, booktitle = {2023 10th IEEE International Conference on Power Systems (ICPS)}, pages = {1--6}, year = {2023}, organization = {IEEE}, doi = {0.1109/ICPS60393.2023.10428886}, url = {https://doi.org/10.1109/ICPS60393.2023.10428886}, } - Small Scale PV Integration in Bangladesh: Opportunities, Challenges, and RecommendationMushfiqur Rahaman Pranta, Md Shariful Alam, Sheik Erfan Ahmed Himu, and 5 more authorsIn 2023 10th IEEE International Conference on Power Systems (ICPS), 2023
In the early 2000s, the Bangladesh government introduced nano and micro-scale photovoltaic (PV) systems in remote areas. As the power sector continues to grow, these nano-scale PV systems are becoming economically impractical. Additionally, the existing PV market policies are not sufficiently attractive to the mass population for installing small-scale PV systems known as SHS through private initiatives. This study aims to replicate the current SHS policies and pricing, assess the obstacles, and evaluate the economic viability of the current SHS system. Load profiles of three consumers are constructed and utilized to evaluate the economic feasibility of the existing system. Furthermore, various renewable-friendly policies, incentives, and net metering are applied to explore the economic viability of a modified system. The REopt tool is used to verify the economic feasibility, employing three hypothetical scenarios to assess the effectiveness of these policies and strategies in making SHS more appealing to the general population. Residential and small business load profiles are simulated using REopt. The findings of this research indicate that the implementation of net metering, combined with appropriate financial policies, can enhance the attractiveness of SHS to the mass population. These results provide valuable insights for policymakers and stakeholders to shape future initiatives and promote the widespread adoption of small-scale PV systems in Bangladesh.
@inproceedings{pranta2023small, title = {Small Scale PV Integration in Bangladesh: Opportunities, Challenges, and Recommendation}, author = {Pranta, Mushfiqur Rahaman and Alam, Md Shariful and Himu, Sheik Erfan Ahmed and Uddin, MD Mofij and Zakaria, Muhammd and Parves, Md Shahazan and Fahim, Joynal Abedin and Ikram, Arafat Ibne}, booktitle = {2023 10th IEEE International Conference on Power Systems (ICPS)}, pages = {1--6}, year = {2023}, organization = {IEEE}, doi = {10.1109/ICPS60393.2023.10428825}, url = {https://doi.org/10.1109/ICPS60393.2023.10428825}, } - Design Optimization and Assessment of Floating Solar PV with Wind Turbine Systems at KEPZArafat Ibne Ikram, Sheik Erfan Ahmed Himu, Tahmid Khandaker, and 4 more authorsIn 2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI), 2023
Renewable energy holds enormous potential in Bangladesh, but significant obstacles must be overcome to fully harness its benefits. With natural gas being the primary source of power generation in the country, there is a growing need to explore alternative sources of energy to reduce emissions and relieve the pressure on limited fuel supplies. Wind turbines (WT) and solar photovoltaic (PV) systems are currently being deployed to harness renewable energy, and Bangladesh’s unique geographical features, including being a riverine country with a modest land area, make it an ideal candidate for floating PV and WT installations. However, the intermittency of renewable generation and high upfront costs pose significant challenges to the technical and economic feasibility of microgrid operation. The use of Energy Management Systems (EMS) and Grey Wolf Optimization (GWO) can help optimize the use of renewable resources and minimize capital costs, respectively. In this research, a methodology is proposed to assess the economic feasibility of floating PV and WT in the Korean Export Processing Zone (KEPZ), a critical hub of the country’s economic activity, while minimizing renewable energy costs using the GWO technique. Mathematical models are used to design the hybrid renewable system, and load-demand data is collected from KEPZ. Based on hourly resource data, annual hourly floating PV and WT energy generation is estimated, and the electricity cost (LCEO) is evaluated, yielding a cost of 0.099$/kWh for the system, taking into account project lifetime, interest rate, and inflation rate.
@inproceedings{ikram2023design, title = {Design Optimization and Assessment of Floating Solar PV with Wind Turbine Systems at KEPZ}, author = {Ikram, Arafat Ibne and Himu, Sheik Erfan Ahmed and Khandaker, Tahmid and Reyad, Md Atikur Rahman and Erfan, Abdul Wazed and Alam, Md Morshed and Islam, Md Sirajul}, booktitle = {2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI)}, pages = {1--6}, year = {2023}, organization = {IEEE}, doi = {10.1109/STI59863.2023.10464595}, url = {https://doi.org/10.1109/STI59863.2023.10464595}, } - Feasibility Study and Performance Analysis of Rooftop Solar Panels and Airdolphin Wind TurbinesSamiul Hoque Kashfi, MD Abdulla Al Noman, Arafat Ibne Ikram, and 4 more authorsIn 2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI), 2023
Bangladesh’s economy has grown significantly in recent years. The nation’s rapid industrialization and population have increased the demand for power. However, to mitigate such issue a vast amount of measures have been taken which is not permanent. The world is moving towards renewable generation as it is also beneficial for the environment. However, renewable generation requires lots of land, that is not so freely available in a capital city like Dhaka. Dhaka has a high energy demand as it consumes 46 % of the total generated electricity. In this study, two approaches are shown by utilizing the same space we can generate electrical energy. The first one is to use the empty rooftop space of various Govt. buildings, commercial buildings, and petrol pumps to install solar panels. Another approach can be taken as implementing telecommunication connected to AirDolphine tower which can convert the wind energy into electrical energy and can be mounted in the existing cell tower. A methodology is established to check the renewable generation feasibility from the performance and the economic standpoint. Using the weather data to simulate the final output from rooftop generation and telecommunication-connected wind turbines, a significant amount of energy can be provided from the given model. An annual generation of 1190.986 GWh with a 10.554 km 2 area can be generated from our simulation which is very positive for the fact that renewable generation is not responsible for any carbon dioxide emissions.
@inproceedings{kashfi2023feasibility, title = {Feasibility Study and Performance Analysis of Rooftop Solar Panels and Airdolphin Wind Turbines}, author = {Kashfi, Samiul Hoque and Al Noman, MD Abdulla and Ikram, Arafat Ibne and Himu, Sheik Erfan Ahmed and Abrar, Fahim and Rahman, Minhazur and Uddin, Md Imtiaz}, booktitle = {2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI)}, pages = {1--6}, year = {2023}, organization = {IEEE}, doi = {10.1109/STI59863.2023.10464881}, url = {https://doi.org/10.1109/STI59863.2023.10464881}, } - Design and Performance Analysis of Grid-Connected Hybrid Renewable SystemsMd Atikur Rahman Reyad, Arafat Ibne Ikrarm, Md Mobasher Karim, and 4 more authorsIn 2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE), 2023
Renewable energy development aims to meet the world’s energy needs while replacing fossil fuels and moving to more renewable energy sources (RES). However, several different RES are tied together, taking into account the local load, and connected to add more energy to the current grid. Sadly, it requires a considerable amount of land. Yet the effects of climate change and the expanding global population both put food security in danger and the contest for scarce land resources has increased. In this regard, it has been claimed that agro-photovoltaic systems, which combine photovoltaics with plant growth, present a chance for the synergistic integration of renewable energy and food production. In this study, a methodology is shown where a grid-connected APV system is combined with other sustainable generation such as wind turbines (WT) and biomass generators. The Perturbation and Observation (P&O) based MPPT controller is implemented to harness the maximum power from APV. An energy management system is employed to use the stored energy in the battery and store the renewable energy generated by APV. To simulate the performance and effectiveness of grid -connected - RES-energy storage, a thorough study has been conducted. WT and BM connected to the existing power grid can generate an avg. of 3508 kW/day. and the APV system can produce avg of 50 kWh/day. The simulation results demonstrated that the suggested strategy works since the controller may use the most power feasible in both steady-state and diverse weather conditions.
@inproceedings{reyad2023design, title = {Design and Performance Analysis of Grid-Connected Hybrid Renewable Systems}, author = {Reyad, Md Atikur Rahman and Ikrarm, Arafat Ibne and Karim, Md Mobasher and Himu, Sheik Erfan Ahmed and Shiam, Mehedi Hasan and Choity, Tasnia Fahrin and Mostafa, Sk Md Golam}, booktitle = {2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE)}, pages = {444--449}, year = {2023}, organization = {IEEE}, doi = {10.1109/WIECON-ECE60392.2023.10456487}, url = {https://doi.org/10.1109/WIECON-ECE60392.2023.10456487}, } - A Grid-Connected ANFIS-MPPT Based Solar PV System and Hybrid Energy StorageArafat Ibne Ikram, Sheik Erfan Ahmed Himu, Rahat Abrar Tahsin, and 4 more authorsIn 2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE), 2023
The rising popularity of renewable energy sources (RES) has escalated due to limited fossil fuel and environmental concerns. However, due to weather dependency, renewable energy generation is uncertain. In order to ensure maximum renewable generation and store the energy for later use, a methodology was shown in this paper. Maximum power point tracking (MPPT) controllers can significantly improve Solar photo-voltaic (PV) performance. Adaptive Neuro-Fuzzy Inference System (ANFIS) based MPPT controller was implemented for a grid-connected PV system considering different levels of load demand, and weather conditions such as solar insolation and temperature. In a time of no renewable generation and peak energy demand, Energy storage can be a sustainable solution. A hybrid energy storage (HES) system consisting of both battery (BAT) and super-capacitor (SC) performs the best in time of peak load demand, and this was implemented in the system. In the time of no renewable generation, HES is able to provide the deficit energy to the grid. A smart energy management system (EMS) is proposed in this study which can effortlessly manage the energy between generation, energy storage, load demand, and existing grid. The proposed model was tested considering real hourly data. The output response of each component was analyzed to measure the performance and redundancy of the system.
@inproceedings{ikram2023grid, title = {A Grid-Connected ANFIS-MPPT Based Solar PV System and Hybrid Energy Storage}, author = {Ikram, Arafat Ibne and Himu, Sheik Erfan Ahmed and Tahsin, Rahat Abrar and Hoque, Mohammad Morshedul and Alam, Md Morshed and Erfan, Abdul Wazed and Farzana, Niger}, booktitle = {2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE)}, pages = {30--35}, year = {2023}, organization = {IEEE}, doi = {10.1109/WIECON-ECE60392.2023.10456412}, url = {https://doi.org/10.1109/WIECON-ECE60392.2023.10456412}, } - A Cutting-Edge Implementation of IoT-Based Monitoring for Floating Solar Cells with Dual-Axis TrackerImtiaz Alam, Arafat Ibne Ikram, Sheik Erfan Ahmed Himu, and 3 more authorsIn 2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE), 2023
Solar power has emerged as a significant and vital renewable energy sector, finding diverse applications such as in commercial settings, solar heaters, and solar pumps. Its adoption has contributed to mitigating the shortage of integrated grid electricity. However, the key challenge remains in optimizing energy extraction from solar sources. A promising solution lies in the utilization of Dual Axis tracker-based solar panels, which facilitate efficient solar energy utilization. Presently, conventional solar power plants necessitate vast land areas and exhibit certain limitations. Considering the context of overpopulated countries like Bangladesh, floating solar power plants offer a more viable alternative to land-based counterparts. This paper delves into the investigation and implementation of Floating Solar Cells (FPV) equipped with dual-axis tracker technology to maximize solar energy capture. The dual-axis tracking capability allows for precise sun tracking, resulting in a significantly higher energy yield. To analyze the photovoltaic (PV) and current-voltage (IV) curves, a MATLAB Simulink model is employed, while meteorological data is collected using Homer Software. The research focuses on the implementation of the project at the Teesta Barrage in Lalmonir Hat Zila. Additionally, an Internet of Things (IoT) integration enables remote plant monitoring and real-time data acquisition. Our investigation concludes that dual-axis trackers represent the optimal solution for maximizing energy harvesting from available resources, and the adoption of Floating Solar Power Plants stands as an efficient means of sustainable energy generation, particularly in densely populated nations like Bangladesh.
@inproceedings{alam2023cutting, title = {A Cutting-Edge Implementation of IoT-Based Monitoring for Floating Solar Cells with Dual-Axis Tracker}, author = {Alam, Imtiaz and Ikram, Arafat Ibne and Himu, Sheik Erfan Ahmed and Khandaker, Tahmid and Abrar, Fahim and Farzana, Niger}, booktitle = {2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE)}, pages = {177--182}, year = {2023}, organization = {IEEE}, doi = {10.1109/WIECON-ECE60392.2023.10456525}, url = {https://doi.org/10.1109/WIECON-ECE60392.2023.10456525}, } - Cognizance of Electric Vehicle Charging’s Impacts on Distribution TransformersNiger Farzana, Rehnuma Kainat, Imtiaz Alam, and 3 more authorsIn 2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE), 2023
Electric vehicles (EVs) have rapidly gained popularity in numerous countries, surpassing other transportation forms. The swift ascent of EV adoption in Bangladesh has exacerbated the prevailing energy crisis. Amid its growth, Bangladesh faces energy-related challenges stemming from excessive consumption. While electric vehicles offer benefits such as cost-effective transportation and reduced greenhouse gas emissions, the substantial energy demand for daily battery charging poses a formidable challenge. This equilibrium will shift shortly despite the current lower EV count compared to conventional vehicles in Bangladesh. Due to the impending increase in EV numbers, the high energy consumption required for frequent battery recharging has significant ramifications for power grids and distribution networks. This paper centers on comprehending the repercussions of EV charging on distribution transformers. Integrating a substantial number of EV chargers into the distribution grid engenders harmonics, which, in turn, influence voltage profiles, contribute to power losses, and ultimately impact electricity quality. This paper’s contribution lies in its investigation of the challenges posed by the increasing adoption of electric vehicles in Bangladesh, particularly concerning the energy demand for EV charging and its impact on the distribution grid, with a specific focus on the role of distribution transformers and harmonics. The paper aims to provide insights and potential solutions for mitigating these challenges in the context of EV adoption.
@inproceedings{farzana2023cognizance, title = {Cognizance of Electric Vehicle Charging's Impacts on Distribution Transformers}, author = {Farzana, Niger and Kainat, Rehnuma and Alam, Imtiaz and Ikram, Arafat Ibne and Abedin, Joynal and Shamim, Muhammad}, booktitle = {2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE)}, pages = {1--6}, year = {2023}, organization = {IEEE}, doi = {10.1109/WIECON-ECE60392.2023.10456528}, url = {https://doi.org/10.1109/WIECON-ECE60392.2023.10456528}, } - A Machine Learning Based Social Network Data Mining System for Better Search Engine AlgorithmSheik Erfan Ahmed Himu, Arafat Ibne Ikram, Kazi Mohammed Abdullah, and 4 more authorsIn 2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE), 2023
Social networks provide access to a vast amount of information in a variety of ways. However, these are poorly organized. On the other hand, data search engines include limited and occasionally inaccurate data. So, it is possible to find the right analytical answer to a problem based on what people say on social media. Consequently, a machine learning-based social network data mining system will aid in the development of a superior search engine. Google is thought to be the best search engine in the world right now. People used to do SEO after building a website to improve its search engine ranking. Google’s AI decides which search results to show based on how much traffic that website gets. But we still aren’t getting the right results. But if we configure our search algorithm to utilize social network user-generated content based on their sentiment, we can obtain accurate search results. This paper proposed a machine learning-based data mining system from social networks where all data is collected from social networks using linear regression, polynomial regression, and percentile machine learning techniques and stores unstructured and pre-structured data in big data for data validation. With the help of some techniques, we can show that the information from social networks is a good way to solve our problems.
@inproceedings{himu2023machine, title = {A Machine Learning Based Social Network Data Mining System for Better Search Engine Algorithm}, author = {Himu, Sheik Erfan Ahmed and Ikram, Arafat Ibne and Abdullah, Kazi Mohammed and Choity, Tasnia Fahrin and Parves, Md Shahazan and Hasan, Md Rabiul and Uddin, Md Imtiaz}, booktitle = {2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE)}, pages = {132--136}, year = {2023}, organization = {IEEE}, doi = {10.1109/WIECON-ECE60392.2023.10456428}, url = {https://doi.org/10.1109/WIECON-ECE60392.2023.10456428}, } - Performance Study of Different Types of Battery of Electric Vehicles Using MATLAB SimulinkMd Sohel Siddequy, Sheik Erfan Ahmed Himu, Arafat Ibne Ikram, and 4 more authorsIn 2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE), 2023
Since the advent of the Industrial Revolution, fossil fuels and internal combustion engines have played a fundamental role in meeting transportation and energy needs. However, the extensive reliance on fossil fuels over the past two centuries has resulted in dire consequences, such as global warming, environmental disruption, glacier melting, rising sea levels, and droughts. Consequently, scientists have been actively exploring alternative solutions to replace fossil fuel-based transportation systems. Electric vehicles (EVs) have emerged as a pivotal solution to address the existing challenges in transportation systems. Although the concept of EV s has existed for some time, the widespread production and adoption of fully electric cars was hindered until the early 21st century owing to the unavailability of suitable batteries or energy storage systems. The efficacy of EVs relies heavily on their energy storage systems. In this article, we evaluate various battery types (including nickel metal hydrate, zinc hybrid cathode, lead acid, and lithium-ion) in the context of EV performance, using MAT LAB Simulink. A MATLAB Simulink-based electric vehicle model was employed to assess battery performance. Our analysis reveals that lithium-ion batteries demonstrate superior performance metrics, including a specific energy ranging from 100–275 WH/kg, energy density of 200–235 Wh/L, specific power of 350–3000 W/kg, cell voltage of 3.6V, and cycle durability of 500–3000. Furthermore, we consider the typical cost of these batteries, noting that lead-acid batteries are relatively more affordable than other options available in the market.
@inproceedings{siddequy2023performance, title = {Performance Study of Different Types of Battery of Electric Vehicles Using MATLAB Simulink}, author = {Siddequy, Md Sohel and Himu, Sheik Erfan Ahmed and Ikram, Arafat Ibne and Abrar, Fahim and Iqbal, SM Shahriar and Rahman, Md Ziaur and Choity, Tasnia Fahrin}, booktitle = {2023 IEEE 9th International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE)}, pages = {125--131}, year = {2023}, organization = {IEEE}, doi = {10.1109/WIECON-ECE60392.2023.10456521}, url = {https://doi.org/10.1109/WIECON-ECE60392.2023.10456521}, } - Optimal cost and component configuration analysis of micro-grid using sso algorithmMd Sajjad-Ul Islam, Md Arafat Bin Zafar, Arafat Ibne Ikram, and 3 more authorsIn 2023 1st International Conference on Innovations in High Speed Communication and Signal Processing (IHCSP), 2023
The efficiency and optimal size of a micro-grid can be evaluated through economic analysis. Optimization is crucial for the sustainable development and upkeep of a micro-grid from a financial perspective. T he total cost of production can be lowered by taking advantage of available subsidies for things like capital, operations, pollution, and renewable energy, as well as satisfying a number of equality and inequality standards. The social spider optimization (SSO) method is an effective and versatile way to save money. In some cases, SSO is used in conjunction with other AI-based optimization techniques. In this work, we present a methodology for assessing the economic and environmental sustainability of grid-connected energy systems. The mathematical function of a micro-grid may consist of recycling the electricity generated each hour in relation to the resources available and storing the surplus in a super capacitor battery bank. Using a model developed for the Halishahar area of Chattogram, Bangladesh, we maximize the performance of a hybrid system consisting of photovoltaic cells, wind turbines, biomass, and a super capacitor battery. Solar panels, wind turbines, super capacitor batteries, and biomass are just some of the sustainable energy sources that the designers are thinking about. The area is estimated to consume roughly 107,150 MWh of electricity each year. We employ a social spider optimization strategy to determine which configuration settings w ill yield the lowest annual cost. More than a year’s worth of electricity for Halishahar can be generated by this micro-grid. With this configuration, t he L COE for electricity i so nly 0.127 $/kWh (dollar per kilowatt-hour). It’s more effective at cutting carbon dioxide emissions than conventional power.
@inproceedings{islam2023optimal, title = {Optimal cost and component configuration analysis of micro-grid using sso algorithm}, author = {Islam, Md Sajjad-Ul and Zafar, Md Arafat Bin and Ikram, Arafat Ibne and Sachha, Mohammad Saimur Rahaman and Ullah, Shihab and Ahamed, Rizvi}, booktitle = {2023 1st International Conference on Innovations in High Speed Communication and Signal Processing (IHCSP)}, pages = {306--311}, year = {2023}, organization = {IEEE}, doi = {10.1109/IHCSP56702.2023.10127165}, url = {https://doi.org/10.1109/IHCSP56702.2023.10127165}, } - Optimal Cost and Component Configuration Analysis of Micro-grid Using GWO AlgorithmMd Sajjad-Ul Islam, Md Arafat Bin Zafar, Arafat Ibne Ikram, and 3 more authorsIn 2023 International Conference on Electrical, Computer and Communication Engineering (ECCE), 2023
Economic analysis is used to assess the ideal size of a micro-grid and its efficiency. In order to maintain and grow a micro-grid economically, optimization is essential. A variety of equality and inequality requirements may be met to reduce the entire production cost, which includes subsidies for things like capital, operations, pollution, and renewable energy. Grey wolf optimization (GWO) is a powerful and adaptable cost-cutting strategy. GWO is used in tandem with other AI-based optimization methods in particular situations. Here, we provide a model for evaluating the viability, expense, and societal and environmental effects of energy systems that operate independently from the grid. Harmonization of micro-grids. It’s possible that the micro-mathematical grid’s role is to recycle power output hour by hour in accordance with available resources and to store any excess energy in a battery. In this work, we simulate and optimize a PV-Wind-WtE-battery hybrid system in the halishahar thana of Chattogram, Bangladesh. Design concerns include renewable energy sources including solar panels, wind turbines, batteries, and diesel engines. By our estimates, the thana uses around 107,150 MWh of power annually. We use a Grey wolf optimization approach to find the optimal design parameters to minimize the overall yearly cost. This micro-grid can easily provide 1,40,423.8 MWh, more than enough to power Halishahar for a whole year. A low levelized cost of energy (LCOE) of 0.221 $kWh is achieved with this setup. It reduces carbon dioxide emissions by a larger margin than traditional power.
@inproceedings{islam2023optimal2, title = {Optimal Cost and Component Configuration Analysis of Micro-grid Using GWO Algorithm}, author = {Islam, Md Sajjad-Ul and Zafar, Md Arafat Bin and Ikram, Arafat Ibne and Chowdhury, Tanzi Ahmed and Sachha, Mohammad Saimur Rahaman and Hossain, Sazzad}, booktitle = {2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)}, pages = {1--6}, year = {2023}, organization = {IEEE}, doi = {10.1109/ECCE57851.2023.10101554}, url = {https://doi.org/10.1109/ECCE57851.2023.10101554}, } - Techno-economic optimization of grid-integrated hybrid storage system using Genetic AlgorithmArafat Ibne Ikram, Md Sajjad-Ul Islam, Md Arafat Bin Zafar, and 3 more authorsIn 2023 1st International Conference on Innovations in High Speed Communication and Signal Processing (IHCSP), 2023
This Paper received the Best Paper Award of Session IEEE-IHCSP 23 for assessing the environmental performance across varying penetration rates, effectively integrating conventional networks and other energy sources to address the intermittency of renewable power output.
Microgrids (MG) are innovative in lowering GHG emissions from electricity production by using renewable energy sources. The technical and economic feasibility of MG operation with hybrid energy storage systems is challenged by the intermittent nature of renewable generation. The hybrid energy storage system has been investigated for decades. We provide a hybrid energy storage system with a Grid-connected MG integration model to assess its technological, economic, and environmental impacts. The MG model included photovoltaic panels, wind turbines, lead-acid batteries, electrolyzer modules, fuel cells, and H2 cylinder tanks. The mathematical function for each component used in the system is developed individually to estimate the annual hourly energy generation and consumption. Annual hourly data sets of load consumption are used as load models. The number of components needed for the MG operation to run economically feasible is achieved using the Genetic algorithm (GA) optimization technique thereafter reducing the Levelized cost of energy (LCOE) of the system. An energy dispatching technique is employed to efficiently distribute energy across the hybrid storage and load models. We examined different MG energy penetration levels of 25%, 50%, 75%, and 100% in terms of peak power distribution capacities to load demand relative to the existing grid. MG with 100% integration strives to maintain full load demand without buying energy from the grid. The LCOE and GHG emissions for each Grid-MG integration scenario are calculated. At 100% of the penetration scenario, the LCOE was found 0.0611 ($/kWh) which was best among all the other penetration scenarios.
@inproceedings{ikram2023techno, title = {Techno-economic optimization of grid-integrated hybrid storage system using Genetic Algorithm}, author = {Ikram, Arafat Ibne and Islam, Md Sajjad-Ul and Zafar, Md Arafat Bin and Rocky, Md Kamruzzaman and Rahman, Asif and others}, booktitle = {2023 1st International Conference on Innovations in High Speed Communication and Signal Processing (IHCSP)}, pages = {300--305}, year = {2023}, organization = {IEEE}, doi = {10.1109/IHCSP56702.2023.10127187}, url = {https://doi.org/10.1109/IHCSP56702.2023.10127187}, }
2022
- Economic analysis and optimal design of micro-grid using pso algorithmMd Arafat Bin Zafar, Md Rashidul Islam, Md Sajjad-Ul Islam, and 2 more authorsIn 2022 12th International Conference on Electrical and Computer Engineering (ICECE), 2022
The efficiency of a micro-grid and its optimal size are both determined through economic analysis. optimization is necessary for running and expanding a micro-grid economically. Fulfilling equity and inequality standards may reduce total production costs including capital, operations, pollution, and renewable energy subsidies. A cost-optimization method called particle swarm optimization (PSO) is effective and flexible. Here, a framework for assessing the practicality, cost, and impact of off-grid energy systems on people and the planet is presented. A mathematical function of the micro-grid component might recycle power production by the hour based on available resources and store any surplus energy in a battery. Here, a model of a PV-Wind-WtE-battery hybrid system is proposed for the halishahar area of Chattogram, Bangladesh. Design considerations include solar panels, wind turbines, batteries, and diesel engine power. To determine the best parameters for the design in terms of total annual cost, particle swarm optimization algorithm is employed. This micro-grid has no trouble providing Halishahar with sufficient power for a whole year. The LCOE of this system is 0.22 $/kWh. Compared to conventional electricity, it results in lower carbon dioxide emissions.
@inproceedings{zafar2022economic, title = {Economic analysis and optimal design of micro-grid using pso algorithm}, author = {Zafar, Md Arafat Bin and Islam, Md Rashidul and Islam, Md Sajjad-Ul and Shafiullah, Md and Ikram, Arafat Ibne}, booktitle = {2022 12th International Conference on Electrical and Computer Engineering (ICECE)}, pages = {421--424}, year = {2022}, organization = {IEEE}, doi = {10.1109/ICECE57408.2022.10088762}, url = {https://doi.org/10.1109/ICECE57408.2022.10088762}, } - Modification of dynamic logic circuit design technique for minimizing leakage current and propagation delaySheik Erfan Ahmed Himu, Sanjida Sultana, Mohammed Soaibul Haque Chowdhury, and 3 more authorsIn 2022 4th International Conference on Sustainable Technologies for Industry 4.0 (STI), 2022
This paper is based on the OR logic operation’s small discharging current and transmission time delay dynamic logic circuit configuration method. In terms of static logic circuits, it require a larger number of transistors and consume a massive amount of power. However, high-speed dynamic logic circuits consume less power due to their lower number of transistors. But, it has an issue with the evaluation phase where current gets leaked from the dynamic node due to sub-threshold leakage. In this paper, we have shown a new dynamic logic circuit design procedure for reducing leakage current from the dynamic node by using delay component, stacking effect, current mirror circuit with footed nmos, and a keeper circuit with the keeper device. The suggested system is analyzed in LTSpice with 45nm CMOS predictive technology model and compared with the previous research to demonstrate validity. The simulation study demonstrates power savings relative to traditional architecture and verifies the suggested strategy. This circuit could be used for designing low power consuming and delay systems for wide fan-in and can be useful for cascading several stages.
@inproceedings{himu2022modification, title = {Modification of dynamic logic circuit design technique for minimizing leakage current and propagation delay}, author = {Himu, Sheik Erfan Ahmed and Sultana, Sanjida and Chowdhury, Mohammed Soaibul Haque and Ikram, Arafat Ibne and Saium, Hasan Rahman and Hossain, Md Minhaj}, booktitle = {2022 4th International Conference on Sustainable Technologies for Industry 4.0 (STI)}, pages = {1--5}, year = {2022}, organization = {IEEE}, doi = {10.1109/STI56238.2022.10103242}, url = {https://doi.org/10.1109/STI56238.2022.10103242}, } - Techno-economic assessment of pso optimized microgrid with hydrogen storage systemARAFAT IBNE IKRAM and MK Rocky2022
Microgrids are designed to utilize the renewable energy sources and it is a revolutionary choice in terms of reducing the environmental effect of excessive GHG emissions while producing electricity. The intermittency of renewable generation poses challenges to the technical and economic feasibility of microgrid operation, which conveys the integration of hybrid energy storage systems. In recent decades, Several researched has already been concluded in search of reliable and economically feasible hybrid energy storage. Hydro gen storage have been considered to be a key vector for enhancing the effectiveness of renewable and sustainable energy storage. The hydrogen ecosystem would be deemed a fully green energy storage system if we could manufacture hydrogen from renewable en ergy sources, store it, and utilize it in times of energy shortage. Here we have presented a model for evaluating the technical, economical feasibility and the environmental impact on a Grid-connected Microgrid integration scenarios consisting hybrid energy storage system. Microgrid model was comprised Photovoltaic Panel, Wind turbine, Lead-Acid battery, Electrolyzer, Fuel cell, and H2 cylinder tank. Microgrid component’s analogous model was presented by the mathematical function by which we estimated annual hourly renewable generation based on given resources. In order to consider the load uncertainty, load consumption model for 50 homes was generated using Gaussian process. The mi crogird components sizing was done by Particle Swarm optimization technique (PSO) to minimize the installation upfront cost as well as levelized cost of energy ($/kWh). We used an energy dispatched strategy for smartly distribute energy among energy storage’s and load consumption model and reduce the loss of power supply probability (LPSP). We tested different microgrid’s energy penetration levels of 25%, 50%, 75% and 100% in terms of peak power distribution capabilities to load demand respective to conventional grid, where, Microgrid’s 100% integration capabilities try to maintain the full load de mand and not bought energy from conventional grid. And we found different LCOE and annual GHG emission for each integration scenario and easily distinguish which system performed better compared with other system.
@article{ikram2022techno, title = {Techno-economic assessment of pso optimized microgrid with hydrogen storage system}, author = {IKRAM, ARAFAT IBNE and Rocky, MK}, year = {2022}, publisher = {Department of Electrical and Electronic Engineering}, organization = {International Islamic University Chittagong}, doi = {10.13140/RG.2.2.11606.42565}, url = {http://dx.doi.org/10.13140/RG.2.2.11606.42565}, }