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Comparative Analysis of Different Control Strategies and Materials for a Community Microgrid - A Case Study Pranto, Jubaer Akon; Kadir, Md Moin; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.118

The main objective of this study is to conduct a comparative analysis of various control strategies and materials used in the operation of community microgrids. An analysis that contrasts various methods for managing a microgrid's operations in a community context is called comparison research on control strategies for community microgrids. The study's objectives are to evaluate the benefits and drawbacks of various control systems and to pinpoint the best approach for maximizing the microgrid's performance and materials for microgrid. The study compares various control strategies, including islanded mode control, hybrid mode control, and grid-connected mode control. Advanced strategies that integrate economic dispatch with optimal power flow are also evaluated. A comparison is done taking into account variables including resilience, cost-effectiveness, efficiency, stability, and reliability. The findings provide valuable insights into the optimal control approach tailored to the specific needs of community microgrids, considering available resources, local energy consumption patterns, and other critical factors. The report also emphasizes the advantages of employing sophisticated control systems, including enhanced resilience and flexibility, increased cost-effectiveness, and improved integration with the main grid. In general, the comparative analysis of different control strategies for community micro-grids offers insightful knowledge to scholars, engineers, and decision-makers engaged in micro-grid design and operation, assisting in enhancing the efficiency and dependability of these systems for the good of communities.

A Review on Employing Weather Forecasts for Microgrids to Predict Solar Energy Generation with IoT and Artificial Neural Networks Islam, Md Monirul; Akter, Mst. Tamanna; Tahrim, H M; Elme, Nafisa Sultana; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.108

In this study, an artificial neural network (ANN) based approach is studied about the prediction of solar energy generation in a microgrid using weather forecasting. The ANN is trained using historical data of solar energy generation and weather forecast data. The input parameters for the ANN include weather variables such as temperature, humidity, wind speed, and solar irradiance. The output parameter is the solar energy generation in kilowatt-hour (kWh). The proposed approach is implemented and tested using real-world data from a microgrid. The results indicate that the ANN-based approach is effective in predicting the solar energy generation with high accuracy. The proposed approach can be used for optimizing the operation of microgrids and facilitating the integration of renewable energy sources into the power grid. This study proposes the use of an Artificial Neural Network (ANN) to predict the solar energy generation in a microgrid using weather forecast data. Weather forecasting has become more precise and dynamic with the integration of IoT data with advanced analytics and machine learning models. These models are quite accurate at predicting solar irradiance and analyzing patterns. The microgrid comprises of a photovoltaic (PV) system which generates solar energy and a battery storage system which stores and supplies the energy to the load. Accurate prediction of solar energy generation is crucial for optimizing management of the microgrid. The inputs to the ANN model include temperature, humidity, wind speed, cloud cover and solar irradiance, which are obtained from weather forecast data. The output of the model is the predicted solar energy generation. The performance of the ANN model is evaluated using various performance metrics such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE) and Coefficient of Determination (R²). This study presents a practical approach for predicting solar energy generation in a microgrid using weather forecast data, which can be used for efficient management of the microgrid.

Challenges and Future Prospects of Electric Vehicles Using Hybrid Energy in Bangladesh - A Case Study Aziz, Tareq; Dodaev, Zohar Al; Hossain, Md. Taufiq; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.96

The main objective of this paper is to review the current challenges and prospects of Electric Vehicles based hybrid energy in Bangladesh. Electric cars (EVs) are a viable way to lessen transportation's negative environmental effects and wean us from fossil fuels. EV adoption has a lot of promise in Bangladesh, where environmental sustainability and energy security are major concerns. However, there are a few obstacles to the general adoption of EVs, including limited infrastructure, high upfront prices, and range anxiety. The difficulties and potential benefits of EVs using hybrid energy in Bangladesh are examined in this case study. It has been reviewed the infrastructure's preparedness, present level of EV adoption, and main obstacles for implementation. In addition, it has been suggested tactics to address these issues, such as public awareness campaigns, infrastructure development, and regulatory changes. It is considered to look at how hybrid energy systems, which combine traditional power grids and renewable energy sources, can power EVs and improve energy sustainability. Bangladesh can achieve sustainable transportation goals, decrease greenhouse gas emissions, and expedite the shift to electric mobility by utilizing hybrid energy solutions and tackling systemic issues. Policymakers, industry stakeholders, and scholars can use this case study to gain important insights into how Bangladesh's energy transition and EV adoption are changing.

A Comprehensive Study of the Importance of Materials for Renewable Energy Generation Pranto, Jubaer Akon; Kadir, Md Moin; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 2, No 3 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i3.119

The main objective of this review is to show the importance of materials in renewable energy generation. Making the switch to renewable energy sources is essential for promoting sustainable growth and halting global warming. This extensive study looks at the critical role that materials play in the production of renewable energy, emphasizing how important they are for improving efficiency, cutting costs, and guaranteeing the longevity of energy systems. Key components of solar, wind, hydro, and biomass energy technologies are the subject of this study. Examples of these components are silicon for solar cells, rare earth metals for wind turbines, and organic matter for biomass conversion. It also examines the effects of cutting-edge energy storage technologies, such as supercapacitors and lithium-ion batteries, on the stability and dependability of renewable energy systems. Materials play a key role in increasing the performance and lowering the cost of renewable energy generation technologies, including fuel cells, wind turbines, solar panels, and batteries. Due to its high energy conversion efficiency and widespread availability, silicon continues to be the most widely used material in photovoltaic (PV) solar panels. However, novel materials such as perovskites offer promise for obtaining higher efficiencies at reduced manufacturing costs. The difficulties in extracting, processing, and recycling materials are discussed, highlighting the necessity of sustainable methods and creative approaches in the field of material science. Many high-performance materials are costly or challenging to manufacture on a large scale, such as advanced composites and some rare earth elements. A big problem is cutting prices and locating more plentiful alternatives. The study highlights the vital need for ongoing research and development in materials to optimize renewable energy technologies and support the worldwide move towards a low-carbon future by examining existing advancements and future potential.

A Review on Integration Challenges for Hybrid Energy Generation Using Algorithms Aziz, Tareq; Dodaev, Zohar Al; Halim, Md. Abdul; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 2, No 2 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i2.85

The main objective of this paper is to review the challenges associated with the integration used in multiple energy generation from renewable energy sources. There are a number of obstacles that must be overcome for the successful integration of various energy sources and storage technologies in a hybrid energy generation system. Algorithms are very crucial for multiple energy generation due to the integration of renewable energy sources, optimum resource allocation, load balancing, system stability and real time decision making. Demand response, load forecasting, and intelligent decision-making algorithms are examples of successful management tactics that may be used to allocate power from various sources according to availability and cost-effectiveness. To operate effectively, algorithms must take into consideration many variables such as state of the batteries, load changes, and weather. The difficulties with circuit design, algorithm design, source management and switching control in hybrid energy generation systems with numerous sources are covered in this paper. These difficulties include maximizing power generation and usage from each source, dynamic power output adjustment based on energy availability and demand, and smooth source changeover. The paper emphasizes how crucial integration of renewable energy sources, using proper algorithm and switching control among energy sources are for successfully integrating various energy sources. Voltage compatibility, current balance, and surge protection are among the difficulties in circuit design. Switching control techniques are very important fact to guarantee smooth switching between energy sources but minimizing power disturbance during source switching and maintaining a steady power supply throughout the process are challenges in switching control. The challenges in circuit and algorithm design for hybrid energy generation systems with multiple sources are highlighted in this review. Hybrid energy generation systems can accomplish effective use of renewable energy sources and contribute to a sustainable energy future by successfully overcoming these obstacles. Algorithms for optimization could be used to weigh environmental sustainability against economic viability while accounting for energy prices, carbon emissions, and lifecycle analysis.

Review of Electrical and Thermal Modeling Techniques for Three-Phase PMSM Drives Azom, Md Ali; Hossain, Md. Shahen; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 3, No 1 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v3i1.172

The objective of this paper is to present a thorough examination of electrical and thermal modelling approaches for three-phase PMSM drives, emphasizing their methods, potential, and constraints. Modern electric drives now rely heavily on Permanent Magnet Synchronous Motors (PMSMs), which are found in renewable energy systems, industrial automation, and electric cars. PMSM drives must be accurately modelled to maximize performance, guarantee dependability, and increase operational longevity. The methods, advantages, and disadvantages of electrical and thermal modelling approaches for three-phase PMSMs are thoroughly examined in this paper. To forecast electromagnetic behavior and drive efficiency, the electrical modelling section examines dynamic dq-axis transformations, finite element methods (FEM), equivalent circuit models, and sophisticated AI-driven techniques. The function of thermal modelling tools in controlling heat dissipation and halting thermal degradation is examined. These techniques include lumped parameter models, coupled electro-thermal models, and computational fluid dynamics (CFD). The trade-offs between these models' practical usability, computational complexity, and accuracy are highlighted by a comparative comparison. Incorporating trade-offs between accuracy, complexity, and usability into modelling methods for three-phase Permanent Magnet Synchronous Motor (PMSM) drives offer a comprehensive viewpoint that strikes a compromise between performance and usefulness. Current issues are noted in the review, including the requirement for real-time adaptive models and the incorporation of multi-physics effects. New developments are highlighted as promising paths to improve PMSM modelling, including AI-based simulations and digital twin technologies. The goal of this study is to provide researchers and engineers with a thorough resource that will direct the creation of reliable and effective PMSM drive systems. The review's findings and insights have the potential to influence a variety of applications, spur innovation in PMSM drives, and aid in the global shift to sustainable technologies and electrification.

Recent Developments in Control and Simulation of Permanent Magnet Synchronous Motor Systems Azom, Md Ali; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 3, No 1 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v3i1.173

This paper's main goal is to present a thorough analysis of current advancements in the simulation and control of Permanent Magnet Synchronous Motor (PMSM) systems. A crucial part of contemporary electrical drive systems, the Permanent Magnet Synchronous Motor (PMSM) finds extensive use in fields like industrial automation, renewable energy systems, and electric cars. This review examines the most current developments in PMSM system control and simulation, with a focus on cutting-edge modelling techniques, new control strategies, and the most recent simulation methods. It emphasizes how increasingly complex strategies like Model Predictive Control (MPC), Sliding Mode Control (SMC), and AI-based approaches have replaced more conventional ones like PID and vector control. Advanced control techniques like Field-Oriented Control (FOC) and MPC are used by Tesla and other EV manufacturers to maximize PMSM performance, guarantee smooth torque delivery, and improve energy economy. Siemens Gamesa wind turbines use PMSMs with reliable control systems for fault tolerance and maximum energy production in a range of wind conditions. The study also discusses the developments in simulation techniques, such as the incorporation of multi-physics models, real-time simulation, and the application of AI to improve simulation efficiency and accuracy. More realistic modelling of PMSM systems in dynamic contexts is now possible thanks to recent developments in simulation approaches, such as Multiphysics models and real-time simulations. These simulations are combined with sophisticated control algorithms to give real-time input while the system is operating, which speeds up fault finding and optimization. This procedure is further improved by AI-based simulation tools, which forecast system behavior’s under varied circumstances and spot possible problems before they arise. It is described how these advancements affect PMSM performance, including increased fault tolerance, robustness, and efficiency. The study concludes by highlighting the significance of integrating cutting-edge control and simulation approaches for optimal performance in PMSM systems, as well as important research issues and prospects.

Challenges and Advances in Electrical and Thermal Modeling of High-Precision PMSM Drives Azom, Md Ali; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 3, No 2 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v3i2.175

This review examines the challenges and advancements in electrical and thermal modeling of PMSM systems, emphasizing their interdependence and practical applications. Permanent Magnet Synchronous Motors (PMSMs) are essential for high-precision applications including electric vehicles, robots, and aerospace systems because of their exact controllability, high efficiency, and high-power density. However, maximizing PMSM drive performance necessitates a thorough comprehension of both their thermal and electrical properties. The difficulties and developments in electrical and thermal modeling for PMSMs are thoroughly examined in this paper, with a focus on high-precision applications. The research starts by going over the basics of PMSM drives and their operating parameters. Next, it examines important electrical modeling methods, such as finite element methods, dq-axis transformations, and approaches to nonlinearities like saturation and harmonics. The conversation goes on to explore thermal modeling techniques, emphasizing computational fluid dynamics, lumped parameter models, and finite element thermal analysis. The review emphasizes how important integrated electrical-thermal models are for accurately predicting the coupled dynamics of electrical performance and heat generation in high-performance applications. Innovative solutions including machine learning-driven models, hybrid approaches, and the usage of digital twins are considered alongside major problems like computational complexity, parameter identification, and real-time implementation. In addition, this paper looks at real-world case studies that demonstrate how sophisticated modeling approaches can improve PMSM designs and guarantee thermal stability in a range of operating scenarios. The development of real-time simulation techniques, investigation of new cooling materials, and improvements in multi-physics modeling are among the final research directions mentioned. Future directions include advancements in real-time simulation, novel cooling materials, and multi-physics modeling. By highlighting this early integration, the study offers a cohesive framework that improves comprehension of coupled electro-thermal phenomena, setting it apart from traditional research and making it an invaluable tool for engineers and researchers.

Comparative Analysis of IoT and AI-Based Control Strategies for Community Micro-Grids Islam, Md Monirul; Akter, Mst. Tamanna; Elme, Nafisa Sultana; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 3, No 2 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v3i2.191

The main objective of this paper is to review the centralized, decentralized, and hybrid control approaches based on key performance metrics such as efficiency, reliability, and scalability. By improving sustainability, dependability, and efficiency, the combination of artificial intelligence (AI) and the Internet of Things (IoT) in community micro-grids has completely changed energy management. The Internet of Things (IoT) and artificial intelligence (AI) have been used more and more in microgrid control to improve autonomy, dependability, and efficiency. Sensors, smart meters, distributed energy resources (DERs), and energy storage systems are just a few of the microgrid's components that can communicate and monitor in real time thanks to the Internet of Things.AI uses this data to make smart decisions on activities like fault detection, load forecasting, renewable energy prediction, and optimal power dispatch. To optimize power distribution, load balancing, and fault detection in micro-grids, this article compares several control systems that make use of IoT and AI. The study looks at decentralized, hybrid, and centralized control strategies, emphasizing their benefits, drawbacks, and applicability in various operational scenarios. Important performance indicators are assessed, including cost-effectiveness, responsiveness, energy efficiency, and flexibility about renewable energy sources. The results contribute to the development of smart energy systems by shedding light on the best control schemes for enhancing microgrid performance.

A Comprehensive Review of Renewable and Sustainable Energy Sources with Solar Photovoltaic Electricity Advancement in Bangladesh Hussain, Md. Naeem; Zaman, Md Rakibur; Halim, Md Abdul; Ali, Md. Sumon; Khan, Md. Yakub Ali
Control Systems and Optimization Letters Vol 2, No 1 (2024)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v2i1.59

With an emphasis on Bangladesh's accomplishments in solar photovoltaic power production, this extensive study offers a comprehensive review of sustainable and renewable energy sources. Bangladesh, a heavily populated country that depends heavily on energy, has a difficult time satisfying its rising electrical demand while also taking environmental issues into account. The assessment covers a wide range of topics related to renewable energy sources, including solar photovoltaic technology, how it fits into the nation's current energy infrastructure, legislative frameworks, and socioeconomic effects. The report emphasizes how solar photovoltaic power may play a key role in Bangladesh's sustainable energy future by lowering the country's reliance on fossil fuels, lessening the effects of climate change, and promoting economic development via the use of renewable energy sources. This comprehensive review explores the many facets of sustainable and renewable energy sources in further detail, with a particular emphasis on Bangladesh's ever-changing solar photovoltaic power market. The topic of discussion includes developments in solar panel technology, such as increased efficiency, lower costs, and novel ideas. It also looks at how solar energy may be integrated into the current energy system, discussing the benefits and problems related to energy storage and grid modernization. This paper has the potential to improve energy security, the environment, the economy, and the general well-being of the populace, with a focus on solar PV advancement in Bangladesh. It can act as a guide for decision-makers in government, academia, and business to work together to create a more resilient and sustainable energy future for the nation. The research explores how the expansion of the solar business might lead to the creation of jobs, the improvement of skills, and the enhancement of local economies. It also takes into account the advantages for the environment that come from using less fossil fuels, such as lower greenhouse gas emissions and better air quality. This thorough review highlights the importance of Bangladesh's progress toward solar photovoltaic electricity development as a way to guarantee a sustainable and environmentally conscious energy future, lower consumer energy costs, and improve energy security in a country with rising energy consumption and aggressive renewable energy targets.

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