Efficient energy demand forecasting is pivotal for addressing energy challenges in remote areas of Bangladesh, where reliable access to energy resources remains a concern. This study proposes an innovative approach that combines linear regression analysis (LRA) and inverse matrix calculation (IMC) to forecast energy demand accurately in these underserved regions. By leveraging historical energy consumption data and pertinent predictors, such as meteorological conditions, population dynamics, economic indicators, and seasonal patterns, the model provides reliable forecasts. The application of the proposed methodology is demonstrated through a case study focused on remote regions of Bangladesh. The results showcase the approach's effectiveness in capturing the intricate dynamics of energy demand and its potential to inform sustainable energy management strategies in these remote areas. This research contributes to the advancement of energy planning and resource allocation in regions facing energy scarcity, fostering a path towards improved energy efficiency and development. These techniques can be applied to estimate short-term electricity demand for any rural or isolated region worldwide.
Empowering Sustainability: A Comprehensive Analysis of Sarishabari Engreen So...IRJET Journal
This document provides an analysis of the Engreen Sarishabari Solar Power Plant in Bangladesh, the country's first grid-connected solar PV power plant. The analysis evaluates the plant's annual performance ratio, estimated at 71%. It also examines the plant's installation cost of $7,012,823 USD, average annual energy production of 3,845 MWh, cost per kWh of $0.1048 USD, and payback period of 9.6 years. The document utilizes PVsyst software and data from plant officials to conduct a comprehensive economic and performance evaluation of the 3 MW solar power plant.
This document discusses the deployment of microgrids in India. It addresses the economic issues and challenges associated with microgrid development in India. Key points include:
1) Microgrids make efficient use of distributed energy resources like solar, wind, and biomass to provide power, especially in remote rural areas of India.
2) Several pilot microgrid projects have been implemented in India using combinations of solar, biomass, and diesel generators. However, the high initial cost of microgrids has been a challenge to widespread adoption.
3) The document examines important economic issues that need to be addressed like cost of energy analysis, regulatory policies, and tariff structures to strengthen the economics of microgrids and justify their implementation in
A road to mitigate energy demand until 2030 & acquisition of Bangladesh in po...Kazi Tanvir
Bangladesh has faced a severe power crisis due to shortages in natural gas and increases in oil prices. The document outlines steps taken by the Bangladesh government from 2009-2013 to address this crisis and plans to meet energy demands through 2030. Key steps included increasing power production through new plants, improving distribution networks, reducing system losses, and developing renewable sources like solar and wind. Future plans include producing more power from renewable sources and nuclear plants, as well as regional cooperation, with a goal of generating 39,000 MW by 2030. Proper implementation of these proposals could effectively solve Bangladesh's power issues.
Modeling and simulation of distributed generation systemIRJET Journal
This document summarizes a study that models and simulates a hybrid photovoltaic (PV) and wind distributed generation system to meet the energy demands of Leh, India effectively. The study analyzes Leh's local energy requirements and assesses the solar and wind resources for their potential contributions to the hybrid system. Using the HOMER software, various system configurations and component sizes are evaluated to optimize the performance of the hybrid system. Simulations determine the most cost-effective and reliable solution that meets Leh's energy demands while considering the intermittency of renewable energy sources. The economic feasibility of the proposed PV-wind hybrid system is examined through metrics such as the levelized cost of energy.
Forecasting and Scheduling of Wind and Solar Power generation in IndiaDas A. K.
The document discusses forecasting and scheduling of wind and solar power generation in India. It notes that wind and solar power are variable and intermittent, posing grid integration challenges. Accurate forecasting is needed to schedule renewable energy and minimize penalties for deviations under India's electricity regulations. The document presents methods for quantifying the variability of wind and solar power, calculating forecasting accuracy and associated penalties, and describes an artificial intelligence technique for wind/solar forecasting developed by the author's company.
Forecasting and scheduling of wind and solar power generation in indiaDas A. K.
This document discusses forecasting and scheduling of wind and solar power generation in India. It notes that wind and solar energy are major sources of renewable energy in India, but their variability poses challenges for grid integration. Accurate forecasting of wind and solar power is needed to effectively integrate renewable energy into the grid. The document examines regulations in India requiring day-ahead forecasting and scheduling of wind and solar power and explores methods for improving forecast accuracy to minimize penalties for deviations from forecasts.
Forecasting and Scheduling of Wind and Solar Power generation in Indiadel2infinity Energy
This document discusses forecasting and scheduling of wind and solar power generation in India. It notes that wind and solar energy are major sources of renewable energy in India, but their variability poses challenges for grid integration. Accurate forecasting of wind and solar power is needed to effectively integrate renewable energy into the grid. The document examines regulations in India requiring day-ahead forecasting and scheduling of wind and solar energy. It also discusses penalty calculations for inaccurate forecasts. The paper aims to show how mixed artificial intelligence techniques can improve forecasting of wind and solar generation to minimize penalties from forecast errors.
Design of solar Parabolic Trough Plant for a Village in RajasthanIRJET Journal
This document describes the design of a solar parabolic trough plant to provide electricity for a village in Rajasthan, India. It first estimates the village's current and future electricity demands based on surveys and population growth projections. It then sizes the key components of the solar plant, such as the solar collectors, receiver tubes, and turbine, to meet the village's electricity needs in 2015, 2019, and 2024. The plant is designed to have a rated capacity of 312.61 kW in 2015, 451.24 kW in 2019, and 641.88 kW in 2024 to fulfill the projected energy demands of 638.25 MWh/year, 821.27 MWh/year, and 1072.
Empowering Sustainability: A Comprehensive Analysis of Sarishabari Engreen So...IRJET Journal
This document provides an analysis of the Engreen Sarishabari Solar Power Plant in Bangladesh, the country's first grid-connected solar PV power plant. The analysis evaluates the plant's annual performance ratio, estimated at 71%. It also examines the plant's installation cost of $7,012,823 USD, average annual energy production of 3,845 MWh, cost per kWh of $0.1048 USD, and payback period of 9.6 years. The document utilizes PVsyst software and data from plant officials to conduct a comprehensive economic and performance evaluation of the 3 MW solar power plant.
This document discusses the deployment of microgrids in India. It addresses the economic issues and challenges associated with microgrid development in India. Key points include:
1) Microgrids make efficient use of distributed energy resources like solar, wind, and biomass to provide power, especially in remote rural areas of India.
2) Several pilot microgrid projects have been implemented in India using combinations of solar, biomass, and diesel generators. However, the high initial cost of microgrids has been a challenge to widespread adoption.
3) The document examines important economic issues that need to be addressed like cost of energy analysis, regulatory policies, and tariff structures to strengthen the economics of microgrids and justify their implementation in
A road to mitigate energy demand until 2030 & acquisition of Bangladesh in po...Kazi Tanvir
Bangladesh has faced a severe power crisis due to shortages in natural gas and increases in oil prices. The document outlines steps taken by the Bangladesh government from 2009-2013 to address this crisis and plans to meet energy demands through 2030. Key steps included increasing power production through new plants, improving distribution networks, reducing system losses, and developing renewable sources like solar and wind. Future plans include producing more power from renewable sources and nuclear plants, as well as regional cooperation, with a goal of generating 39,000 MW by 2030. Proper implementation of these proposals could effectively solve Bangladesh's power issues.
Modeling and simulation of distributed generation systemIRJET Journal
This document summarizes a study that models and simulates a hybrid photovoltaic (PV) and wind distributed generation system to meet the energy demands of Leh, India effectively. The study analyzes Leh's local energy requirements and assesses the solar and wind resources for their potential contributions to the hybrid system. Using the HOMER software, various system configurations and component sizes are evaluated to optimize the performance of the hybrid system. Simulations determine the most cost-effective and reliable solution that meets Leh's energy demands while considering the intermittency of renewable energy sources. The economic feasibility of the proposed PV-wind hybrid system is examined through metrics such as the levelized cost of energy.
Forecasting and Scheduling of Wind and Solar Power generation in IndiaDas A. K.
The document discusses forecasting and scheduling of wind and solar power generation in India. It notes that wind and solar power are variable and intermittent, posing grid integration challenges. Accurate forecasting is needed to schedule renewable energy and minimize penalties for deviations under India's electricity regulations. The document presents methods for quantifying the variability of wind and solar power, calculating forecasting accuracy and associated penalties, and describes an artificial intelligence technique for wind/solar forecasting developed by the author's company.
Forecasting and scheduling of wind and solar power generation in indiaDas A. K.
This document discusses forecasting and scheduling of wind and solar power generation in India. It notes that wind and solar energy are major sources of renewable energy in India, but their variability poses challenges for grid integration. Accurate forecasting of wind and solar power is needed to effectively integrate renewable energy into the grid. The document examines regulations in India requiring day-ahead forecasting and scheduling of wind and solar power and explores methods for improving forecast accuracy to minimize penalties for deviations from forecasts.
Forecasting and Scheduling of Wind and Solar Power generation in Indiadel2infinity Energy
This document discusses forecasting and scheduling of wind and solar power generation in India. It notes that wind and solar energy are major sources of renewable energy in India, but their variability poses challenges for grid integration. Accurate forecasting of wind and solar power is needed to effectively integrate renewable energy into the grid. The document examines regulations in India requiring day-ahead forecasting and scheduling of wind and solar energy. It also discusses penalty calculations for inaccurate forecasts. The paper aims to show how mixed artificial intelligence techniques can improve forecasting of wind and solar generation to minimize penalties from forecast errors.
Design of solar Parabolic Trough Plant for a Village in RajasthanIRJET Journal
This document describes the design of a solar parabolic trough plant to provide electricity for a village in Rajasthan, India. It first estimates the village's current and future electricity demands based on surveys and population growth projections. It then sizes the key components of the solar plant, such as the solar collectors, receiver tubes, and turbine, to meet the village's electricity needs in 2015, 2019, and 2024. The plant is designed to have a rated capacity of 312.61 kW in 2015, 451.24 kW in 2019, and 641.88 kW in 2024 to fulfill the projected energy demands of 638.25 MWh/year, 821.27 MWh/year, and 1072.
Integrating Renewable Energy in Smart Grid: Opportunity, Challenges and Progr...IRJET Journal
1) India has seen significant growth in renewable energy, especially solar and wind, over the last decade and has set a target of installing 500GW of renewable capacity by 2030.
2) Integrating such large amounts of renewable energy will be challenging due to the variable and intermittent nature of solar and wind sources.
3) The document discusses India's progress in renewable energy development and generation as well as the opportunities and challenges of integrating renewable energy into the country's power grid at large scale.
Solar Photovoltaic (PV) Grid Integration IssuesIJMTST Journal
High electricity demand, reduction in fossil fuels and increasing demand towards solar energy, the integration of solar photovoltaic (PV) generation in the utility grid is gaining high popularity in India. Many distributed energy resources (DERs) are connected to the utility grid or microgrids with the help of power electronics interface, while interfacing power electronics with microgrids there are valid technical concerns from utilities about power quality and the impact of DG on the low voltage (LV) grid. This paper focuses on India’s Current Solar generation capacity and grid integration issues such as voltage, frequency regulation, active, reactive power control and power quality issues.
A Low-cost Renewable Energy Solution for Improved Energy Access in NigeriaIRJET Journal
This document discusses a low-cost renewable energy solution implemented in Afikpo, Nigeria to provide improved energy access. The residents of Afikpo had not received power from the national grid for many years. To address this, the authors designed and implemented a solar photovoltaic system for a residential building. They analyzed the power needs of the residence and designed a system using solar panels, batteries, an inverter, and charge controller. The system has provided the residents with uninterrupted power for six months. The residents have benefited from reliable power without noise or fuel costs. The authors conclude solar energy can provide a clean and reliable alternative for powering homes in Nigeria.
POTENTIAL STUDY ADDRESSING SHORTAGE OF POWER AND ECONOMIC GROWTH THROUGH FORE...IAEME Publication
India is densely populated and has high solar insolation, an ideal combination for using solar power in India. India is already a leader in wind power generation. India is now one of the top five solar energy developments worldwide as per Ernst & Young’s renewable energy attractiveness index. As per report by WATO-India, 2012, the Indian Renewable Energy business market is experiencing a growth rate of 15 %/yr and the opportunities for private investments are estimated to
be of about USD 34 billion.
Large scale grid amalgamation of renewable energy sources in indian power systemIjrdt Journal
This document discusses the challenges and solutions related to large-scale integration of renewable energy sources into India's power grid. The key points are:
1. Integrating renewable energy is challenging due to its intermittent nature and geographical distribution far from load centers. This requires improved transmission infrastructure and balancing across regions.
2. Distributed generation from renewables also presents issues if connected to medium and low voltage distribution systems. Solutions include intelligent grid configurations and prioritizing generation to match demand.
3. Potential solutions discussed are energy storage, power electronics to enable grid integration, distributing renewable generation over large areas, and using solar power for irrigation to match generation with load.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Techno economic analysis of SPV-DG hybrid model using HOMERIRJET Journal
This document summarizes a study that conducts a techno-economic analysis of a solar photovoltaic (SPV)-diesel generator (DG) hybrid energy system model implemented in Leh, India. The HOMER software is used to optimize and simulate the SPV-DG hybrid system. Simulation results are analyzed to determine the optimal sizing of SPV and DG components and overall system performance. A life cycle cost analysis is performed considering capital, operating, maintenance and fuel costs. The study also examines the environmental impacts of the SPV-DG system, focusing on reductions in greenhouse gas emissions and fossil fuel dependence.
Optimization towards cost effective solar mini grids in bangladeshDipta Majumder
People living in remote rural areas e.g. islands of Bangladesh don’t have access to electricity due to financial and technical challenges. Solar Photovoltaic (PV)-Diesel based hybrid mini grids can be a way to electrify remote rural areas of Bangladesh. However, solar energy is costly compared to conventional energy sources. Hence, optimization is essential to ensure success of solar mini grids in remote rural areas. Optimization of mini grid plant capacity based on demand is discussed. Diesel consumption and excess electricity from plant are the key optimization parameters. A case at Paratoli, Narsingdi, Bangladesh is taken into consideration to validate the optimization. Data is further analyzed to find out the future requirements and effects after optimization.
Optimal Hybrid Energy System for Rural Electrification in India using HOMER S...IRJET Journal
This document discusses the optimal design of a hybrid energy system for a village in India using the HOMER software. It analyzes a grid-connected hybrid system combining solar PV, diesel generator, battery storage, and grid connection. The system is designed to meet the village's daily electricity demand of 202 kWh and peak demand of 16.67 kW. Simulation results show the optimal system would include 14.6 kW of solar PV panels, 19 kW diesel generator, 56 batteries, and 16 kW converter. The levelized cost of electricity for this system would be $0.1903/kWh, lower than an off-grid system. The hybrid system would generate most power from the grid, but the solar PV and diesel generator
Performance Analysis of Autonomous Hybrid Distributed Generation Based on Typ...ijtsrd
It is undeniable fact that even though fossil fuels are likely more to fulfill the requirements of energy, the rare of natural resources and their harmful contents for the environment have directed people to search for new energy sources like renewable resources such as hydropower, biomass, wind, solar and other types of clean energy. In order to highlight the proposed methodology, PV Diesel generator DG with battery energy system BESS based on two typical control strategies, load following LF control strategy and cycle charging CC control strategy, have been analyzed by using HOMER Software to supply the Makyiyay village which is located at 22.02 north latitude and 96.56 east longitude in the Naungkhyo Township, Southern Shan State in Myanmar. The yearly average solar radiation of that area is 4.895kWh m2 day and it is very important to prepare a proper load data to meet the current situation of the target village which has 45 household numbers. By calculating the total load demand, the peak demand of that proposed village is 34kW. The fractions of energy production from PV array and diesel generator of the proposed PV Diesel BESS hybrid system using LF control strategy are 60 and 40 to meet the demand. Moreover, the proposed hybrid system based on LF control strategy provides the lowest TNPC, COE and carbon emission than the hybrid system based on CC control strategy according to the evaluation results. In contrast, the analysis of evaluation results shows that the PV Diesel ESS based on LF control choice is more economically possible than that system based on CC control. Phyu Phyu Win | Zin Mar "Performance Analysis of Autonomous Hybrid Distributed Generation Based on Typical Control Strategies for Rural Electrification in Myanmar" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26695.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/26695/performance-analysis-of-autonomous-hybrid-distributed-generation-based-on-typical-control-strategies-for-rural-electrification-in-myanmar/phyu-phyu-win
Integration of SPV/Biomass resources for sustainable energy supply in Leh: a ...IRJET Journal
This document summarizes a research study that models and optimizes a hybrid energy system for Leh, India using HOMER software. The proposed system integrates solar PV panels, biomass resources, and batteries. HOMER is used to simulate the system and analyze its technical and economic feasibility. The goal is to minimize costs while maximizing reliable energy supply given Leh's climate and demand patterns. Sensitivity analyses assess the impacts of variables like biomass availability and solar irradiance on system performance.
The document summarizes a study of an optimal grid-integrated solar PV system. A hybrid system was modeled using HOMER software to integrate a 25 kWp solar PV array with the existing electrical grid. Simulation results found the system could meet the local load of 69 kWh/day while selling excess solar energy to the grid. The optimal system achieved 79% renewable energy penetration and a net annual energy export of 17,505 kWh to the grid. The study contributes to the design and optimization of grid-connected solar PV systems.
Present situation of renewable energy in bangladesh, renewable energy resourc...Sk Sohag
This document summarizes renewable energy resources in Bangladesh. It finds that Bangladesh has significant potential for solar, wind, biogas, and other renewable sources. Around 70% of the population lacks access to electricity, most living in rural areas. Renewable resources could help meet energy demand and support development. Solar radiation is abundant year-round, making solar panels a promising option. Coastal areas experience average wind speeds over 5m/s, allowing for wind energy. Biogas can be produced from organic waste. Overall, renewable sources could help address Bangladesh's energy crisis if developed and utilized effectively.
Feasibility Study on Battery Energy Storage System for Mini gridijtsrd
Mini grids defined as a set of electricity generators and battery energy storage system is connected between the load side and the source side. A key feature of mini grids is that they can operate autonomously with no connection to a centralized grid. Gaw Cho village, Sagaing Division, Myanmar is selected because of the higher potential of solar energy. This paper presents the unbalance condition between the load side and the source side because the solar energy is changing under weather condition. Diesel generator is used as a backup system for this proposed area but the operation of the fuel cost increased for long term period. Here, battery energy storage system is used as a secondary supplier to balance between them. This paper focus on to used HOMER software for pointing out the result outcome not be oversizing the system requirement. Using real time data, storage characteristics and HOMER simulations, optimal sizing for both approaches were established. A well design min grid offered available tool for the rural electrification system. Nang Saw Yuzana Kyaing | June Tharaphe Lwin | Chris Tie Lin "Feasibility Study on Battery Energy Storage System for Mini-grid " Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27863.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/27863/feasibility-study-on-battery-energy-storage-system-for-mini-grid-/nang-saw-yuzana-kyaing
Auroville has been active in renewable energy generation since the early years, starting with windmills for water pumping and stand-alone solar PV systems with battery banks. In 2012 Auroville pioneered rooftop grid-connected solar energy by proposing to the Tamil Nadu Government that pilot projects may be undertaken in Auroville with grid-connectivity.
This document proposes a hybrid renewable energy system using solar, wind, and biomass power for a rural village in Uttarakhand, India. It analyzes the feasibility of the system using the HOMER software. The village has abundant solar and biomass resources due to its location and access to agricultural waste. The proposed system would help electrify the village in a sustainable way and reduce reliance on fossil fuels. Load data from the village is collected and the resources are analyzed to size an optimal hybrid system configuration using the HOMER optimization tool.
The document discusses load forecasting techniques used in Rajasthan, India. It provides background on why load forecasting is needed, an overview of power supply and demand in Rajasthan, and describes short-term load forecasting methods like neural networks used to predict load 15 minutes to a week in advance. Traditional techniques like regression and exponential smoothing are discussed along with modified methods. The results are used for generation and infrastructure planning, and both advantages like improved insight and disadvantages like inaccuracies are noted.
This document summarizes a research paper on the potential for solar power in India. It finds that:
1) India has high solar potential and is becoming a leader in solar development through initiatives like Jawaharlal Nehru National Solar Mission.
2) The costs of solar power are declining rapidly due to economies of scale, while coal costs are rising.
3) The analysis projects that solar power could reach grid parity with coal in India by 2016-2018 and capture a significant share of India's energy mix by 2022, helping to address India's major power issues.
Roadmap for Indonesia's Power Sector - Summary for Policy MakersGandabhaskara Saputra
- The study models different pathways for Indonesia's power system to meet energy and climate targets from 2018-2027, focusing on Java-Bali and Sumatra where most people and electricity consumption are located.
- Analysis using PLEXOS power system modeling software finds that if PLN continues overestimating demand and building excess coal capacity, over $12 billion could be wasted. Doubling renewable energy through wind and solar is comparable in cost and would reduce emissions 36%.
- A high renewables scenario coupled with energy savings could save $10 billion over 10 years compared to current plans, requiring lower costs and a long-term strategic renewable energy expansion plan with clear targets. Even with 43% renewables, security of
The document summarizes a seminar on energy efficiency and renewable energy held in Itanagar, Arunachal Pradesh. The seminar focused on the need for conservation of energy resources and use of renewable resources to meet growing energy demands. Speakers emphasized using renewable resources as fossil fuels are declining rapidly. Arunachal Pradesh has significant hydroelectric potential but many projects are facing delays. The seminar aimed to discuss issues, showcase technologies, and suggest ways forward for a sustainable energy future.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
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1) India has seen significant growth in renewable energy, especially solar and wind, over the last decade and has set a target of installing 500GW of renewable capacity by 2030.
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High electricity demand, reduction in fossil fuels and increasing demand towards solar energy, the integration of solar photovoltaic (PV) generation in the utility grid is gaining high popularity in India. Many distributed energy resources (DERs) are connected to the utility grid or microgrids with the help of power electronics interface, while interfacing power electronics with microgrids there are valid technical concerns from utilities about power quality and the impact of DG on the low voltage (LV) grid. This paper focuses on India’s Current Solar generation capacity and grid integration issues such as voltage, frequency regulation, active, reactive power control and power quality issues.
A Low-cost Renewable Energy Solution for Improved Energy Access in NigeriaIRJET Journal
This document discusses a low-cost renewable energy solution implemented in Afikpo, Nigeria to provide improved energy access. The residents of Afikpo had not received power from the national grid for many years. To address this, the authors designed and implemented a solar photovoltaic system for a residential building. They analyzed the power needs of the residence and designed a system using solar panels, batteries, an inverter, and charge controller. The system has provided the residents with uninterrupted power for six months. The residents have benefited from reliable power without noise or fuel costs. The authors conclude solar energy can provide a clean and reliable alternative for powering homes in Nigeria.
POTENTIAL STUDY ADDRESSING SHORTAGE OF POWER AND ECONOMIC GROWTH THROUGH FORE...IAEME Publication
India is densely populated and has high solar insolation, an ideal combination for using solar power in India. India is already a leader in wind power generation. India is now one of the top five solar energy developments worldwide as per Ernst & Young’s renewable energy attractiveness index. As per report by WATO-India, 2012, the Indian Renewable Energy business market is experiencing a growth rate of 15 %/yr and the opportunities for private investments are estimated to
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This document discusses the challenges and solutions related to large-scale integration of renewable energy sources into India's power grid. The key points are:
1. Integrating renewable energy is challenging due to its intermittent nature and geographical distribution far from load centers. This requires improved transmission infrastructure and balancing across regions.
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International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Techno economic analysis of SPV-DG hybrid model using HOMERIRJET Journal
This document summarizes a study that conducts a techno-economic analysis of a solar photovoltaic (SPV)-diesel generator (DG) hybrid energy system model implemented in Leh, India. The HOMER software is used to optimize and simulate the SPV-DG hybrid system. Simulation results are analyzed to determine the optimal sizing of SPV and DG components and overall system performance. A life cycle cost analysis is performed considering capital, operating, maintenance and fuel costs. The study also examines the environmental impacts of the SPV-DG system, focusing on reductions in greenhouse gas emissions and fossil fuel dependence.
Optimization towards cost effective solar mini grids in bangladeshDipta Majumder
People living in remote rural areas e.g. islands of Bangladesh don’t have access to electricity due to financial and technical challenges. Solar Photovoltaic (PV)-Diesel based hybrid mini grids can be a way to electrify remote rural areas of Bangladesh. However, solar energy is costly compared to conventional energy sources. Hence, optimization is essential to ensure success of solar mini grids in remote rural areas. Optimization of mini grid plant capacity based on demand is discussed. Diesel consumption and excess electricity from plant are the key optimization parameters. A case at Paratoli, Narsingdi, Bangladesh is taken into consideration to validate the optimization. Data is further analyzed to find out the future requirements and effects after optimization.
Optimal Hybrid Energy System for Rural Electrification in India using HOMER S...IRJET Journal
This document discusses the optimal design of a hybrid energy system for a village in India using the HOMER software. It analyzes a grid-connected hybrid system combining solar PV, diesel generator, battery storage, and grid connection. The system is designed to meet the village's daily electricity demand of 202 kWh and peak demand of 16.67 kW. Simulation results show the optimal system would include 14.6 kW of solar PV panels, 19 kW diesel generator, 56 batteries, and 16 kW converter. The levelized cost of electricity for this system would be $0.1903/kWh, lower than an off-grid system. The hybrid system would generate most power from the grid, but the solar PV and diesel generator
Performance Analysis of Autonomous Hybrid Distributed Generation Based on Typ...ijtsrd
It is undeniable fact that even though fossil fuels are likely more to fulfill the requirements of energy, the rare of natural resources and their harmful contents for the environment have directed people to search for new energy sources like renewable resources such as hydropower, biomass, wind, solar and other types of clean energy. In order to highlight the proposed methodology, PV Diesel generator DG with battery energy system BESS based on two typical control strategies, load following LF control strategy and cycle charging CC control strategy, have been analyzed by using HOMER Software to supply the Makyiyay village which is located at 22.02 north latitude and 96.56 east longitude in the Naungkhyo Township, Southern Shan State in Myanmar. The yearly average solar radiation of that area is 4.895kWh m2 day and it is very important to prepare a proper load data to meet the current situation of the target village which has 45 household numbers. By calculating the total load demand, the peak demand of that proposed village is 34kW. The fractions of energy production from PV array and diesel generator of the proposed PV Diesel BESS hybrid system using LF control strategy are 60 and 40 to meet the demand. Moreover, the proposed hybrid system based on LF control strategy provides the lowest TNPC, COE and carbon emission than the hybrid system based on CC control strategy according to the evaluation results. In contrast, the analysis of evaluation results shows that the PV Diesel ESS based on LF control choice is more economically possible than that system based on CC control. Phyu Phyu Win | Zin Mar "Performance Analysis of Autonomous Hybrid Distributed Generation Based on Typical Control Strategies for Rural Electrification in Myanmar" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26695.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/26695/performance-analysis-of-autonomous-hybrid-distributed-generation-based-on-typical-control-strategies-for-rural-electrification-in-myanmar/phyu-phyu-win
Integration of SPV/Biomass resources for sustainable energy supply in Leh: a ...IRJET Journal
This document summarizes a research study that models and optimizes a hybrid energy system for Leh, India using HOMER software. The proposed system integrates solar PV panels, biomass resources, and batteries. HOMER is used to simulate the system and analyze its technical and economic feasibility. The goal is to minimize costs while maximizing reliable energy supply given Leh's climate and demand patterns. Sensitivity analyses assess the impacts of variables like biomass availability and solar irradiance on system performance.
The document summarizes a study of an optimal grid-integrated solar PV system. A hybrid system was modeled using HOMER software to integrate a 25 kWp solar PV array with the existing electrical grid. Simulation results found the system could meet the local load of 69 kWh/day while selling excess solar energy to the grid. The optimal system achieved 79% renewable energy penetration and a net annual energy export of 17,505 kWh to the grid. The study contributes to the design and optimization of grid-connected solar PV systems.
Present situation of renewable energy in bangladesh, renewable energy resourc...Sk Sohag
This document summarizes renewable energy resources in Bangladesh. It finds that Bangladesh has significant potential for solar, wind, biogas, and other renewable sources. Around 70% of the population lacks access to electricity, most living in rural areas. Renewable resources could help meet energy demand and support development. Solar radiation is abundant year-round, making solar panels a promising option. Coastal areas experience average wind speeds over 5m/s, allowing for wind energy. Biogas can be produced from organic waste. Overall, renewable sources could help address Bangladesh's energy crisis if developed and utilized effectively.
Feasibility Study on Battery Energy Storage System for Mini gridijtsrd
Mini grids defined as a set of electricity generators and battery energy storage system is connected between the load side and the source side. A key feature of mini grids is that they can operate autonomously with no connection to a centralized grid. Gaw Cho village, Sagaing Division, Myanmar is selected because of the higher potential of solar energy. This paper presents the unbalance condition between the load side and the source side because the solar energy is changing under weather condition. Diesel generator is used as a backup system for this proposed area but the operation of the fuel cost increased for long term period. Here, battery energy storage system is used as a secondary supplier to balance between them. This paper focus on to used HOMER software for pointing out the result outcome not be oversizing the system requirement. Using real time data, storage characteristics and HOMER simulations, optimal sizing for both approaches were established. A well design min grid offered available tool for the rural electrification system. Nang Saw Yuzana Kyaing | June Tharaphe Lwin | Chris Tie Lin "Feasibility Study on Battery Energy Storage System for Mini-grid " Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27863.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/27863/feasibility-study-on-battery-energy-storage-system-for-mini-grid-/nang-saw-yuzana-kyaing
Auroville has been active in renewable energy generation since the early years, starting with windmills for water pumping and stand-alone solar PV systems with battery banks. In 2012 Auroville pioneered rooftop grid-connected solar energy by proposing to the Tamil Nadu Government that pilot projects may be undertaken in Auroville with grid-connectivity.
This document proposes a hybrid renewable energy system using solar, wind, and biomass power for a rural village in Uttarakhand, India. It analyzes the feasibility of the system using the HOMER software. The village has abundant solar and biomass resources due to its location and access to agricultural waste. The proposed system would help electrify the village in a sustainable way and reduce reliance on fossil fuels. Load data from the village is collected and the resources are analyzed to size an optimal hybrid system configuration using the HOMER optimization tool.
The document discusses load forecasting techniques used in Rajasthan, India. It provides background on why load forecasting is needed, an overview of power supply and demand in Rajasthan, and describes short-term load forecasting methods like neural networks used to predict load 15 minutes to a week in advance. Traditional techniques like regression and exponential smoothing are discussed along with modified methods. The results are used for generation and infrastructure planning, and both advantages like improved insight and disadvantages like inaccuracies are noted.
This document summarizes a research paper on the potential for solar power in India. It finds that:
1) India has high solar potential and is becoming a leader in solar development through initiatives like Jawaharlal Nehru National Solar Mission.
2) The costs of solar power are declining rapidly due to economies of scale, while coal costs are rising.
3) The analysis projects that solar power could reach grid parity with coal in India by 2016-2018 and capture a significant share of India's energy mix by 2022, helping to address India's major power issues.
Roadmap for Indonesia's Power Sector - Summary for Policy MakersGandabhaskara Saputra
- The study models different pathways for Indonesia's power system to meet energy and climate targets from 2018-2027, focusing on Java-Bali and Sumatra where most people and electricity consumption are located.
- Analysis using PLEXOS power system modeling software finds that if PLN continues overestimating demand and building excess coal capacity, over $12 billion could be wasted. Doubling renewable energy through wind and solar is comparable in cost and would reduce emissions 36%.
- A high renewables scenario coupled with energy savings could save $10 billion over 10 years compared to current plans, requiring lower costs and a long-term strategic renewable energy expansion plan with clear targets. Even with 43% renewables, security of
The document summarizes a seminar on energy efficiency and renewable energy held in Itanagar, Arunachal Pradesh. The seminar focused on the need for conservation of energy resources and use of renewable resources to meet growing energy demands. Speakers emphasized using renewable resources as fossil fuels are declining rapidly. Arunachal Pradesh has significant hydroelectric potential but many projects are facing delays. The seminar aimed to discuss issues, showcase technologies, and suggest ways forward for a sustainable energy future.
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Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Neural network optimizer of proportional-integral-differential controller par...IJECEIAES
Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
A review on features and methods of potential fishing zoneIJECEIAES
This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naïve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.
Electrical signal interference minimization using appropriate core material f...IJECEIAES
As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Data Control Language.pptx Data Control Language.pptx
Energy demand forecasting of remote areas using linear regression and inverse matrix analysis
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 14, No. 1, February 2024, pp. 129~139
ISSN: 2088-8708, DOI: 10.11591/ijece.v14i1.pp129-139 129
Journal homepage: http://ijece.iaescore.com
Energy demand forecasting of remote areas using linear
regression and inverse matrix analysis
Md. Tanjil Sarker1,3
, Mohammed Jaber Alam2
, Gobbi Ramasamy1
, Mohammed Nasir Uddin3
1
PV Energy Storage Lab, Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia
2
Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia
3
Department of Computer Science and Engineering, Jagannath University, Dhaka, Bangladesh
Article Info ABSTRACT
Article history:
Received Sep 3, 2022
Revised May 7, 2023
Accepted May 11, 2023
Efficient energy demand forecasting is pivotal for addressing energy
challenges in remote areas of Bangladesh, where reliable access to energy
resources remains a concern. This study proposes an innovative approach that
combines linear regression analysis (LRA) and inverse matrix calculation
(IMC) to forecast energy demand accurately in these underserved regions. By
leveraging historical energy consumption data and pertinent predictors, such
as meteorological conditions, population dynamics, economic indicators, and
seasonal patterns, the model provides reliable forecasts. The application of the
proposed methodology is demonstrated through a case study focused on
remote regions of Bangladesh. The results showcase the approach's
effectiveness in capturing the intricate dynamics of energy demand and its
potential to inform sustainable energy management strategies in these remote
areas. This research contributes to the advancement of energy planning and
resource allocation in regions facing energy scarcity, fostering a path towards
improved energy efficiency and development. These techniques can be
applied to estimate short-term electricity demand for any rural or isolated
region worldwide.
Keywords:
Electrical power generation
Energy demand
Inverse matrix
Linear regression
Load forecasting
Remote area
Short-term and long-term
This is an open access article under the CC BY-SA license.
Corresponding Author:
Gobbi Ramasamy
PV Energy Storage Lab, Faculty of Engineering, Multimedia University
Cyberjaya, Malaysia
Email: gobbi@mmu.edu.my
1. INTRODUCTION
In order to ensure the effective allocation and usage of energy resources, energy demand forecasting
is of utmost importance, particularly in distant places where energy accessibility continues to be problematic.
Accurate energy demand projection is sometimes made more difficult by remote places particular features,
such as their poor infrastructure and remoteness from other areas. In Bangladesh, a nation that struggles with
inequalities in its energy supplies, the need for exact forecasting in outlying areas is even more critical. The
main objective of this work is to provide a unique method for predicting energy consumption in rural areas of
Bangladesh utilizing inverse matrix computation and linear regression. This approach aims to provide a tailored
solution for energy forecasting that can effectively address the complexities of remote energy consumption
patterns by combining historical energy consumption data with pertinent influencing factors, such as
meteorological parameters, demographic trends, economic indicators, and seasonal variations.
Although Bangladesh has made great strides in developing its energy infrastructure, the government
still has issues providing fair access to power throughout the nation. Energy usage varies in remote areas
because of geographical factors that are specific to particular regions. Due to data constraints, non-linear
interactions, and seasonal dynamics, conventional forecasting techniques frequently find it difficult to take into
2. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 14, No. 1, February 2024: 129-139
130
account the complexity of such scenarios. This study proposes a methodology that not only considers these
challenges but also utilizes the interplay of linear regression and inverse matrix analysis to provide accurate
energy demand forecasts.
In Bangladesh, the per-person electricity consumption is one of the lowest in the world, standing at
136 kWh. This implies that almost half of the country's energy usage comes from non-commercial sources,
such as wood fuel, animal waste, and crop residues. The nation has a significant abundance of natural gas,
while its coal and oil reserves are meager [1]. Commercial energy usage is predominantly reliant on natural
gas, making up 66%, with oil, hydropower, and coal following suit. Electricity powers most of the country's
financial activities. However, with an annual usage of just 321 kWh per person, only 70% of Bangladesh's
population has access to electricity, with the government setting a 20 GW target in 2019, expected to increase
to 61 GW by 2041. Regrettably, Bangladesh's power sector is grappling with various issues, such as corruption
in administration, high system losses, and project delays in constructing new power plants. These issues must
be dealt with to improve the countries electricity infrastructure [2]. The countries power generation capability
hasn't been able to keep up with demand for the last ten years now. Even so, the government of Bangladesh
has made long-standing arrangements to address the countries energy problems, and it has begun to put those
arrangements into action. Planned increases in electricity generation from 2021 to 2041 are shown in Figure 1.
This study forecasts reactive demand at every transmission substation in light of a power factor of 90% for the
transmission enquiry study for the years 2013, 2015, 2020, 2025, and 2030, based on a survey of 2016
information and interactions with Bangladesh power development board (BPDB) and power grid company of
Bangladesh (PGCB) [3].
Figure 1. Power plant generation capacity expansion plans
Approximately 10% of the population has used petroleum natural gas, mainly in rural areas where it
is not readily available [4]. People in rural areas use biomass energy sources like firewood, cow feces, and
farming leftovers to heat their homes and cook their food. The most common form of lighting in rural areas is
the lamp oil-based illumination. It was decided to continue the installation of new gas connections in
manufacturing companies in April of this year, after they were originally scheduled to be completed in 2009
[5]. As a result, new gas connections in the residence house have been placed on hold "until further notice"
because they were confined and expensive. So, in urban areas, individuals rely heavily on electric appliances
in their homes. To maintain uninterrupted electrical supply across the country, there is not enough electricity
generation and there is no way to estimate demand. Because of this, load shedding has been taking place.
Currently, Bangladesh's government is planning to develop its power producing plant in order to ensure that
there will be no interruptions in the supply of electricity [5].
There are numerous studies on how to predict the energy needs of a remote location [1], [6]. But the
key limitation of these research papers is the energy demand histories are expected as known, which is not
genuine. The use of solar panels in rural regions has recently been advocated using mixed-integer linear
programming [7]. In comparison to traditional power generation, solar energy is more expensive and comes
with a slew of drawbacks. In order to keep costs down, a remote location's energy demand must be accurately
estimated before any new power lines or renewable microgrid systems can be built. The ones normally used
by scientists are [8]: i) time series methods, ii) artificial intelligence (AI) based procedures [9], iii) regression-
based analysis model, iv) bottom-up technique, v) top-down technique, vi) additive control methods, vii) matrix
analysis, and viii) machine learning.
0
10000
20000
30000
40000
50000
60000
70000
2020 2025 2030 2035 2040 2045
Capacity
in
MW
Years
Generation capacity expansion plans
3. Int J Elec & Comp Eng ISSN: 2088-8708
Energy demand forecasting of remote areas using linear regression and inverse … (Md Tanjil Sarker)
131
Kolapara and Kuakata, the locations under consideration, are two of Bangladesh's most important
islands. The panoramic sea beach is another name for this location. Kolapara and Kuakata represent two distinct
yet interconnected aspects of Bangladesh's coastal region. While Kolapara showcases the challenges and
livelihoods of a coastal sub-district with an emphasis on agriculture, Kuakata shines as a picturesque tourist
destination famous for its beach beauty and natural attractions. Both locations contribute to the diverse fabric
of Bangladesh's coastal landscape, highlighting the importance of sustainable development and resilience in
the face of environmental and economic changes.
The remainder of the paper is outlined as follows: linear regression analysis (LRA) [10], [11] and
inverse matrix calculation (IMC) [11] for energy demand forecasting are briefly discussed in section 2 of this
article. After that, a short description of the research location and the data collection are provided. According
to section 4, it is explained how to use regression analysis and significant outcomes with graphical
representation to forecast energy consumption in an off-grid location and displays the inverse matrices analysis
approach. Lastly, in section 5, we offer some closing thoughts and ideas for further research.
2. LITERATURE REVIEW
2.1. Load forecasting
Load forecasting is a critical component of energy management and planning, encompassing the
prediction of future electricity or energy demand based on historical data, external factors, and emerging trends.
Accurate load forecasting is essential for ensuring reliable power supply, efficient resource allocation, and
optimal operation of energy systems [12]. It plays a crucial role in addressing the challenges posed by
fluctuating demand patterns, varying consumer behavior, and the integration of renewable energy sources into
the grid. The complexity of modern energy systems, coupled with the increasing penetration of distributed
energy resources and the advent of smart grid technologies, has amplified the significance of load forecasting.
Accurate forecasts enable utilities and energy providers to make informed decisions regarding capacity
expansion, infrastructure upgrades, and demand response strategies. Moreover, they facilitate cost-effective
energy procurement and help prevent potential grid instability due to demand-supply imbalances.
The following are examples of load forecasting:
a. Short-term forecasts: For short-term load forecasting, a number of parameters, including time, weather data,
and prospective client classifications, must be taken into account [13]. The day of the year, the week, and
the time of day are all aspects to consider. The load is affected by the weather. In fact, short-term load
projections rely heavily on the weather characteristics that have been predicted. The forecasting of loads
can take into account a variety of weather variables. Predictors of demand, like temperature and humidity,
are the most common. Daily operations and unit commitment are supported by this data, which is used to
support system management. With short-term power load forecasting, utility company managers are
provided with information about future electric load demand to help them run more efficient and reliable
day-to-day operations.
b. Medium-term forecasts: A variety of elements go into the medium and long-term projections, including
historical load and weather data, customer demographics, the types and ages of local appliances, and a
variety of other variables, such as economic and demographic trends. Scheduled fuel deliveries and
equipment maintenance are two of its primary functions [14].
c. Long-term forecasts: In most cases, it is utilized to provide electric utility company management with
forecasts of upcoming requirements for expansion, equipment acquisitions, or staffing [15].
Load forecasting is a fundamental tool for ensuring the reliability, efficiency, and sustainability of
energy systems. It makes it possible for customers, governments, and energy suppliers to prepare in advance,
adjust to changing circumstances, and maximize resource use. Accurate load forecasting is a crucial facilitator
of efficient energy management and a significant driver of the transition to a more resilient and sustainable
energy future as the energy environment continues to change.
2.2. Linear regression analysis
A fundamental statistical method called LRA is used to represent the connection between one or more
independent variables (predictors) and a dependent variable (response). Making forecasts, figuring out the
strength and direction of their connections, and comprehending the linear link between variables are all things
that may be done with it to great advantage. Due to its simplicity and interpretability, LRA is frequently used
in a variety of disciplines, including economics, social sciences, engineering, and data science. Regression
analysis is used to analyze the relationships between two or more variables [16]–[18]. Numerous modeling and
analytic strategies are used to investigate the relationship between one dependent variable and several
independent variables [19]. In this kind of study, off-grid regions are considered as dependent variables, whilst
on-grid areas are handled as independent variables [20].
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The simplest version of linear regression assumes that the independent variable(s) and dependent
variable have a linear relationship. Finding the best-fitting model that reduces the discrepancies between the
anticipated values. The actual observed value is the objective. The equation of a linear regression line is often
represented as (1):
𝑦 = 𝑏0 + 𝑏1𝑥 + 𝜖. (1)
where y is the dependent variable. 𝑥 is the independent variable, 𝑏0 is the intercept. 𝑏1 is the coefficient for the
independent variable 𝑥. 𝜖 represents the error term or residual, accounting for unexplained variability. Linear
regression analysis is a versatile and widely used technique for understanding the relationships between
variables and making predictions based on historical data. Despite its simplicity, LRA remains a powerful tool
in data analysis, hypothesis testing, and decision-making across diverse domains. A proper understanding of
its assumptions, limitations, and appropriate usage is essential for obtaining meaningful insights from the data.
2.3. Inverse matrix calculation
There are many research conducting using inverse matrix calculation [21]–[23]. Four types of loads
can be found in any given location, and they are all subdivided into one another: household loads, commercial
loads, irrigation loads, and industrial loading. Factors like population, per capita revenue and adult literacy rate
are also taken into consideration when determining the amount of work that must be done [11].
2.3.1. Local load demand
The local load may be affected by factors such as population density and living standards. Per capita
income and the percentage of adults who are able to read are two factors that contribute to the disparity in the
standard of living. All of these variables change throughout time. The local load, 𝐿𝐿 may then be expressed as (2),
𝐿𝐿𝐷(𝑡) = 𝑓1 (𝑅𝐿 (𝑡), 𝑃𝑂 (𝑡), 𝑅𝑃(𝑡)) (2)
where, 𝑅𝐿 (𝑡)=Adult reading ability rate at time t, 𝑃𝑂 (𝑡)=Populace at time t, 𝑅𝑃(𝑡)=Per capita revenue at time t.
2.3.2. Load demand of manufacturing
Per capita income, inland communication in total area, distance from the local town, reading ability
rate, and farming land in total area may all affect manufacturing load in a given location. Communication
across the sea may be the primary mode of communication in some distant regions. That is why it is important
to include both land and water routes in the communication [11]. This manufacturing load 𝑀𝐿 can be calculated
as (3),
𝑀𝐿𝐷(𝑡) = 𝑓2 (𝑅𝑃 (𝑡), 𝐿𝑅 (𝑡),𝑇𝐷(𝑡), 𝐿𝐹(𝑡)) (3)
where, 𝑅𝑃 (𝑡)=per capita revenue, 𝐿𝑅 (𝑡)=inland communication length in per unit area at time 𝑡,
𝑇𝐷(𝑡)=distance from local town, 𝐿𝐹(𝑡)=farming land in percent of total area at time 𝑡.
2.3.3. Load demand of commercial
It typically refers to the demand for electrical power or energy that business buildings and
establishments use. Offices, retail stores, restaurants, malls, and other non-residential buildings are examples
of commercial buildings where business operations are conducted. In general, the commercial load is
influenced by factors such as per capita income, inland communication per unit area, and distance from the
next town. The commercial load, 𝐶𝐿 may then be expressed as (4),
𝑐𝐿𝐷(𝑡) = 𝑓3 (𝑅𝑃 (𝑡), 𝐿𝑅 (𝑡), 𝑇𝐷(𝑡)) (4)
2.3.4. Load demand of farming
Per capita income and farming land area are the two most important factors affecting farming's burden.
This industrial load 𝐹𝐿 can be calculated as (5),
𝐹𝐿𝐷(𝑡) = 𝑓
4 (𝐿𝐹 (𝑡),𝑅𝑃 (𝑡)) (5)
The total electrical load demand, 𝐸𝐿𝐷(𝑡) in an isolated area is the sum of the above four loads. That is (6),
𝐸𝐿𝐷(𝑡) = 𝐿𝐿𝐷 (𝑡) + 𝑀𝐿𝐷(𝑡) + 𝐶𝐿𝐷(𝑡) + 𝐹𝐿𝐷(𝑡) (6)
5. Int J Elec & Comp Eng ISSN: 2088-8708
Energy demand forecasting of remote areas using linear regression and inverse … (Md Tanjil Sarker)
133
Therefore, the load demand of an isolated area can be expressed as (7),
𝑇𝐿𝐷(𝑡) = 𝑓
4(𝑅𝐿(𝑡), 𝑃0(𝑡), 𝑅𝑝(𝑡), 𝐿𝑅(𝑡),𝑇𝐷(𝑡), 𝐿𝐹(𝑡)) (7)
There are six time-dependent variables in equation, however this does not mean that the load depends on them.
To generate load, however, not all variables must be equal. Let Q1, Q2, Q3, Q4, Q5, and Q6 represent the
weighting factors by which each time varying factor 𝑅𝐿(𝑡), 𝑃0(𝑡), 𝑅𝑝(𝑡), 𝐿𝑅(𝑡), 𝑇𝐷(𝑡) and 𝐿𝐹(𝑡) respectively
contributes towards the load growth. The weighting factors, [Q] are also random in nature. It is possible that
they'll differ depending on where you live.
It is now possible to represent the load as (8),
𝐸𝐿𝐷(𝑡) = [𝑄] ×
[
𝑅𝐿(𝑡)
𝑃𝑂(𝑡)
𝑅𝑃(𝑡)
𝐿𝑅(𝑡)
𝑇𝐷(𝑡)
𝐿𝐹(𝑡)]
(8)
From the equation, the weight factors [Q] can be calculated as (9).
[𝑄] = 𝐸𝐿𝐷 𝑇
× 𝑃𝑖𝑛𝑣
[
𝑅𝐿(𝑡)
𝑃𝑂(𝑡)
𝑅𝑃(𝑡)
𝐿𝑅(𝑡)
𝑇𝐷(𝑡)
𝐿𝐹(𝑡)]
(9)
IMC is a fundamental mathematical operation with diverse applications in various fields. It plays a
crucial role in solving systems of equations, transformations, and numerous other mathematical tasks that
involve matrices. However, care must be taken to consider conditions, computational complexity, and
numerical stability when dealing with inverse matrices in practical applications.
3. DATA COLLECTION
The data collection process is a systematic approach to gathering information for research, analysis,
or decision-making purposes. It involves planning, designing, implementing, and managing strategies to
acquire relevant and accurate data. An effective data collection process ensures the quality and integrity of the
collected data. Collecting high-quality data is a crucial step in performing accurate and meaningful regression
analysis. The data will directly impact the results and insights derived from analysis. Three stages of data
collection are involved. In the first place, I went to the Kalapara Upazila Nirbahi Officer (UNO) office to
collect the time-invariant data such as population (𝑃𝑂), adult literacy rate (𝑅𝐿), per capita income (𝑅𝑃), land
communication strength (𝐿𝑅) and agricultural land (𝐿𝐹), distance from main land (𝑇𝐷), tourist visitor (𝑇𝑣). After
that, we headed to the Kalapara Bangladesh Rural Electrification Board (BREB) office to collect the town's
maximum and average load. For more trustworthy data and an understanding of per-capita income, I then
visited the Bangladesh Statistical Bureau. The Kalapara area is connected to the grid, while the Kuakata area
is not. The following are the results of the data collection for time invariant variables shown in Table 1. The
regression table of Kalapara (Ka) and Kuakata (Ku) is shown in Table 2. Tables 3 and 4 are the average
demand/load and maximum demand/load of Kalapara town from 2019-2022 by month respectively.
Table 1. The data collected from UNO office of Kalapara
Data Kalapara (on-grid) Kuakata (off-grid)
𝑃𝑂 (1000) 19.92 10.51
𝑅𝐿 (%) 75.08 65.08
𝑅𝑃 (USD) 79.17 59.63
𝐿𝑅 (KM) 12.11 3.13
𝐿𝐹 (Hector) 1.6 1.45
𝑇𝐷 (KM) 3.1 20
𝑇𝑣 (1000) 0.5 1.2
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134
Table 2. The regression table of Kalapara (Ka) and Kuakata (Ku)
Ka Ku Ka^2 KaKu
19.92 10.51 396.81 209.36
75.08 65.08 5037.01 4886.21
79.17 59.63 6267.89 4720.91
12.11 3.13 146.65 37.9043
1.6 1.45 2.56 2.32
3.1 20 9.61 62
0.5 1.2 0.25 0.6
∑Ka=191.48 ∑ Ku=161 ∑Ka^2=11860.78 ∑KaKu=9919.304
Table 3. The average demand/load of Kalapara
town from 2019-2022 by month
Month Average demand/load (KW)
2022 2021 2020 2019
January 101.9814 94.613 80.6192 72.4458
February 99.6904 92.8793 83.7771 78.6378
March 97.9567 91.0217 84.582 84.9536
April 102.3529 99.5666 84.8297 91.3932
May 96.7183 99.3189 90.031 90.774
June 107.3065 90.4025 96.2229 85.5728
July 103.9009 98.7616 97.5851 87.1207
August 102.7864 92.8793 87.9257 88.6068
September 86.6873 102.0433 90.2786 93.6842
October 104.5201 105.7585 90.5263 91.8266
November 96.4706 95.1084 88.2972 87.0588
December 97.2136 94.1176 81.0526 85.6966
Table 4. The maximum demand/load of Kalapara
town from 2019-2022 by month
Month Maximum demand/load (KW)
2022 2021 2020 2019
January 226.6254 210.2786 179.195 160.9907
February 221.4241 206.4396 186.192 174.8607
March 217.5851 202.291 188.0495 188.7926
April 227.4923 221.3003 188.5449 203.096
May 214.7988 220.805 200.1238 201.7337
June 238.5759 200.805 201.4241 190.2167
July 231.0217 219.5046 216.904 193.6842
August 228.4211 206.5015 195.4799 197.0279
September 192.5077 226.8111 200.743 208.2972
October 232.2601 235.0464 201.2384 204.0867
November 214.2415 211.4551 196.2229 193.4985
December 216.0991 209.2879 180.1238 190.4644
It is necessary to know the area's history in order to compute the weighted average value of these
variables. Another alternative is to look at a location that has some of the isolated area's characteristics. This is
the key contribution of this work. The practical execution of the proposed strategy will shed light on this issue.
4. RESULTS AND DISCUSSION
4.1. Load forecasting using LRA
In this section, we present the results of our load forecasting study using regression analysis. We focus
on the key findings derived from the regression model and discuss their implications for accurate load
prediction. The performance of the regression model was evaluated through the coefficient of determination,
which quantifies the proportion of variability in the load data explained by the independent variables. The
regression value obtained for our model was 0.83, indicating that approximately 83% of the load variation can
be accounted for by the predictor variables integrated into the model. This suggests a substantial relationship
between the predictors and the load in the short term.
Load forecasting using regression analysis of (10):
𝐾𝑢 = 𝐴 + 𝑅 𝐾𝑎 (10)
where
𝑅 =
(∑ 𝐾𝑎𝐾𝑢−
∑ 𝑲𝒂 ∑ 𝑲𝒖
𝒏
)
(
∑ 𝑲𝒂𝟐−(∑ 𝑲𝒂)
𝟐
𝒏
)
= (
9919.304 −
191.48∗161
7
11860.78 −
191.482
7
) = 0.8327 (11)
𝐴 = ∑ 𝐾𝑢/𝑛 − ∑
𝐾𝑎
𝑛
= 23 – 0.83 ∗ 27.3 = 30 (12)
𝐾𝑢 = 𝐴 + 𝑅 𝐾𝑎 →= 0.30 + 0.8327 𝐾𝑎
when
𝐾𝑎 = 101.9814 𝐾𝑊 (𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑙𝑜𝑎𝑑 𝑜𝑓 𝐽𝑎𝑛𝑢𝑎𝑟𝑦 2022 𝑜𝑓 𝐾𝑎𝑙𝑎𝑝𝑎𝑟𝑎).
= 0.30 + 0.8327 ∗ 101.9814
= 85.22 𝐾𝑊 (𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑙𝑜𝑎𝑑 𝑜𝑓 𝐽𝑎𝑛𝑢𝑎𝑟𝑦 2022 𝑜𝑓 𝐾𝑢𝑎𝑘𝑎𝑡𝑎)
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Table 5 summarizes the average and maximum demand of Kuakata for 2022 based on Kalapara's 2022
load using regression analysis and shown in Figure 2. In this study, we employed regression analysis to forecast
short-term load patterns, and the results have provided valuable insights into the dynamic behavior of energy
demand. Our analysis underscores the significance of considering key predictor variables to achieve accurate
short-term load predictions.
Table 5. The estimated average and maximum load of Kuakata
Month Average demand/load (KW) 2022 Maximum demand/load (KW) 2022
January 85.2199 189.011
February 83.3122 184.6798
March 81.8685 181.4831
April 85.5293 189.7328
May 80.8373 179.163
June 89.6541 198.9622
July 86.8183 192.6718
August 85.8902 190.5062
September 72.4845 160.6012
October 87.3339 193.703
November 80.6311 178.6989
December 81.2498 180.2457
Figure 2. The graphical diagram of estimated average and maximum load of Kuakata, left: bar, right: line
4.2. Load forecasting using IMC
It is customary to utilize the Moore–Penrose pseudoinverse (henceforth, just pseudoinverse) to
compute a "best fit" (least squares) solution to a non-unique set of linear equations [24]–[26]. Finding the
smallest (Euclidean) norm solution to a linear equation system with many solutions is another use [11], [27].
In linear algebra, the pseudoinverse makes it easier to state and prove results [9], [28], [29]. The IMC-based
load forecasting method was evaluated based on its ability to accurately predict load values for a specified time
period. The calculated root mean squared error (RMSE) between the forecasted load values and the actual load
data was found to be very small units. This indicates a relatively small deviation between the forecasted values
and the actual load, suggesting that the IMC approach effectively captures load trends. Matrix study estimates
the average and maximum load for Kuakata, with Kalapara representing the on-grid area and Kuakata
representing the off-grid territory. Table 6 shows the estimated average and maximum load of Kuakata using
inverse matrix analysis and shown in Figure 3.
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Table 6. The estimated average and maximum load of Kuakata
Month Average demand/load (KW) 2022 Maximum demand/load (KW) 2022
January 90.3331 207.9121
February 88.3109 203.1478
March 86.7806 199.6314
April 90.6611 208.7061
May 85.6875 197.0793
June 95.0333 218.8584
July 92.0274 211.939
August 91.0436 209.5568
September 76.8336 176.6613
October 92.5739 213.0733
November 85.469 196.5688
December 86.1248 198.2703
Figure 3. The graphical diagram of estimated average and maximum load of Kuakata. Left: bar, right: line
In conclusion, our load forecasting approach utilizing IMC offers a practical and accurate method for
predicting load variations. By effectively incorporating external factors such as temperature and day of the
month, our approach contributes to the arsenal of tools available for enhancing energy management and
ensuring a stable and reliable energy supply. As the energy landscape evolves, accurate load forecasting
remains pivotal, and our study contributes to advancing this critical facet of modern energy systems.
4.3. Load forecasting comparison between LRA and IMC
Two separate approaches are used to forecast the amount of traffic in this particular patch of work.
The results of the comparison demonstrate that the two methods yielded roughly the same estimates of
electricity consumption. Figure 4 shows the comparison of estimated average load of Kuakata using two
methods. Short-term forecasting was used in this case. The results would be more exact and precise if more
aspects such as time, temperature, area, peak and off-peak time, lifestyle of the people, etc. were taken into
consideration. However, this research anticipated demand is rather realistic because it is based on on-load data.
Electric utility companies will be able to use this information to help with purchasing and generation of electric
power [30], [31], load switching and infrastructure development. Above all, the mathematical model can be
used in any off-grid or isolated island setting.
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Figure 4. The comparison of estimated average load of Kuakata using two methods
5. CONCLUSION
In this study, we embarked on a comprehensive exploration of energy demand forecasting for remote
areas through the combined application of linear regression and inverse matrix analysis. The amalgamation of
these techniques offered valuable insights into the intricacies of energy consumption patterns in regions where
access to reliable energy sources is crucial. The purpose of this research methodology is to determine the
average and maximum load of a remote location to aid the government in estimating the potential load
requirements for constructing a power plant in the future. The study team successfully applied a regression
analysis strategy to this end. The efficiency of the approach utilized was demonstrated by a comparison of the
regression analysis findings with those using matrices. Both methods provided results that were almost similar.
Energy consumption for remote places has been predicted thanks to the interaction between linear regression
and inverse matrix analysis. Our research emphasizes the significance of taking into account a variety of
influencing elements, enabling precise forecasts that serve as the basis for energy planning and resource
management. Our study significantly contributes to the energy independence and resilience of distant regions
as they grow and work toward sustainable development, promoting a better future for these neglected places.
The study recommends the use of artificial intelligence (AI) and machine learning algorithms for
future load forecasting work. The researcher can look into how combining smart grid and internet of things
(IoT) devices might deliver real time data for demand forecasts. These approaches have the potential to provide
more accurate and reliable predictions, which can help in planning and constructing power plants in isolated
regions.
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BIOGRAPHIES OF AUTHORS
Md. Tanjil Sarker obtained his Ph.D. degree in engineering in the Faculty of
Engineering, Multimedia University, Malaysia in 2022. He has been a research scholar in the
same institution for four years. He has completed his M.Sc. degree in computer science and
engineering from Jagannath University, Dhaka, Bangladesh in 2017. He received the B.Sc.
degree in electrical and electronic engineering and MBA degree in human resource management
from Bangladesh University, Dhaka, Bangladesh in 2013 and 2015, respectively. He was a
graduate student member in the IEEE Student Branch of the Malaysia section. He has authored
and co-authored several publications in the field of engineering. He has conducted much
research in relevant fields. His research interests are in system identification, signal processing
and control, power system analysis and high voltage engineering, renewable energy and solar
system. He can be contacted at email: tanjilbu@gmail.com.
Mohammed Jaber Alam has been pursuing his Ph.D. degree from CQ University,
Australia. He is a research fellow at the School of Engineering and Technology, CQ University.
He has completed his Master of Engineering Science by research from Multimedia University,
Malaysia in 2019. He has been a research scholar in the same institution for a couple of years.
Previously in 2016, he has completed his Bachelor of Engineering Science degree with
distinction achieving the best CGPA among the departments from IIUC, Bangladesh. He has
authored and co-authored several publications in the field of engineering. His research interests
include wireless communication, antenna systems, electrical systems, and semiconductor
electronics fields. He can be contacted at email: alam.jaber42@gmail.com.
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Gobbi Ramasamy received the bachelor’s degree in electrical engineering from
University of Technology, Malaysia, and the master’s degree in technology management from
the National University of Malaysia, and the Ph.D. degree in the area of torque control of
switched reluctance motors from Multimedia University, Malaysia. He was an R&D Engineer
in an electronics company before becoming a lecturer in electrical and electronics engineering.
He has supervised many research projects on power electronics, variable-speed drives,
automation, and domestic electrical installations. He is a project leader and member of various
government research projects related to electric motors and drives system. He is a consultant
providing solutions for many problems associated with electric motors and drives system for
various industries. He is an associate professor in faculty of Engineering, Multimedia
University, Malaysia. He can be contacted at email: gobbi@mmu.edu.my.
Mohammed Nasir Uddin is a professor in the Department of Computer Science
and Engineering at Jagannath University, Bangladesh. He was a faculty member in the
Department of Computer Science and Engineering at Moscow Power Engineering Institute
(Technical University) Moscow, Russia from February 2001 to June 2010. He received a Ph.D.
in computer science from Moscow Power Engineering Institute (Technical University),
Moscow. Russia. His areas of interest include cyber security and digital forensic. He can be
contacted at email: nasir@cse.jnu.ac.bd.