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Karnilius, Gideon Fwah, John Ibanga Isaac, and Rabiu Falama. "Smart Grid Technologies: Advancements and Applications in Nigeria." Journal of Multidisciplinary Science: MIKAILALSYS 2, no. 3 (2024): 359–70. http://dx.doi.org/10.58578/mikailalsys.v2i3.3777.
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This study explores the impact of smart grid technologies on the modernization of power grids in response to evolving energy demands and the integration of renewable energy sources in Nigeria. It aims to empirically assess advancements in smart grid technologies, focusing on four key objectives: eval_uating the impact of smart meters on energy consumption and peak demand reduction, analyzing the effectiveness of Advanced Distribution Management Systems (ADMS) in enhancing grid reliability and efficiency, assessing the role of demand response programs in balancing supply and demand, and examining the integration and management of Distributed Energy Resources (DERs) within smart grids. The research employs a quantitative methodology, collecting and analyzing data from utility companies that have implemented smart grid technologies. Key findings reveal that smart meters significantly reduce energy consumption and peak demand by providing real-time monitoring, while ADMS improves grid reliability and operational efficiency through enhanced fault detection and automated control. Demand response programs effectively balance energy supply and demand, reducing peak loads and energy costs. The integration of DERs increases renewable energy utilization and grid stability but also presents challenges related to variability in power output and management complexity. The study concludes that smart grid technologies play a crucial role in achieving a more resilient and efficient power grid, though addressing challenges related to DER integration and system management is essential for maximizing their benefits.
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Utsab, Banerjee. "The Future Direction of Smart Grid by 2050 in India." International Journal of Trend in Scientific Research and Development 4, no. 1 (2019): 141–45. https://doi.org/10.5281/zenodo.3604721.
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The present power network utilizing the technology of 1970, however are associated with increment with the advancement in various idea of intensity age, issues with the power blackouts and robbery, and furthermore due to the interest, we require a modernized matrix to fit the requirements of the clients even in the to take the circumstance in case publicity, what can be called Smart Grid . The Smart Grid performs different capacities, so it builds organize solidness, unwavering quality, proficiency and eventually decreases the conduction misfortunes. The Smart Grids are the two way preparing intensity of the shoppers who may have disseminated age. Different advancements for example, sensors and estimation, utilization of propelled segments are utilized for the effective working of the system. Stood up to in this paper, Smart Grid, its highlights, advancements in keen framework utilized, usage and difficulties of Smart Grid in India are examined. Utsab Banerjee "The Future Direction of Smart Grid by 2050 in India" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29431.pdf
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Dorji, Sonam, Albert Alexander Stonier, Geno Peter, Ramya Kuppusamy, and Yuvaraja Teekaraman. "An Extensive Critique on Smart Grid Technologies: Recent Advancements, Key Challenges, and Future Directions." Technologies 11, no. 3 (2023): 81. http://dx.doi.org/10.3390/technologies11030081.
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Given the various aspects of climate change and the growing demand for energy, energy efficiency and environmental protection have become major concerns worldwide. If not taken care of, energy demand will become unmanageable due to technological growth in cities and nations. The solution to the global energy crisis could be an advanced two-way digital power flow system that is capable of self-healing, interoperability, and predicting conditions under various uncertainties and is equipped with cyber protections against malicious attacks. The smart grid enables the integration of renewable energy sources such as solar, wind, and energy storage into the grid. Therefore, the perception of the smart grid and the weight given to it by researchers and policymakers are of utmost importance. In this paper, the studies of many researchers on smart grids are examined in detail. Based on the literature review, various principles of smart grids, the development of smart grids, functionality of smart grids, technologies of smart grids with their characteristics, communication of smart grids, problems in the implementation of smart grids, and possible future studies proposed by various researchers have been presented.
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Wisdom Samuel Udo, Jephta Mensah Kwakye, Darlington Eze Ekechukwu, and Olorunshogo Benjamin Ogundipe. "SMART GRID INNOVATION: MACHINE LEARNING FOR REAL-TIME ENERGY MANAGEMENT AND LOAD BALANCING." Engineering Science & Technology Journal 4, no. 6 (2023): 603–16. http://dx.doi.org/10.51594/estj.v4i6.1395.
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The integration of machine learning into smart grid technology represents a significant advancement in real-time energy management and load balancing. Smart grids, which enhance traditional power grids with digital communication and automation, face challenges such as fluctuating energy demands and the need for efficient load distribution. Machine learning (ML) offers transformative solutions by leveraging algorithms to analyze vast amounts of data, forecast energy consumption, and optimize load balancing. This paper explores the application of ML techniques in smart grids, focusing on load forecasting, demand response management, and energy consumption optimization. It examines how ML models, such as time series analysis and reinforcement learning, can improve the accuracy of load predictions, enable dynamic demand adjustments, and enhance overall grid stability. The integration of these technologies with existing smart grid infrastructure involves addressing challenges related to data collection, preprocessing, and computational requirements. Case studies illustrate successful implementations of ML in real-world smart grid systems, demonstrating tangible benefits such as increased efficiency and reliability. The paper also highlights future directions, including advancements in ML algorithms, the integration of renewable energy sources, and considerations for data privacy and security. Ultimately, the application of machine learning in smart grid technology promises to revolutionize energy management, making power grids more responsive, efficient, and adaptable to the evolving demands of modern energy systems. This paper provides insights into how these innovations can be harnessed to address current and future challenges in energy management. Keywords: Smart Grid, Innovation, Machine Learning, Real-Time Energy, Management, Load Balancing.
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Pasupuleti, Murali Krishna. "Advancement of Renewable Energy Integration into National Grids." International Journal of Academic and Industrial Research Innovations(IJAIRI) 05, no. 04 (2025): 259–66. https://doi.org/10.62311/nesx/rp2125.
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Abstract: The global shift towards renewable energy sources necessitates the modernization of national grids to accommodate variable and decentralized power generation. This paper explores the advancements, challenges, and strategies associated with integrating renewable energy into national grids. It examines technological innovations, policy frameworks, and case studies that highlight successful integration efforts. The study aims to provide a comprehensive understanding of the current landscape and future prospects of renewable energy integration into national power systems. Keywords: Renewable Energy Integration, National Grids, Smart Grid, Variable Renewable Energy (VRE), Grid Flexibility, Energy Storage Systems, High-Voltage Direct Current (HVDC), Advanced Metering Infrastructure (AMI), Demand Response, Distributed Energy Resources (DER), Grid Modernization, Renewable Energy Forecasting, Power System Stability, Grid Resilience, Sector Coupling, Energy Transition, Grid Infrastructure, Renewable Energy Policy, Grid Interconnection, Grid Reliability.
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Mohanty, Asit, Sthitapragyan Mohanty, Abhay Sanatan Satapathy, Manzoore Elahi M. Soudagar, Kiran Shahapurkar, and Erdem Cuce. "Empowering smart city through smart grid communication and measurement technology." International Journal of Low-Carbon Technologies 20 (2025): 404–20. https://doi.org/10.1093/ijlct/ctae224.
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Abstract In smart cities, reliable, energy-efficient power supply is crucial, highlighting the need for smart grids (SGs). Continuous advancements have enhanced grid resilience, precision, and efficiency through improved communication and collaboration between components. SGs reduce power outages, improve energy consumption control, and integrate renewable sources. Utilities benefit from lower costs and enhanced security. This paper explores the role of advanced communication techniques in SGs, focusing on how technologies like IoT sensors and smart meters enhance energy distribution, promote sustainability, and support real-time data flow for better system control in smart cities.
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Mirafzal, Behrooz, and Aswad Adib. "On Grid-Interactive Smart Inverters: Features and Advancements." IEEE Access 8 (2020): 160526–36. http://dx.doi.org/10.1109/access.2020.3020965.
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Nwankwo Charles Uzondu and Dominic Dummene Lele. "Comprehensive analysis of integrating smart grids with renewable energy sources: Technological advancements, economic impacts, and policy frameworks." Engineering Science & Technology Journal 5, no. 7 (2024): 2334–63. http://dx.doi.org/10.51594/estj.v5i7.1347.
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This study presents a comprehensive analysis of integrating smart grids with renewable energy sources, focusing on technological advancements, economic impacts, and policy frameworks. The primary objective is to explore how smart grid technologies can efficiently incorporate renewable energy sources, thereby enhancing grid reliability, efficiency, and sustainability. Utilizing a multidisciplinary approach, the study examines successful case studies, pilot projects, and innovative practices that highlight the potential and challenges of this integration. Key findings reveal that advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), and blockchain are crucial for the real-time monitoring, predictive maintenance, and optimized management of energy systems. These technologies address the inherent variability and intermittency of renewable energy sources like solar and wind power. Case studies, including the Brooklyn Microgrid and Germany’s Energiewende, demonstrate significant improvements in energy resilience, efficiency, and consumer empowerment through decentralized energy systems. Economic analysis underscores the dual impact of cost savings from operational efficiencies and the financial challenges posed by substantial upfront investments in smart grid infrastructure. Policy frameworks play a pivotal role, with recommendations for supportive regulatory policies, increased funding for research and development, and enhanced public-private partnerships to drive innovation and consumer engagement. The study concludes that overcoming the technical, economic, and regulatory barriers requires coordinated efforts among stakeholders. Recommendations include developing consistent regulatory frameworks, fostering public-private partnerships, and implementing educational programs to encourage consumer participation in renewable energy initiatives. By addressing these challenges, the integration of smart grids with renewable energy sources can pave the way for a more sustainable, resilient, and efficient energy future. Keywords: Smart Grids, Renewable Energy Integration, Technological Advancements, Economic Impacts, Policy Frameworks, Grid Management Innovations.
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Kiasari, Mahmoud, Mahdi Ghaffari, and Hamed H. Aly. "A Comprehensive Review of the Current Status of Smart Grid Technologies for Renewable Energies Integration and Future Trends: The Role of Machine Learning and Energy Storage Systems." Energies 17, no. 16 (2024): 4128. http://dx.doi.org/10.3390/en17164128.
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The integration of renewable energy sources (RES) into smart grids has been considered crucial for advancing towards a sustainable and resilient energy infrastructure. Their integration is vital for achieving energy sustainability among all clean energy sources, including wind, solar, and hydropower. This review paper provides a thoughtful analysis of the current status of the smart grid, focusing on integrating various RES, such as wind and solar, into the smart grid. This review highlights the significant role of RES in reducing greenhouse gas emissions and reducing traditional fossil fuel reliability, thereby contributing to environmental sustainability and empowering energy security. Moreover, key advancements in smart grid technologies, such as Advanced Metering Infrastructure (AMI), Distributed Control Systems (DCS), and Supervisory Control and Data Acquisition (SCADA) systems, are explored to clarify the related topics to the smart grid. The usage of various technologies enhances grid reliability, efficiency, and resilience are introduced. This paper also investigates the application of Machine Learning (ML) techniques in energy management optimization within smart grids with the usage of various optimization techniques. The findings emphasize the transformative impact of integrating RES and advanced smart grid technologies alongside the need for continued innovation and supportive policy frameworks to achieve a sustainable energy future.
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Kandasamy, Manivel, S. Anto, K. Baranitharan, Ravi Rastogi, Gunda Satwik, and A. Sampathkumar. "Smart Grid Security Based on Blockchain with Industrial Fault Detection Using Wireless Sensor Network and Deep Learning Techniques." Journal of Sensors 2023 (May 9, 2023): 1–13. http://dx.doi.org/10.1155/2023/3806121.
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Low-cost monitoring and automation solutions for smart grids have been made viable by recent advancements in embedded systems and wireless sensor networks (W.S.N.s). A well-designed smart network of subsystems and metasystems known as a “smart grid” is aimed at enhancing the conventional power grid’s efficiency and guaranteeing dependable energy delivery. A smart grid (S.G.) requires two-way communication between utility providers and end users in order to accomplish its aims. This research proposes a novel technique in enhancing the smart grid security and industry fault detection using a wireless sensor network with deep learning architectures. The smart grid network security has been enhanced using a blockchain-based smart grid node routing protocol with IoT module. The industrial analysis has been carried out based on monitoring for fault detection in a network using Q-learning-based transfer convolutional network. The experimental analysis has been carried out in terms of bit error rate, end-end delay, throughput rate, spectral efficiency, accuracy, M.A.P., and RMSE. The proposed technique attained bit error rate of 65%, end-end delay of 57%, throughput rate of 97%, spectral efficiency of 93%, accuracy of 95%, M.A.P. of 55%, and RMSE of 75%. This proposed paradigm is advantageous for the operation of smart grids for increased security and industrial fault detection across the network because security is the biggest barrier in smart grid implementation.
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Avwioroko, Afor, Chinedu Ibegbulam, Israel Afriyie, and Aminat Temitope Fesomade. "Smart Grid Integration of Solar and Biomass Energy Sources." European Journal of Computer Science and Information Technology 12, no. 3 (2024): 1–14. http://dx.doi.org/10.37745/ejcsit.2013/vol12n3114.
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The integration of solar and biomass energy sources into smart grids marks a significant step toward a sustainable and efficient energy future. Smart grids, which can dynamically manage and distribute energy, are essential for incorporating renewable energy sources that are naturally variable and decentralized. This paper details the strategies and technologies necessary for the smooth integration of solar and biomass energy into smart grids. Solar energy, with its intermittent nature, presents unique challenges for grid stability and reliability. Advanced technologies such as solar panels, energy storage systems, and real-time monitoring solutions are crucial for optimizing solar energy integration. Similarly, biomass energy, derived from organic materials, provides a reliable and dispatchable power source but requires advanced conversion and distribution mechanisms for effective integration into the smart grid. The smart grid itself, equipped with demand response systems, advanced metering infrastructure, and grid balancing tools, is vital for managing variability and ensuring energy supply stability. This paper also examines several case studies of successful solar and biomass energy integration, highlighting technological innovations and strategic planning. Despite promising advancements, challenges remain, including regulatory barriers, technological limitations, and the need for significant investment. This paper discusses these challenges and explores future research and development directions to improve the scalability and efficiency of smart grid systems. In conclusion, integrating solar and biomass energy into smart grids not only supports a sustainable energy landscape but also enhances grid reliability and efficiency. Ongoing innovation and strategic policy-making are essential to fully realize the potential of smart grids in the renewable energy sector.
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Researcher. "ENERGY-EFFICIENT CONTROL STRATEGY DEVELOPMENT FOR SMART GRIDS INTEGRATING DISTRIBUTED RENEWABLE ENERGY RESOURCES WITH REAL-TIME DEMAND RESPONSE OPTIMIZATION." International Journal of Control Systems Engineering (IJoCSE) 3, no. 1 (2025): 1–6. https://doi.org/10.5281/zenodo.14715816.
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This paper explores an energy-efficient control strategy for smart grids by integrating distributed renewable energy resources (DRER) with real-time demand response optimization (DR). We propose a dynamic framework that balances energy supply and demand while ensuring grid stability and reducing costs. This study identifies the latest advancements in DRER, assesses existing literature, and incorporates optimization algorithms to enhance energy efficiency and sustainability. The findings underscore the importance of intelligent energy management and its potential in advancing future smart grid operations.
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Pankaj, Sharma, Reddy Salkuti Surender, and Kim Seong-Cheol. "Advancements in energy storage technologies for smart grid development." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 4 (2022): 3421–29. https://doi.org/10.11591/ijece.v12i4.pp3421-3429.
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In the modern world, the consumption of oil, coal natural gas, and nuclear energy has been causing by a serious environmental problem and an ongoing energy crisis. The generation and consumption of renewable energy sources (RESs) such as solar and wind tidal, can resolve the problem but the nature of the RESs is fluctuating and intermitted. This evolution brings a lot of challenges in the management of electrical grids. The paper reviewed the advancements in energy storage technologies for the development of a smart grid (SG). More attention was paid to the classification of energy storage technologies based on the form of energy storage and based on the form of discharge duration. The evaluation criteria for the energy storage technologies have been carried out based on technological dimensions such as storage capacity, efficiency, response time, energy density, and power density, the economic dimension such as input cost and economic benefit; and the environmental dimension such as emission and stress on ecosystem, social demission such as job creation and social acceptance were also presented in this paper.
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Singh, Bikram, Harkamaldeep Singh, and Santosh Kumar. "OVERVIEW ON IMPLEMENTATION OF SMART GRID TECHNOLOGY." Journal of Engineering, Management and Information Technology 2, no. 4 (2024): 185–94. http://dx.doi.org/10.61552/jemit.2024.04.003.
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The Elevated energy consumption and a growing need for power in commercial, residential, and industrial settings have drawn researchers to explore novel solutions for the grid of the future. This review provides an overview on smart grid technology and its historical development from its conceptual beginnings to its today real-world implementation (intelligent networks). The review then analyzes the multifaceted impacts of smart grids such as social impact, user impact, security impact and environmental impacts. We also delve into their positive performance metrics, including enhanced reliability, efficiency, and resilience, with specific examples of improved power quality and increased renewable energy integration. Finally, the various challenges and opportunities that smart grids offer. We explore cutting-edge advancements like artificial intelligence, edge computing, & blockchain technology, showcasing their potential to overcome existing barriers and pave the way for a new era of intelligent energy management.
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Ahmad, Farhan. "Big Data Analytics in Smart Power Systems: A Survey Paper." UMT Artificial Intelligence Review 1, no. 2 (2021): 12–26. http://dx.doi.org/10.32350/air.0102.02.
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In recent years, technology has brought us many advancements. One of them is integrating big data with smart grid/smart power. In this study, a scientific approach used to help the power system is studied. Additionally, with the help of previously published literature, different survey papers are reviewed to investigate the key challenges of integrating Big Data Analytics (BDA) with smart grid. Subsequently, BDA characteristics are also studied. Next, data analysis techniques and BDA applications in the domain of smart grids are studied. It is followed by a section discussing techniques such as Hadoop and Spark. Their framework is also briefly examined in order to know about their working. The last section provides a conclusion and future directions.
 KEYWORDS: advanced metering infrastructure (AMI), applications of big data, big data analytics (BDA), data architectures, data mining, data privacy, data security, data uncertainty, data volume, hadoop, spark, Vz of the data, smart grid, smart power system big
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Deevanshu Shrivastava. "Untangling the Knot of Intellectual Property in Power Engineering: Powering Up Innovation in India." Power System Technology 48, no. 1 (2024): 973–79. https://doi.org/10.52783/pst.356.
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Power engineering technology is a field focused on the practical application of scientific and engineering principles to create, transmit, and utilize electrical power in a safe, reliable, and efficient manner. It encompasses a wide range of areas, including the design, operation, and maintenance of power plants, transmission and distribution grids, and renewable energy systems. Power engineering technicians play a vital role in ensuring the smooth functioning of this complex infrastructure. They work with various equipment, from high-pressure boilers and turbines in power plants to transformers and control systems in electricity grids. Their responsibilities include monitoring system performance, troubleshooting technical issues, implementing maintenance procedures, and adhering to safety regulations. The field is constantly evolving with advancements in renewable energy integration, smart grid technologies, and energy storage solutions. Effective management of intellectual property rights is crucial in this sector to foster innovation and protect these advancements, ultimately contributing to a sustainable and efficient future of power generation and distribution. The power sector is undergoing a rapid transformation, driven by advancements in renewable energy sources, smart grid technologies, and energy storage solutions. These innovations hold immense potential for a more sustainable and efficient energy future. However, intellectual property rights (IPR) play a critical role in fostering innovation and ensuring fair returns for inventors and developers. This research paper analyses the key IPR issues specific to power engineering technology, explores their impact on technological advancement, and proposes potential solutions for a more balanced and effective IPR landscape.
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Nitin, Shejwal, Bibave Rahul, and D. B. Pardeshi Dr. "Advanced Data Analytics and Machine Learning Applications in Smart Grids: A Comprehensive Review." Journal of Research and Advancement in Electrical Engineering 7, no. 1 (2024): 25–33. https://doi.org/10.5281/zenodo.10623383.
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<em>This paper consist a comprehensive review study on Advanced Data Analytics and Machine Learning Applications system technology used for systematic computations analyses of data generated in grids, helps in better interpretation. This also helps in making precise communication, identification of data trends which develops meaningful patterns which comes in. An Internet of Things (IoT) Base is mainly used in Smart Grid which provides better connectivity and constant communication. Use of (IoT) provides protection to the grid in the form of Cybersecurity. Machine Learning Algorithms helps in increasing efficiency of grid, energy wastage is reduced due to which reliability increases. This will reduce cost of energy which will be profitable for both (consumers and providers). As day-by-day advancements are been made in the field of grid connections networks, which increases reliability and efficiency which will result in guarantee of stable power supply.</em>
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Basharat, Arooj, and Zilly Huma. "Enhancing Resilience: Smart Grid Cybersecurity and Fault Diagnosis Strategies." Asian Journal of Research in Computer Science 17, no. 6 (2024): 1–12. http://dx.doi.org/10.9734/ajrcos/2024/v17i6453.
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The increasing integration of advanced technologies within the power grid infrastructure has led to significant advancements in efficiency, reliability, and sustainability. However, this integration also introduces new vulnerabilities, particularly in the realm of cybersecurity. This paper presents an overview of smart grid cybersecurity challenges and proposes strategies for enhancing resilience through fault diagnosis techniques. Firstly, the paper examines the evolving threat landscape facing smart grids, encompassing cyber-attacks, insider threats, and natural disasters. It highlights the critical need for robust cybersecurity measures to safeguard grid operations and prevent potentially catastrophic disruptions. Next, the paper delves into various cybersecurity frameworks and standards tailored specifically for smart grids, emphasizing the importance of comprehensive risk assessment, intrusion detection systems, and secure communication protocols. Additionally, it discusses the role of machine learning and artificial intelligence in augmenting cyber defense capabilities, enabling proactive threat detection and rapid response. Furthermore, the paper explores fault diagnosis strategies aimed at maintaining grid resilience in the face of cyber incidents or physical faults. It discusses the integration of data analytics, predictive modeling, and real-time monitoring to identify and mitigate potential grid disturbances swiftly.
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Notis, Mengidis, Tsikrika Theodora, Vrochidis Stefanos, and Kompatsiaris Ioannis. "Blockchain and AI for the Next Generation Energy Grids: Cybersecurity Challenges and Opportunities." Information & Security: An International Journal 43, no. 1 (2019): 21–33. https://doi.org/10.11610/isij.4302.
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Renewable energy sources and the increasing interest in green energy has been the driving force behind many innovations in the energy sector, such as how utility companies interact with their customers and vice versa. The introduction of smart grids is one of these innovations in what is basically a fusion between the traditional energy grid with the IT sector. Even though this new combination brings a plethora of advantages, it also comes with an increase of the attack surface of the energy grid, which becomes susceptible to cyberattacks. In this work, we analyse the emerging cybersecurity challenges and how these could be alleviated by the advancements in AI and blockchain technologies.
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Vinayak, Deshmukh. "Advancements in Renewable Energy Storage and Smart Grids for a Sustainable Future." International Journal of Advance and Applied Research S6, no. 18 (2025): 761–66. https://doi.org/10.5281/zenodo.15266494.
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<em>This paper explores recent advancements in renewable energy storage and smart grid technologies, which are essential for a sustainable energy future. It covers a range of energy storage solutions, including lithium-ion batteries, pumped hydro, and emerging technologies like hydrogen storage, highlighting their role in addressing the intermittency of renewable energy sources. The paper also delves into smart grid innovations, emphasizing their ability to improve grid efficiency, integrate renewable energy, and enhance reliability through real-time data and automation. By examining current trends, challenges, and case studies, the paper outlines how these technologies can drive the transition to a cleaner, more resilient energy system.</em>
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Purna Prakash, Kasaraneni, Yellapragada Venkata Pavan Kumar, Kasaraneni Himajyothi, and Gogulamudi Pradeep Reddy. "Comprehensive Bibliometric Analysis on Smart Grids: Key Concepts and Research Trends." Electricity 5, no. 1 (2024): 75–92. http://dx.doi.org/10.3390/electricity5010005.
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Over the years, a rapid evolution of smart grids has been witnessed across the world due to their intelligent operations and control, smart characteristics, and benefits, which can overcome several difficulties of traditional electric grids. However, due to multifaceted technological advancements, the development of smart grids is evolving day by day. Thus, smart grid researchers need to understand and adapt to new concepts and research trends. Understanding these new trends in smart grids is essential for several reasons, as the energy sector undergoes a major transformation towards becoming energy efficient and resilient. Moreover, it is imperative to realize the complete potential of modernizing the energy infrastructure. In this regard, this paper presents a comprehensive bibliometric analysis of smart grid concepts and research trends. In the initial search, the bibliometric data extracted from the Scopus and Web of Science databases totaled 11,600 and 2846 records, respectively. After thorough scrutiny, 2529 unique records were considered for the bibliometric analysis. Bibliometric analysis is a systematic method used to analyze and evaluate the scholarly literature on a particular topic and provides valuable insights to researchers. The proposed analysis provides key information on emerging research areas, high-impact sources, authors and their collaboration, affiliations, annual production of various countries and their collaboration in smart grids, and topic-wise title count. The information extracted from this bibliometric analysis will help researchers and other stakeholders to thoroughly understand the above-mentioned aspects related to smart grids. This analysis was carried out on smart grid literature by using the bibliometric package in R.
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Chaudhary, Ninad A. "Smart Grid Technology : Simplifying the Complexities of Modern Energy Management." International Scientific Journal of Engineering and Management 03, no. 04 (2024): 1–9. http://dx.doi.org/10.55041/isjem01619.
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This paper explores the transformative role of smart grid technology in simplifying contemporary energy management complexities. By integrating advanced communication and automation, smart grids enhance efficiency, reliability, and sustainability in power distribution, paving the way for a more resilient and responsive energy infrastructure Through the integration of cutting-edge communication and automation, smart grids not only bolster efficiency but also elevate the reliability and sustainability of power distribution. This research sheds light on the potential of smart grids to create a more resilient and responsive energy infrastructure, addressing the challenges of our rapidly evolving energy landscape. The exploration extends beyond the surface benefits, delving into the nuanced ways in which smart grids empower energy systems to adapt and evolve. This adaptive prowess not only simplifies the complexities of energy management but also fosters a more resilient and responsive energy infrastructure. The intricate interplay of technological advancements within smart grids forms the bedrock for a paradigm shift in how we conceptualize, distribute, and consume energy resources. As the world grapples with the pressing need for sustainable energy solutions, this research sheds light on the multifaceted contributions of smart grid technology. By paving the way for a harmonized and dynamic energy ecosystem, smart grids stand poised to redefine the future of energy management, offering a promising path towards a more sustainable and resilient global energy landscape. Keywords-Advanced Metering Infrastructure (AMI), Distributed Energy Resources (DERs)
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Shohel, Mohammad Shoriful Hossan, Muhammad Mohiul Islam, Ripan Kumar Prodhan, and ASM Morshed. "Lifecycle Management Of Renewable Energy Systems In Residential Housing Construction." Innovatech Engineering Journal 1, no. 01 (2024): 124–38. https://doi.org/10.70937/faet.v1i01.23.
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This study investigates the transformative role of smart grids in integrating renewable energy systems into residential and industrial power networks, emphasizing their potential to enhance energy efficiency, improve grid stability, and address the challenges posed by renewable energy variability. By adopting the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the study ensures a systematic and transparent approach to the review process. A total of 42 peer-reviewed articles were analyzed, providing comprehensive insights into the technological advancements, challenges, and future prospects of smart grid systems. Key findings reveal that smart grids significantly improve energy efficiency by 20–25%, primarily through the use of real-time monitoring, AI-driven optimization, and advanced energy storage solutions. The review also highlights critical challenges such as high implementation costs, cybersecurity risks, and interoperability issues, which require collaborative efforts among stakeholders to overcome. Additionally, the study underscores the role of microgrids as decentralized extensions of smart grids, offering scalable and resilient solutions for integrating distributed renewable energy sources. This comprehensive review not only validates the importance of smart grids in achieving sustainable energy goals but also provides actionable insights for policymakers, engineers, and researchers aiming to optimize renewable energy integration.
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Dhantiya, Javed A., Amin S. Kharadi, and Anas I. Shikari. "AUTONOMOUS DISTRIBUTED SYSTEMS FOR SMART GRIDS: A CURRENT PERSPECTIVE." COMPUSOFT: An International Journal of Advanced Computer Technology 11 (July 26, 2022): 3998–4000. https://doi.org/10.5281/zenodo.15087275.
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The increasing complexity of power distribution networks, combined with the rise of renewable energy sources, has spurred the development of autonomous distributed systems for smart grids. These systems leverage advanced algorithms and distributed computing to optimize energy distribution, enhance grid stability, and reduce operational costs. This paper explores recent advancements in autonomous distributed systems for smart grids, focusing on the integration of machine learning, multiagent systems, and blockchain technology. We evaluate the effectiveness of these technologies through simulations and discuss future directions for research in this domain.
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A.SHAJI, GEORGE. "SURVEY ON ADVANCED DATA COMMUNICATION." Journal of Interdisciplinary Cycle Research (JICR) VII, no. II (2015): 11–20. https://doi.org/10.5281/zenodo.7215953.
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Brilliant Grid is intended to incorporate progressed correspondence/organizing innovations into electrical power frameworks to make them ''more intelligent''. Current circumstance is that a large portion of the power outages and voltage lists could be forestalled in the event that we have better and quicker specialized gadgets and advancements for the electrical matrix. To make the flow electrical force lattice a Smart Grid, the plan and execution of another correspondence framework for the lattice are two significant fields of examination. Be that as it may, Brilliant Grid projects have just been proposed as of late and a couple of recommendations for forward looking necessities and starting exploration work have been offered in this field. No any efficient audits of correspondence/organizing in Smart Grids have been led at this point. In this manner, we direct an orderly survey of correspondence/organizing innovations in Smart Grid in this paper, including correspondence/organizing engineering, distinctive correspondence innovations that would be utilized into this design, nature of administration (QoS), upgrading use of resources, control and the board, and so forth.
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Vodapally, Sai Nikhil, and Mohd Hasan Ali. "Overview of Intelligent Inverters and Associated Cybersecurity Issues for a Grid-Connected Solar Photovoltaic System." Energies 16, no. 16 (2023): 5904. http://dx.doi.org/10.3390/en16165904.
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The major problem associated with the grid-connected solar photovoltaic (PV) system is the integration of the generated DC power into the AC grid and maintaining the stability of the system. With advancements in research on these PV inverters, artificial intelligence (AI)-based control models are replacing the existing linear methods. These smart PV systems are prone to a variety of attacks, ranging from physical attacks on the PV plants to data integrity attacks and communication-based attacks. This paper provides an overview of the cybersecurity issues with smart PV inverters, their impacts on the grids, and control methods that exist to detect and identify cyber-attacks on a smart PV grid system. An extensive bibliography is provided on grid-forming and grid-following inverters with a variety of control techniques like Proportional–Integral–Derivative (PID) control, fuzzy-based control, and their performances under different fault situations. Multi-level inverter design approaches with various intelligent control techniques to overcome switching failures and other system faults are reviewed. Moreover, some recommendations for future research on intelligent inverters for grid-connected PV systems are proposed. This work will benefit researchers, scientists, and engineers who are working in the field of intelligent inverters for the grid-connected PV system.
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Adeyemi Zaheed Oshilalu, Michael Ibukun Kolawole, and Onaopemipo Taiwo. "Innovative solar energy integration for efficient grid electricity management and advanced electronics applications." International Journal of Science and Research Archive 13, no. 2 (2024): 2931–50. https://doi.org/10.30574/ijsra.2024.13.2.2513.
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The integration of smart electronics into solar-powered grid systems has revolutionized renewable energy by enhancing efficiency, reliability, and scalability. As the global demand for sustainable energy solutions grows, the deployment of smart devices, including inverters, controllers, and sensors, in solar grid systems has become pivotal in addressing challenges such as energy intermittency and system optimization. Smart electronics enable real-time monitoring, predictive maintenance, and intelligent energy management, ensuring efficient energy distribution and reduced operational costs. By leveraging advanced technologies like machine learning and Internet of Things (IoT), these systems dynamically adapt to fluctuating energy demands and environmental conditions, improving overall grid stability. This study explores the critical role of smart electronics in transforming solar-powered grid systems into resilient and adaptive energy networks. The research delves into key technologies, including Maximum Power Point Tracking (MPPT) for optimizing solar energy capture and smart controllers for load balancing and fault detection. Furthermore, the study highlights the importance of integrating energy storage solutions, such as lithium-ion batteries, with smart grid systems to mitigate the effects of energy intermittency. Despite significant advancements, the implementation of smart electronics in solar grids faces challenges such as high initial costs, cybersecurity risks, and the need for standardized frameworks to ensure interoperability. This study proposes strategies to overcome these obstacles, emphasizing collaborative efforts between governments, industries, and researchers to drive innovation. By optimizing renewable energy systems with smart electronics, the transition to sustainable, reliable, and efficient energy networks becomes a practical and achievable goal for addressing global energy demands.
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Afor Avwioroko. "THE INTEGRATION OF SMART GRID TECHNOLOGY WITH CARBON CREDIT TRADING SYSTEMS: BENEFITS, CHALLENGES, AND FUTURE DIRECTIONS." Engineering Science & Technology Journal 4, no. 2 (2023): 33–45. http://dx.doi.org/10.51594/estj.v4i2.1287.
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The integration of smart grid technology with carbon credit trading systems offers a promising path to improve the grid efficiency and stability and reduce greenhouse gas emissions. This paper examines the possible interoperability of smart grid technology and carbon credit trading systems. Smart grid technology, characterized by its advanced monitoring, control, and optimization capabilities, offers the foundation for real-time data collection and analysis. On the other hand, carbon credit trading systems create financial incentives for reducing emissions. By combining these two systems, Nigeria can improve grid stability and increase the adoption of renewable energy sources, accelerating the transition to cleaner energy. Additionally, this paper discusses challenges that could hamper the successful integration of smart grid and carbon credit systems such as data security, regulatory compliance, and technological infrastructure requirements. Using case studies and examples, this paper examines the successful implementation of an integrated smart grid and carbon credit trading system, sharing valuable lessons learned and best practices. The paper also highlights the potential for advancements in technology and policy frameworks to promote wider adoption of these integrated systems.. Keywords: Integration, Smart Grid Technology, Carbon, Credit, Trading Systems.
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G, DEEPU, and HARSHITHA M. "CYBER RESILIENCE USING SMART GRID." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 01 (2024): 1–13. http://dx.doi.org/10.55041/ijsrem28312.
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With the integration of sophisticated automation, control, and communication capabilities into conventional power systems, the smart grid has developed into a game-changing technological advancement. But greater connectivity also poses serious problems for data security. This article discusses the hazards and vulnerabilities posed by cyberattacks and offers a thorough examination of data security in smart grids. In order to guarantee the availability, integrity, and confidentiality of data within the smart grid architecture, it looks at a number of data security solutions, including intrusion detection, authentication, and encryption. Future developments and cutting-edge technologies that can strengthen data security resilience within the smart grid ecosystem are also covered. Index Terms – Security, Encryption, Smart Grid, Digital signature, Blockchain technology, Quantum cryptography
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Ali, Md Shopan, Anik Sharma, Tamal Ahammed Joy, and Md Abdul Halim. "A Comprehensive Review of Integrated Energy Management for Future Smart Energy System." Control Systems and Optimization Letters 2, no. 1 (2024): 43–51. http://dx.doi.org/10.59247/csol.v2i1.77.
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The main objective of this paper is to review the integration of energy management for future smart energy systems. The authors hope to address the developing landscape of energy management in the context of new smart energy systems in this review. The paper conducts a thorough review of integrated energy management methodologies that maximize energy generation, consumption, and distribution within these systems. The study assesses the multifarious solutions that enable effective and sustainable energy consumption by considering many components such as renewable energy sources, storage technologies, demand-side management, and grid interactions. The authors present insights into the problems and opportunities inherent in realizing the potential of future smart energy systems through an in-depth assessment of recent research, case studies, and advances in energy management. The assessment focuses on the inherent problems and opportunities associated with pursuing integrated energy management in smart energy systems. The application of cutting-edge sensing, communication, and control technologies to electrical grids has been studied to increase resilience, efficiency, and dependability. Real-time monitoring, analysis, and optimization of energy flows are made possible by the integration of cutting-edge sensors, communication systems, and control algorithms into electrical grids. Variable renewable energy sources, such solar PV and wind power, may now be seamlessly integrated into the grid thanks to advancements in renewable energy integration technologies. Case studies have shown how smart grid technologies can optimize energy management and save system costs. Integrating various DERs into grid operations has been the main focus of advancements in energy management. The paper navigates through the intricate considerations that stakeholders must make to maintain the resilience and sustainability of future energy systems, from dealing with the intermittent nature of renewable sources to maximizing energy dispatch mechanisms. The study reveals the revolutionary potential of a holistic approach to energy management by studying the changing role of digital technologies, data analytics, and predictive algorithms. Finally, this review contributes to a better knowledge of integrated energy management techniques, opening the path for a more robust, responsive, and environmentally friendly energy landscape.
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Ojo, Oluwafemi Tayo, Temitope James Dada, Yusuff Afees Ademola, et al. "Smart Grids And IOT-Enabled Renewable Energy Integration." Path of Science 11, no. 1 (2025): 8012. https://doi.org/10.22178/pos.113-28.
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Over the past decades, the power system has undergone significant transformations. However, it faces multiple challenges, including rising electricity demand, power losses, grid failures, and a lack of innovative technology. Additionally, security threats to the grid have escalated. The existing power grid cannot effectively address these issues. The rapid advancement of the Internet of Things (IoT) has introduced innovative solutions, making it a promising technology for modernising power grids. Integrating IoT into the grid can enhance efficiency, capacity, reliability, sustainability, scalability, and stability. IoT-based smart grids offer solutions to many of the limitations of traditional grid systems. However, recent studies on IoT-enabled smart grids highlight security vulnerabilities as a critical concern. This paper explores various security challenges and frameworks associated with IoT-integrated smart grids. It also examines IoT and non-IoT technologies essential to intelligent grid networks, including sensing, communication, and computing technologies, along with relevant standards.
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Ojadi, Jessica Obianuju, Chinekwu Somtochukwu Odionu, Ekene Cynthia Onukwulu, and Olumide Akindele Owulade. "AI-Enabled Smart Grid Systems for Energy Efficiency and Carbon Footprint Reduction in Urban Energy Networks." International Journal of Multidisciplinary Research and Growth Evaluation. 5, no. 1 (2024): 1549–66. https://doi.org/10.54660/.ijmrge.2024.5.1.1549-1566.
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The increasing energy demand in urban areas necessitates the development of efficient and sustainable power distribution systems. AI-enabled smart grid systems have emerged as transformative solutions for optimizing energy efficiency, enhancing grid reliability, and reducing carbon footprints in urban energy networks. This paper explores the integration of artificial intelligence (AI) with smart grid technologies to improve energy distribution, demand-side management, and real-time decision-making. AI-driven techniques, such as machine learning (ML) algorithms, deep learning models, and predictive analytics, play a crucial role in forecasting energy consumption patterns, optimizing load balancing, and detecting faults. These intelligent systems enhance grid stability by enabling automated demand response, improving the integration of renewable energy sources, and facilitating real-time monitoring of power flow. Smart grids embedded with AI technologies leverage real-time data analytics to enable energy forecasting and adaptive load management, which minimizes energy wastage and enhances grid efficiency. AI-based optimization techniques help utilities manage peak load conditions effectively, reducing reliance on fossil fuel-based power plants and lowering greenhouse gas emissions. Additionally, AI-powered anomaly detection and predictive maintenance improve system resilience by identifying faults and preventing failures before they escalate. The deployment of AI-driven energy management systems in urban grids enables decentralized energy distribution and fosters the adoption of distributed energy resources, including solar and wind power. Despite the advantages of AI-enabled smart grids, challenges such as cybersecurity risks, data privacy concerns, and integration complexities remain critical barriers to widespread implementation. The need for robust regulatory frameworks, secure data management strategies, and interdisciplinary collaborations among policymakers, energy providers, and AI researchers is imperative for the successful adoption of AI-driven smart grid systems. Future advancements in AI, including federated learning, edge computing, and blockchain-based energy trading, can further enhance the efficiency and security of urban energy networks. This study highlights the potential of AI-enabled smart grids in revolutionizing urban energy systems by improving energy efficiency, reducing carbon footprints, and ensuring sustainable power management. The findings provide valuable insights into the role of AI in shaping next-generation smart grids, fostering a cleaner, more efficient, and resilient energy infrastructure.
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Agnew, Dennis, Sharon Boamah, Arturo Bretas, and Janise McNair. "Network Security Challenges and Countermeasures for Software-Defined Smart Grids: A Survey." Smart Cities 7, no. 4 (2024): 2131–81. http://dx.doi.org/10.3390/smartcities7040085.
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The rise of grid modernization has been prompted by the escalating demand for power, the deteriorating state of infrastructure, and the growing concern regarding the reliability of electric utilities. The smart grid encompasses recent advancements in electronics, technology, telecommunications, and computer capabilities. Smart grid telecommunication frameworks provide bidirectional communication to facilitate grid operations. Software-defined networking (SDN) is a proposed approach for monitoring and regulating telecommunication networks, which allows for enhanced visibility, control, and security in smart grid systems. Nevertheless, the integration of telecommunications infrastructure exposes smart grid networks to potential cyberattacks. Unauthorized individuals may exploit unauthorized access to intercept communications, introduce fabricated data into system measurements, overwhelm communication channels with false data packets, or attack centralized controllers to disable network control. An ongoing, thorough examination of cyber attacks and protection strategies for smart grid networks is essential due to the ever-changing nature of these threats. Previous surveys on smart grid security lack modern methodologies and, to the best of our knowledge, most, if not all, focus on only one sort of attack or protection. This survey examines the most recent security techniques, simultaneous multi-pronged cyber attacks, and defense utilities in order to address the challenges of future SDN smart grid research. The objective is to identify future research requirements, describe the existing security challenges, and highlight emerging threats and their potential impact on the deployment of software-defined smart grid (SD-SG).
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Rahul Kumar Jha. "Cybersecurity and Confidentiality in Smart Grid for Enhancing Sustainability and Reliability." December 2023 2, no. 2 (2023): 215–41. http://dx.doi.org/10.36548/rrrj.2023.2.001.
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Ensuring cybersecurity and confidentiality in smart grids is crucial for enhancing sustainability and reliability in today's technology-driven world. With the increasing reliance on smart grid technologies, it is imperative to address the potential cybersecurity risks and protect the confidentiality of sensitive data. This research focuses on exploring the challenges and strategies associated with cybersecurity and confidentiality in smart grids. It examines the importance of safeguarding smart grid infrastructure from cyber threats to maintain sustainable and reliable energy delivery systems. The study investigates various techniques and technologies, including encryption, authentication, intrusion detection, and secure communication protocols, that can be employed to enhance the cybersecurity and confidentiality of smart grids. By highlighting the significance of a robust cybersecurity framework and the integration of privacy-preserving measures, this research aims to contribute to the development of secure and resilient smart grid systems. The findings and recommendations presented in this work provide valuable insights for policymakers, industry professionals, and researchers involved in the design and implementation of secure smart grid solutions, ultimately leading to the advancement of sustainable and reliable energy infrastructures.
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Talwariya, Akash, Santosh Kumar Sharma, Pushpendra Singh, and Mohan Kolhe. "SMART GRID DEVELOPMENT IN INDIA WITH CHALLENGES AND OPPORTUNITIES: EXECUTION WITH GAME THEORY." International Journal of Technical Research & Science 3, no. 04 (2018): 122–28. http://dx.doi.org/10.30780/ijtrs.v3.i3.2018.019.
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Advancement in energy technologies are much needed for social and economical enlargement of our society. The weakest electric grid in the world in India lost 26% of total power generation as transmission and distribution losses. The sustainable energy resources and development of efficient modules are highly required in present power system. Existing power system is designed as a one way supply system from source to utility. The objective of this paper is to study the problems of conventional power grids in India, and optimize the problems through smart grid to enhance the bidirectional flow of power in distribution network. The increasing embodiment of renewable energy sources and variable energy consumption patterns make the smart grid complex. Smart grid (SG) components such as smart meters, virtual power system and microgrid are discussed with challenges in adoption of smart grid. Renewable energy sources provides a solution against the emission of CO2 from conventional power system by the establishment of smart grid. Game theory approach has been proposed in smart grid to conflicting the grid secure in global environment and reduces the dependency of consumers on fossil fuel sources. This paper discusses the overview of game theory, Cooperative and noncooperative game theory.
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Archana. "Exploring the Acceptance of Smart Grid Technology in India." International Journal of Electronic Government Research 18, no. 1 (2022): 1–30. http://dx.doi.org/10.4018/ijegr.314219.
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In the last few decades, technological advancements in the power sector have accelerated the evolution of the smart grid to make the grid more efficient, reliable, and secure. Being a consumer-centric technology, a lack of knowledge and awareness in consumers may lead to consumer opposition, which could imperil the grid modification process. This research aims to identify and prioritize the factors that can be considered barriers to technology acceptance for smart grid development in India. This study follows an integrated approach of literature review, AHP, and FERA. In the present work, 17 barriers have been identified and ranked on the basis of the social, technical, and economic paradigm. This study finds the impact of government policies and stakeholders' involvement in consumers' acceptance of smart grid technology and its importance towards improving the quality of life of Indians. The government should play as the main proponent. The present work will contribute to developing and upgrading the basic framework for the smart grid in a developing country like India.
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Daniel, S. Arul, Ramakrishna Kappagantu, and N. S. Suresh. "Techno-economic analysis of Smart Grid pilot project- Puducherry." Resource-Efficient Technologies, no. 4 (December 2, 2016): 185–98. http://dx.doi.org/10.18799/24056529/2016/4/64.
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Smart Grid (SG) a well-known concept being rapidly introduced in the power industry. New transformation of Indian power network has begun with 14 SG pilot projects across the nation. One of such projects has been successfully commissioned in Puducherry. The motive of this research work is to analyze the techno-economic aspects of a smart distribution network before being implemented nation-wide the study case facilitatingefficient planning and deployment of technology. This paper presents techno-economic analysis of Smart Grid via a case study of Puducherry pilot project. Covered in this paper are different components of investment which convey an idea about services and their proposition as well as technical advancements with their benefits. This paper discusses the gain in terms of energy and money saving through different smart technical tools. Payback analysis explains how investment in smart distribution network is justified.
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Mahmood, Bushra, Ahmed Ghanim Wadday, and Ahmed Kareem Abdullah. "Innovative Smart Inverter Design for Enhanced Integration of DistributedEnergy." Al-Furat Journal of Innovations in Electronics and Computer Engineering 3, no. 2 (2024): 216–50. http://dx.doi.org/10.46649/fjiece.v3.2.16a.25.5.2024.
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This comprehensive exploration delves into the innovative field of smart inverter design, with a particular focus on the role of artificial intelligence (AI) in enhancing the integration of Distributed Energy Resources (DERs) into power grids. The rapid evolution of energy systems and the increasing reliance on renewable energy sources have necessitated the development of more sophisticated technologies for power system management. Smart inverters, at the heart of this transformation, are crucial for integrating DERs like solar panels and wind turbines into existing power grids. The integration of AI into smart inverters represents a significant advancement in managing and optimizing these complex systems. This study demonstrates how these advanced technologies can lead to substantial improvements in inverter reliability, power distribution efficiency, and overall management of renewable energy sources. Realistic models highlight the resilience of smart inverters to fluctuating grid conditions and their ability to maintain system reliability and efficiency. Furthermore, the study critically assesses the current challenges facing this field, such as the need for standardized communication protocols, robust cybersecurity measures against digital threats, and the ongoing requirement for innovation to keep pace with rapid technological advancements. Finally, the exploration forecasts future developments and areas that will further enhance smart inverter technology, emphasizing the essential role of continued research and development in fully realizing AI's potential to transform power grids. The examination concludes by highlighting the promising future of AI in smart inverter design, particularly in contributing to the development of more efficient, reliable, and sustainable energy systems.
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ERÇİK, Hüseyin, and Mahmut DİRİK. "Data Analysis for Smart Grid and Communication Technologies." International Conference on Scientific and Innovative Studies 1, no. 1 (2023): 331–42. http://dx.doi.org/10.59287/icsis.621.
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Smart grids and communication technologies are among the significant advancements in theenergy sector. These technologies improve energy efficiency by increasing the use of renewable energysources. However, the integration of these technologies also creates a vast amount of data that requiresanalysis to optimize energy management and improve system performance. In this context, data analysisplays a crucial role in identifying patterns, predicting energy demand, and managing energy supply. Thispaper provides an overview of the importance of data analysis in smart grids and communicationtechnologies and discusses various data analysis techniques used in energy management systems.Additionally, it highlights the challenges and opportunities associated with data analysis in the context ofsmart grids and communication technologies.
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Ifeanyi Kingsley Egbuna, Faisal Benna Salihu, Chinemeremma Collins Okara, et al. "Advances in AI-powered energy management systems for renewable-integrated smart grids." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 2300–2325. https://doi.org/10.30574/wjaets.2025.15.2.0685.
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The accelerating global shift toward renewable energy integration presents both a technical imperative and a systemic challenge to traditional power grid architectures. Variability, decentralization, and real-time balancing requirements have exposed the limitations of conventional control and forecasting strategies. This review critically examines how artificial intelligence (AI) is redefining energy management systems to meet the operational and strategic needs of renewable-integrated smart grids. It explores the state-of-the-art in AI-based load and generation forecasting, real-time grid state estimation, anomaly detection, and predictive maintenance, highlighting how machine learning and deep learning techniques enhance grid observability and fault resilience. Particular attention is given to AI-driven optimization of energy storage dispatch, multi-agent coordination in microgrids, and the deployment of edge intelligence for decentralized control. Furthermore, the review evaluates current barriers—ranging from data sparsity and model interpretability to lack of standardization—and proposes targeted research directions, including explainable AI, quantum-enhanced computing, and AI-powered coordination of distributed storage and vehicle-to-grid (V2G) networks. The convergence of AI, digital infrastructure, and policy innovation emerges as critical to unlocking the full potential of next-generation grids. This article provides researchers, engineers, and policymakers with a rigorous synthesis of current advancements and a forward-looking agenda for achieving intelligent, resilient, and decarbonized energy systems.
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Mosleuzzaman, Md, H. M. Shamsuzzaman, and Md Delwar Hussain. "ENGINEERING CHALLENGES AND SOLUTIONS IN SMART GRID INTEGRATION WITH ELECTRIC VEHICLES." ACADEMIC JOURNAL ON SCIENCE, TECHNOLOGY, ENGINEERING & MATHEMATICS EDUCATION 4, no. 3 (2024): 139–50. http://dx.doi.org/10.69593/ajsteme.v4i03.102.
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This paper explores the critical engineering challenges and innovative solutions for successfully integrating intelligent grids and electric vehicles (EVs), emphasizing the increasing need for a resilient and adaptive electrical grid as global EV adoption accelerates. It comprehensively examines the technological, infrastructural, and regulatory obstacles that must be addressed to ensure seamless integration, focusing on advanced energy management systems, grid stability amidst fluctuating demand, and incorporating renewable energy sources. The study delves into the infrastructural requirements, including the expansion of charging networks, upgrades to transmission and distribution systems, and the implementation of vehicle-to-grid (V2G) technologies, while also analyzing the necessary regulatory and policy frameworks, stressing the importance of clear standards, incentives, and public-private collaboration. The paper offers a forward-looking perspective on overcoming current challenges by reviewing recent advancements in innovative grid technology—such as high-capacity energy storage and artificial intelligence (AI) use for predictive maintenance and load balancing. It highlights the need for interdisciplinary collaboration among engineers, policymakers, and industry leaders to develop a cohesive strategy for future energy distribution while underscoring the role of AI in optimizing grid performance, predicting energy consumption patterns, and enhancing overall efficiency. Ultimately, the paper provides a comprehensive analysis of the current state of smart grid and EV integration, offering actionable insights for stakeholders and concluding with recommendations for future research and development priorities, with a strong emphasis on continued innovation and cooperation to achieve a sustainable and resilient energy future.
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Cao, Yi, Tianying Xiao, and Yu Liang. "Analysis on the development of modern rural power grids with low carbon serving rural revitalization from the perspective of scientific and technological innovation." International Journal of Low-Carbon Technologies 19 (2024): 1445–52. http://dx.doi.org/10.1093/ijlct/ctae075.
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Abstract Our country is a large agricultural nation where the development of rural areas holds paramount importance. To achieve rural revitalization, the development of electric power infrastructure is crucial. However, to ensure sustainable growth, attention must be directed towards low-carbon initiatives. With the continuous advancement of science and technology, rural power grids are steadily transitioning towards intelligent development, marking a significant stride in our nation’s power grid evolution. The establishment of smart grids can effectively address energy consumption issues in rural areas, simultaneously aiding in the reduction of energy usage and carbon emissions. Information technology, interactivity and automation are pivotal technical features characterizing the intelligence of rural power grids, leveraging technological advancements to drive the reform of modern rural power systems. This article intends to focus on optimizing low-carbon development within the ambit of intelligent rural power grid construction, alongside a comprehensive analysis of related developments. Such efforts aim to seamlessly integrate rural power development with a low-carbon economy, offering crucial insights and guidance for the sustainable growth of rural power grids. This endeavor contributes to the overarching objectives of rural revitalization and fostering a low-carbon economy.
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Yewande Mariam Ogunsuji, Olamide Raimat Amosun, Praveen Kumar, and Divya Choubey. "Integration of smart grid technologies: Implementing advanced procurement strategies leveraging AI and machine learning." World Journal of Advanced Research and Reviews 23, no. 1 (2024): 2985–98. http://dx.doi.org/10.30574/wjarr.2024.23.1.2214.
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Integrating smart grid technologies represents a pivotal advancement in modernizing electrical grids and enhancing efficiency, reliability, and sustainability. This publication explores the role of advanced procurement strategies, specifically leveraging artificial intelligence (AI) and machine learning (ML), in streamlining the sourcing and integration of smart grid components. By examining current challenges, potential solutions, and the impact on national security and economic stability, this paper aims to provide a comprehensive framework for the effective implementation of smart grid technologies. The traditional electrical grid, characterized by its centralized generation and unidirectional power flow, faces numerous challenges, such as inefficiency, susceptibility to outages, and inability to integrate renewable energy sources effectively (Brown et al., 2020). The transformation to a smart grid infrastructure, which incorporates digital communication technology and advanced sensors, promises significant improvements. However, the transition is fraught with challenges, particularly in the procurement and integration of the necessary components. One of the primary challenges in smart grid integration is the complexity of supply chains. The procurement of smart grid components involves multiple stakeholders, including manufacturers, suppliers, and regulatory bodies. This complexity often leads to delays, increased costs, and inefficiencies (Smith & Wang, 2019). Additionally, the high initial costs of smart grid technologies pose a barrier to widespread adoption. Traditional procurement methods struggle to balance cost-efficiency with the need for high-quality, durable components, often resulting in budget overruns or compromised quality.
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Yewande, Mariam Ogunsuji, Raimat Amosun Olamide, Kumar Praveen, and Choubey Divya. "Integration of smart grid technologies: Implementing advanced procurement strategies leveraging AI and machine learning." World Journal of Advanced Research and Reviews 23, no. 1 (2024): 2985–98. https://doi.org/10.5281/zenodo.14830574.
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Integrating smart grid technologies represents a pivotal advancement in modernizing electrical grids and enhancing efficiency, reliability, and sustainability. This publication explores the role of advanced procurement strategies, specifically leveraging artificial intelligence (AI) and machine learning (ML), in streamlining the sourcing and integration of smart grid components. By examining current challenges, potential solutions, and the impact on national security and economic stability, this paper aims to provide a comprehensive framework for the effective implementation of smart grid technologies. The traditional electrical grid, characterized by its centralized generation and unidirectional power flow, faces numerous challenges, such as inefficiency, susceptibility to outages, and inability to integrate renewable energy sources effectively (Brown et al., 2020). The transformation to a smart grid infrastructure, which incorporates digital communication technology and advanced sensors, promises significant improvements. However, the transition is fraught with challenges, particularly in the procurement and integration of the necessary components. One of the primary challenges in smart grid integration is the complexity of supply chains. The procurement of smart grid components involves multiple stakeholders, including manufacturers, suppliers, and regulatory bodies. This complexity often leads to delays, increased costs, and inefficiencies (Smith & Wang, 2019). Additionally, the high initial costs of smart grid technologies pose a barrier to widespread adoption. Traditional procurement methods struggle to balance cost-efficiency with the need for high-quality, durable components, often resulting in budget overruns or compromised quality.
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Nagarsheth, Shaival, Kodjo Agbossou, Nilson Henao, and Mathieu Bendouma. "The Advancements in Agricultural Greenhouse Technologies: An Energy Management Perspective." Sustainability 17, no. 8 (2025): 3407. https://doi.org/10.3390/su17083407.
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Greenhouse technologies provide controlled environmental conditions for crop growth, often incorporating automation to enhance productivity. Energy management, which involves monitoring, controlling, and conserving energy, is particularly crucial in northern climates, where greenhouses are among the most energy-intensive sectors of agriculture. This paper presents a comprehensive review of state-of-the-art greenhouse technologies from an energy management perspective, exploring their role in enhancing efficiency and sustainability. It examines the energy management framework, key technological advancements, benefits, challenges, and available solutions in the market. Furthermore, it discusses principles and methods of energy optimization, best practices for sustainable greenhouse operations, and emerging trends in smart grids, renewable integration, and automation. Unlike previous studies primarily focusing on agricultural and control perspectives, this review highlights new insights into integrating greenhouse energy management with smart grid participation, leveraging model predictive control (MPC) for energy optimization, multi-agent reinforcement learning (DRL) for adaptive control, and digital twin technology for real-time system modeling. By bridging greenhouse energy management with transactive energy platforms, this paper underscores the importance of intelligent, data-driven decision-making in enhancing efficiency, sustainability, and system resilience while minimizing environmental impact.
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Adewale Wasiu Adegboyega, Stephen Opeyemi Oladunni, Abrar Shahriar Pramanik, Emmanuel Chigozie Ani, and Ayodele Oyesanya. "Agile project management in smart grid design: Comparative insights from Africa and the United States." International Journal of Science and Research Archive 12, no. 2 (2024): 1411–19. http://dx.doi.org/10.30574/ijsra.2024.12.2.1397.
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The transition to smart grid technologies represents a critical evolution in modern power systems, driven by the need for enhanced efficiency, reliability, and sustainability. This article explores the integration of agile project management principles within the context of smart grid design and deployment. By examining the foundational concepts of agile methodologies and their application in smart grid projects, this study highlights the benefits of iterative development, stakeholder collaboration, and rapid adaptation to technological advancements. A comparative analysis of agile practices in Africa and the United States reveals unique regional challenges and opportunities, emphasizing the importance of tailored approaches. Furthermore, emerging trends such as the convergence of agile with artificial intelligence, cybersecurity, and digital twin technologies are discussed, showcasing the future potential of these methodologies in advancing smart grid innovations. Despite the inherent complexities and security concerns, the adoption of agile practices offers significant advantages, including enhanced flexibility, efficient resource utilization, and improved stakeholder engagement. The findings underscore the necessity for a balanced approach, combining agile methods with traditional project management to navigate the multifaceted landscape of smart grid development. This study provides valuable insights and recommendations for stakeholders aiming to leverage agile principles to create resilient, user-centric, and future-proof energy systems.
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Michael Ibukun Kolawole and Busayo Leah Ayodele. "Smart electronics in solar-powered grid systems for enhanced renewable energy efficiency and reliability." International Journal of Science and Research Archive 13, no. 2 (2024): 2910–30. https://doi.org/10.30574/ijsra.2024.13.2.2512.
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Harnessing solar energy for grid electricity management has become a global imperative in the pursuit of sustainable energy solutions. Advanced electronics, including smart inverters, IoT-enabled sensors, and intelligent monitoring systems, are revolutionizing how solar energy is integrated into power grids. These technologies enable efficient energy storage, dynamic load balancing, and seamless distribution, addressing the variability of solar power and ensuring grid stability. By adopting innovative strategies, solar energy integration enhances overall grid efficiency, minimizes energy losses, and supports the scalability of renewable energy systems worldwide. This paper provides a global perspective on advanced approaches to solar energy integration within modern grids, highlighting the transformative role of cutting-edge electronics. Key innovations, such as real-time energy routing, intelligent demand forecasting, and Maximum Power Point Tracking (MPPT), are explored for their ability to optimize energy capture and consumption. The study also emphasizes the importance of hybrid energy storage systems, including next-generation lithium-ion and solid-state batteries, in stabilizing grid performance and ensuring resilience against disruptions. Despite these advancements, challenges such as high implementation costs, cybersecurity vulnerabilities, and interoperability issues persist. The paper proposes globally-oriented solutions, including international policy frameworks, cross-sector partnerships, and increased investments in research and development, to drive adoption. By aligning technological innovation with collaborative action, integrating solar energy into grid management systems can accelerate the global transition to a reliable, efficient, and sustainable energy future.
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Vinodkumar Devarajan. "Revolutionizing Energy Management: The Impact of AI and Machine Learning Technologies." Journal of Computer Science and Technology Studies 7, no. 3 (2025): 327–33. https://doi.org/10.32996/jcsts.2025.7.3.37.
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The integration of Artificial Intelligence and Machine Learning technologies is revolutionizing the energy sector by transforming energy optimization, predictive maintenance, and smart grid management. From advanced demand forecasting to dynamic pricing mechanisms, these technologies enable sophisticated control and monitoring of power distribution networks. The implementation of predictive maintenance systems with sensor analytics and anomaly detection frameworks has enhanced equipment reliability and operational efficiency. Smart grid management through AI-driven optimization and edge computing capabilities has improved grid stability and monitoring capabilities. Technical considerations in infrastructure requirements and algorithm selection have led to optimized system performance, while emerging developments in quantum computing and privacy preservation technologies promise further advancements in energy management systems.
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Kalalas, Charalampos, Linus Thrybom, and Jesús Alonso-Zárate. "Cellular Communications for Smart Grid Neighborhood Area Networks: A Survey." IEEE Access 4 (April 1, 2016): 1469–93. https://doi.org/10.1109/ACCESS.2016.2551978.
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This paper surveys the literature related to the evolution of cellular communications as a key enabling technology for fundamental operations of smart grid neighborhood area networks (NANs). The latest releases of the LTE standard, representing the recent advancements in cellular technology, offer significant benefits to the modernization of the aging power distribution grid compared with other communication technologies. However, since LTE was not originally designed for smart grid applications, important challenges remain unsolved before it can efficiently support advanced NAN functionalities. This survey identifies the limitations of LTE and provides a comprehensive review of the most relevant proposed architectural and protocol enhancements for the communication infrastructure associated with smart grid NANs that can be found in the literature to date. As device-to-device (D2D) communications in LTE standards are a promising technology for reducing delay and boost reliability, this paper dwells on the potential gains that can be achieved by enabling direct communication using cellular networks, and also discusses in detail LTE-D2D applicability in representative NAN use cases in the power distribution grid. We conclude by stating open issues and providing research directions for future research in the field. This paper constitutes the first comprehensive survey of proposed LTE-enhancement and D2D solutions for smart grid NANs.
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Shawanti, Roy, Paramanik Sayan, and Sarker Krishna. "Advancements in smart meter design and integration for enhanced energy management and efficiency." i-manager’s Journal on Electrical Engineering 18, no. 1 (2024): 12. https://doi.org/10.26634/jee.18.1.21366.
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The integration of smart meters into contemporary energy infrastructure is paramount for optimizing energy utilization and efficiency. This paper delves into a comprehensive exploration of smart meter design and operation using microcontroller-based simulation through Proteus Professional software. Incorporating essential components such as OPAMP LM358, XOR Gate 74LS386, resistors, capacitors, diodes, transformers, and microcontrollers, the smart meter aims to precisely measure and monitor power consumption. Moreover, it envisions seamless integration with connectivity technologies like GPRS, Public Network, Corporate Network, and Global Gateway to facilitate real-time communication and data exchange. By fostering a symbiotic relationship between smart meters and the smart grid, this integration strives to elevate energy management practices, curtail wastage, and foster sustainability. The paper elucidates the conceptual framework, design principles, and potential benefits of this integration, thus setting the stage for future advancements in smart energy infrastructure. Notably, the proposed smart meter boasts the capability to measure various electrical parameters including Voltage, Current, Frequency, Energy, Phase Angle, Active power, Reactive power, making it pivotal for big data analysis, thereby underscoring its significance in contemporary energy management endeavours.