Relevant bibliographies by topics / Smart Grid and Advancements

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Academic literature on the topic 'Smart Grid and Advancements'

Author: Grafiati
Published: 5 June 2025
Last updated: 16 July 2025

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Journal articles on the topic "Smart Grid and Advancements"

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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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Dissertations / Theses on the topic "Smart Grid and Advancements"

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Rylander, Anton. "Smart Grid." Thesis, Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-23430.

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Wang, Zhimin. "Smart pricing for smart grid." Thesis, University of Bath, 2014. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.619224.

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Flat-rate electricity tariffs in Great Britain, which have no price variation throughout a day or a year, have been ongoing for decades to recover the cost of energy production and delivery. However, this type of electricity tariff has little incentives to encourage customers to modify their demands to suit the condition of the power supply system. Hence, it is challenged in the new smart grid environment, where demand side responses have important roles to play to encourage conventional energy efficiency and support the integration of renewable generation. In order to accommodate this new environment, the investigations of smart tariff designs and their applications in demand side response are therefore carried out from three main aspects. In a high carbon system dominated by controllable fossil generation where energy peaks typically coincide with those of networks, smart tariffs are developed by statistically tracking dynamic energy price variation tendencies and categorising real-time prices to form time-of-use patterns that capture the most significant price variations without compromising too much accuracy in total energy revenue from customers. In a low carbon system where energy peaks and network peaks may not be in synchronism at all times, additional complications will be raised when developing smart tariffs and optimal demand side response strategies. A new concept is developed in this thesis to allow shared utilization of energy storage between customers and distributed network operators to respond to conflicting energy price and network conditions. In this work, two operation models of storage share are implemented. One is fixed share between customers and network operators regardless of network conditions, and the other is dynamic share that storage capacity utilized by network operator changes with network condition. The consequential system benefit in terms of energy cost reduction and network cost saving is evaluated and converted into per unit cost reduction in the energy bill. Addition to technical solution in the form of storage, the benefit from household demand shifting, such as shifting wet appliances, in the presence of smart tariffs is evaluated. The value of household demand shifting is quantified as an equivalent storage capacity for the investigation of complementarity between technical and social interventions.
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Mustafa, Mustafa Asan. "Smart Grid security : protecting users' privacy in smart grid applications." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/smart-grid-security-protecting-users-privacy-in-smart-grid-applications(565d4c36-8c83-4848-a142-a6ff70868d93).html.

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Smart Grid (SG) is an electrical grid enhanced with information and communication technology capabilities, so it can support two-way electricity and communication flows among various entities in the grid. The aim of SG is to make the electricity industry operate more efficiently and to provide electricity in a more secure, reliable and sustainable manner. Automated Meter Reading (AMR) and Smart Electric Vehicle (SEV) charging are two SG applications tipped to play a major role in achieving this aim. The AMR application allows different SG entities to collect users’ fine-grained metering data measured by users’ Smart Meters (SMs). The SEV charging application allows EVs’ charging parameters to be changed depending on the grid’s state in return for incentives for the EV owners. However, both applications impose risks on users’ privacy. Entities having access to users’ fine-grained metering data may use such data to infer individual users’ personal habits. In addition, users’ private information such as users’/EVs’ identities and charging locations could be exposed when EVs are charged. Entities may use such information to learn users’ whereabouts, thus breach their privacy. This thesis proposes secure and user privacy-preserving protocols to support AMR and SEV charging in an efficient, scalable and cost-effective manner. First, it investigates both applications. For AMR, (1) it specifies an extensive set of functional requirements taking into account the way liberalised electricity markets work and the interests of all SG entities, (2) it performs a comprehensive threat analysis, based on which, (3) it specifies security and privacy requirements, and (4) it proposes to divide users’ data into two types: operational data (used for grid management) and accountable data (used for billing). For SEV charging, (1) it specifies two modes of charging: price-driven mode and price-control-driven mode, and (2) it analyses two use-cases: price-driven roaming SEV charging at home location and price-control-driven roaming SEV charging at home location, by performing threat analysis and specifying sets of functional, security and privacy requirements for each of the two cases. Second, it proposes a novel Decentralized, Efficient, Privacy-preserving and Selective Aggregation (DEP2SA) protocol to allow SG entities to collect users’ fine-grained operational metering data while preserving users’ privacy. DEP2SA uses the homomorphic Paillier cryptosystem to ensure the confidentiality of the metering data during their transit and data aggregation process. To preserve users’ privacy with minimum performance penalty, users’ metering data are classified and aggregated accordingly by their respective local gateways based on the users’ locations and their contracted suppliers. In this way, authorised SG entities can only receive the aggregated data of users they have contracts with. DEP2SA has been analysed in terms of security, computational and communication overheads, and the results show that it is more secure, efficient and scalable as compared with related work. Third, it proposes a novel suite of five protocols to allow (1) suppliers to collect users accountable metering data, and (2) users (i) to access, manage and control their own metering data and (ii) to switch between electricity tariffs and suppliers, in an efficient and scalable manner. The main ideas are: (i) each SM to have a register, named accounting register, dedicated only for storing the user’s accountable data, (ii) this register is updated by design at a low frequency, (iii) the user’s supplier has unlimited access to this register, and (iv) the user cancustomise how often this register is updated with new data. The suite has been analysed in terms of security, computational and communication overheads. Fourth, it proposes a novel protocol, known as Roaming Electric Vehicle Charging and Billing, an Anonymous Multi-User (REVCBAMU) protocol, to support the priced-driven roaming SEV charging at home location. During a charging session, a roaming EV user uses a pseudonym of the EV (known only to the user’s contracted supplier) which is anonymously signed by the user’s private key. This protocol protects the user’s identity privacy from other suppliers as well as the user’s privacy of location from its own supplier. Further, it allows the user’s contracted supplier to authenticate the EV and the user. Using two-factor authentication approach a multi-user EV charging is supported and different legitimate EV users (e.g., family members) can be held accountable for their charging sessions. With each charging session, the EV uses a different pseudonym which prevents adversaries from linking the different charging sessions of the same EV. On an application level, REVCBAMU supports fair user billing, i.e., each user pays only for his/her own energy consumption, and an open EV marketplace in which EV users can safely choose among different remote host suppliers. The protocol has been analysed in terms of security and computational overheads.
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Asbery, Christopher W. "SMART GRID COMMUNICATIONS." UKnowledge, 2012. http://uknowledge.uky.edu/ece_etds/10.

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Smart grid technologies are starting to be the future of electric power systems. These systems are giving the utilities detailed information about their systems in real time. One of the most challenging things of implementing smart grid applications is employing the communications into the systems. Understanding the available communications can help ease the transition to these smart grid applications. Many of the utility personnel are spending too much time trying to figure out which communication is better for their application or applications. So this thesis presents the different communication types available with discussing the different attributes in which these communication types are going to offer to the utility. Then these communication types are looked such that utilities can quickly understand how to approach the difficult task of obtaining the information from the different smart grid applications by the use of different communication options.
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Chang, Shuai, Andy Gee, Benjamin Ramos, Kyle Province, Dan Harcourt, and Matthew Hendrick. "Smart Grid Impedance Meter." Thesis, The University of Arizona, 2013. http://hdl.handle.net/10150/297527.

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Texas Instruments has been developing Power Line Communication (PLC) technology to provide a form of communication for worldwide applications. By utilizing power grids within an infrastructure, it is possible to transmit a signal through the existing power lines such as a network would. Transmission of data within the electrical grid proves to be inherently noisy, thus compromising any information that is sent over the network. In order to provide a reliable platform of communication, frequency and impedance variation needs to be analyzed in order to provide proper development into PLC solutions. Within the scope of this project an analytical tool was developed to provide engineers with a method to determine impedance and frequency variations. Analysis and testing has been conducted to ensure the device satisfies the design requirements.
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Piehl, Hampus. "Wind power integration in island-based smart grid projects : A comparative study between Jeju Smart Grid Test-bed and Smart Grid Gotland." Thesis, Uppsala universitet, Elektricitetslära, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-224531.

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Smart grids seem to be the solution to use energy from renewable and intermittent energy sources in an efficient manner. There are many research projects around the world and two of them are Jeju Smart Grid Test-bed and Smart Grid Gotland. They have in common that they are both island-based projects and connected to the Powergrid on the mainland by HVDC-link. The purpose of this thesis is to compare the two projects and find out what challenges and strategies they have related to wind power integration. The objective of the two projects were somewhat different. Jeju Smart Grid Test-bedare the starting point for South Korea’s smart grid road map, where the objective ultimately is to construct a smart grid on a national scale in South Korea. For Smart Grid Gotland there are three main focus areas; electricity market, power quality and wind power integration. In this thesis focus is on wind power integration. Wind power integration in smart grids would benefit from energy storage technology connected to the wind power-park to even out the power output. Properties for a potential energy storage connected to Näsudden wind power park situated on the southern tip of Gotland has been investigated and the result is that such an energy storage would likely need to be big and expensive, but able to stabilize the power output.
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Zhang, Haotian. "Smart grid technologies and implementations." Thesis, City University London, 2014. http://openaccess.city.ac.uk/5918/.

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Smart grid has been advocated in both developing and developed countries in many years to deal with large amount of energy deficit and air pollutions. However, many literatures talked about some specific technologies and implementations, few of them could give a clear picture on the smart grid implementations in a macro scale like what is the main consideration for the smart grid implementations, how to examine the power system operation with communication network deployment, how to determine the optimal technology scheme with consideration of economic and political constraints, and so on. Governments and related institutions are keen to evaluate the cost and benefit of new technologies or mechanisms in a scientific way rather than making decision blindly. Decision Support System, which is an information system based on interactive computers to support decision making in planning, management, operations for evaluating technologies, is an essential tool to provide decision makers with powerful scientific evidence. The objective of the thesis is to identify the data and information processing technologies and mechanisms which will enable the further development of decision support systems that can be used to evaluate the indices for smart grid technology investment in the future. First of all, the thesis introduces the smart grid and its features and technologies in order to clarify the benefits can be obtained from smart grid deployment in many aspects such as economics, environment, reliability, efficiency, security and safety. Besides, it is necessary to understand power system business and operation scenarios which may affect the communication network model. This thesis, for the first time, will give detailed requirements for smart grid simulation according to the power system business and operation. In addition, state of art monitoring system and communication system involved in smart grid for better demand side management will be reviewed in order to find out their impacts reflecting to the power systems. The methods and algorithms applied to the smart grid monitoring, communication technologies for smart grid are summarized and the monitoring systems are compared with each other to see the merits and drawbacks in each type of the monitoring system. In smart grid environment, large number of data are need to be processed and useful information are required to be abstracted for further operation in power systems. Machine learning is a useful tool for data mining and prediction. One of the typical machine learning artificial algorithms, artificial neural network (ANN) for load forecasting in large power system is proposed in this thesis and different learning methods of back-propagation, Quasi-Newton and Levenberg-Marquardt, are compared with each other to seek the best result in load forecasting. Bad load forecasting may leads to demand and generation mismatch, which could cause blackout in power systems. Load shedding schemes are powerful defender for power system from collapsing and keep the grid in integral to a maximum extent. A lesson learned from India blackout in July 2012 is analyzed and recommendations on preventing grid from blackout are given in this work. Also, a new load shedding schemes for an isolated system is proposed in this thesis to take full advantage from information sharing and communication network deployment in smart grid. Lastly, the new trend of decision support system (DSS) for smart grid implementation is summarized and reliability index and stability scenarios for cost benefit analysis are under DSS consideration. Many countries and organizations are setting renewable penetration goals when planning the contribution to reduce the greenhouse gas emission in the future 10 or 20 years. For instance, UK government is expecting to produce 27% of renewable energies EU-wide before 2030. Some simulations have been carried out to demonstrate the physical insight of a power system operation with renewable energy integration and to study the non-dispatchable energy source penetration level. Meanwhile, issues from power system reliability which may affect consumers are required to take into account. Reliability index of Centralized wind generations and that of distributed wind generations are compared with each other under an investment perspective.
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Panneerselvam, Praveen Jelish. "Design of smart grid interfaces, Focusing of smart TVs." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3670.

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Smart Grid research is growing around the world due to the need to replace the ageing old electricity grid with an intelligent, reliable electricity network. The smart grid aims at creating a reliable power distribution and efficient power usage in homes. One of the key issues focused in this project is providing real time energy feedback to users, which is minimal or non-existent in the current grid system. This thesis investigates about using smart TVs to provide real time energy feedback in homes. Since its introduction in 2009 smart TVs are growing in popularity in European market. To provide real time energy feedback on smart TVs three features are identified Smart TV application, ambilighting and push notification. The Human-centered design process is used for designing the Smart TV interface system using the identified features. A literature study is conducted to gather the user requirements for the smart TV interface. The information gathered during the study is used for the design and implementation of the interface prototype. As an example platform the Philips smart TV 2013 is chosen to demonstrate the various features that can be used to provide energy feedback. The usability of the Smart TV interface is evaluated with users and the results are recorded. The smart TV application, ambient lighting and push notification system in Smart TVs is demonstrated for providing real-time energy feedback. The interface is evaluated with users and results are discussed. The result suggests that Smart TVs can serve as an informational display in homes. The Smart TV interface should be interlinked with Smart Phone and Tablet applications to be effective, further the users prefer the Smart Phone over the Smart TV application to control the household devices.<br>The thesis work evaluates the potential of using smart TVs to provide real time energy feedback in homes. The results of the thesis showed that smart phone are the primary interaction medium suitable for home environment while smart TVs can serve as an informative medium to provide ambient feedback in homes.<br>praveenjelish@ymail.com +46727700788
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Kalalas, Charalampos. "Cellular networks for smart grid communication." Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/620760.

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The next-generation electric power system, known as smart grid, relies on a robust and reliable underlying communication infrastructure to improve the efficiency of electricity distribution. Cellular networks, e.g., LTE/LTE-A systems, appear as a promising technology to facilitate the smart grid evolution. Their inherent performance characteristics and well-established ecosystem could potentially unlock unprecedented use cases, enabling real-time and autonomous distribution grid operations. However, cellular technology was not originally intended for smart grid communication, associated with highly-reliable message exchange and massive device connectivity requirements. The fundamental differences between smart grid and human-type communication challenge the classical design of cellular networks and introduce important research questions that have not been sufficiently addressed so far. Motivated by these challenges, this doctoral thesis investigates novel radio access network (RAN) design principles and performance analysis for the seamless integration of smart grid traffic in future cellular networks. Specifically, we focus on addressing the fundamental RAN problems of network scalability in massive smart grid deployments and radio resource management for smart grid and human-type traffic. The main objective of the thesis lies on the design, analysis and performance evaluation of RAN mechanisms that would render cellular networks the key enabler for emerging smart grid applications. The first part of the thesis addresses the radio access limitations in LTE-based networks for reliable and scalable smart grid communication. We first identify the congestion problem in LTE random access that arises in large-scale smart grid deployments. To overcome this, a novel random access mechanism is proposed that can efficiently support real-time distribution automation services with negligible impact on the background traffic. Motivated by the stringent reliability requirements of various smart grid operations, we then develop an analytical model of the LTE random access procedure that allows us to assess the performance of event-based monitoring traffic under various load conditions and network configurations. We further extend our analysis to include the relation between the cell size and the availability of orthogonal random access resources and we identify an additional challenge for reliable smart grid connectivity. To this end, we devise an interference- and load-aware cell planning mechanism that enhances reliability in substation automation services. Finally, we couple the problem of state estimation in wide-area monitoring systems with the reliability challenges in information acquisition. Using our developed analytical framework, we quantify the impact of imperfect communication reliability in the state estimation accuracy and we provide useful insights for the design of reliability-aware state estimators. The second part of the thesis builds on the previous one and focuses on the RAN problem of resource scheduling and sharing for smart grid and human-type traffic. We introduce a novel scheduler that achieves low latency for distribution automation traffic while resource allocation is performed in a way that keeps the degradation of cellular users at a minimum level. In addition, we investigate the benefits of Device-to-Device (D2D) transmission mode for event-based message exchange in substation automation scenarios. We design a joint mode selection and resource allocation mechanism which results in higher data rates with respect to the conventional transmission mode via the base station. An orthogonal resource partition scheme between cellular and D2D links is further proposed to prevent the underutilization of the scarce cellular spectrum. The research findings of this thesis aim to deliver novel solutions to important RAN performance issues that arise when cellular networks support smart grid communication.<br>Las redes celulares, p.e., los sistemas LTE/LTE-A, aparecen como una tecnología prometedora para facilitar la evolución de la próxima generación del sistema eléctrico de potencia, conocido como smart grid (SG). Sin embargo, la tecnología celular no fue pensada originalmente para las comunicaciones en la SG, asociadas con el intercambio fiable de mensajes y con requisitos de conectividad de un número masivo de dispositivos. Las diferencias fundamentales entre las comunicaciones en la SG y la comunicación de tipo humano desafían el diseño clásico de las redes celulares e introducen importantes cuestiones de investigación que hasta ahora no se han abordado suficientemente. Motivada por estos retos, esta tesis doctoral investiga los principios de diseño y analiza el rendimiento de una nueva red de acceso radio (RAN) que permita una integración perfecta del tráfico de la SG en las redes celulares futuras. Nos centramos en los problemas fundamentales de escalabilidad de la RAN en despliegues de SG masivos, y en la gestión de los recursos radio para la integración del tráfico de la SG con el tráfico de tipo humano. El objetivo principal de la tesis consiste en el diseño, el análisis y la evaluación del rendimiento de los mecanismos de las RAN que convertirán a las redes celulares en el elemento clave para las aplicaciones emergentes de las SGs. La primera parte de la tesis aborda las limitaciones del acceso radio en redes LTE para la comunicación fiable y escalable en SGs. En primer lugar, identificamos el problema de congestión en el acceso aleatorio de LTE que aparece en los despliegues de SGs a gran escala. Para superar este problema, se propone un nuevo mecanismo de acceso aleatorio que permite soportar de forma eficiente los servicios de automatización de la distribución eléctrica en tiempo real, con un impacto insignificante en el tráfico de fondo. Motivados por los estrictos requisitos de fiabilidad de las diversas operaciones en la SG, desarrollamos un modelo analítico del procedimiento de acceso aleatorio de LTE que nos permite evaluar el rendimiento del tráfico de monitorización de la red eléctrica basado en eventos bajo diversas condiciones de carga y configuraciones de red. Además, ampliamos nuestro análisis para incluir la relación entre el tamaño de celda y la disponibilidad de recursos de acceso aleatorio ortogonales, e identificamos un reto adicional para la conectividad fiable en la SG. Con este fin, diseñamos un mecanismo de planificación celular que tiene en cuenta las interferencias y la carga de la red, y que mejora la fiabilidad en los servicios de automatización de las subestaciones eléctricas. Finalmente, combinamos el problema de la estimación de estado en sistemas de monitorización de redes eléctricas de área amplia con los retos de fiabilidad en la adquisición de la información. Utilizando el modelo analítico desarrollado, cuantificamos el impacto de la baja fiabilidad en las comunicaciones sobre la precisión de la estimación de estado. La segunda parte de la tesis se centra en el problema de scheduling y compartición de recursos en la RAN para el tráfico de SG y el tráfico de tipo humano. Presentamos un nuevo scheduler que proporciona baja latencia para el tráfico de automatización de la distribución eléctrica, mientras que la asignación de recursos se realiza de un modo que mantiene la degradación de los usuarios celulares en un nivel mínimo. Además, investigamos los beneficios del modo de transmisión Device-to-Device (D2D) en el intercambio de mensajes basados en eventos en escenarios de automatización de subestaciones eléctricas. Diseñamos un mecanismo conjunto de asignación de recursos y selección de modo que da como resultado tasas de datos más elevadas con respecto al modo de transmisión convencional a través de la estación base. Finalmente, se propone un esquema de partición de recursos ortogonales entre enlaces celulares y D2
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Lohani, Satyendra Nath. "Communication Network Analysis in Smart Grid." Thesis, Linnéuniversitetet, Institutionen för datavetenskap, fysik och matematik, DFM, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-19088.

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With the world suffering from energy crisis, Smart Grid is the expanding research topic that deals vigorously with the current problems. It promotes decentralized renewable energy generation system, participate many local energy producers to energy market, adds vehicle to grid (V2G), minimize the energy loss in the electrical system, and participate many active consumers to the real market. It is an emerging project that needs an expert from many fields, thus it opens door of opportunities for many people around the globe. The present thesis deals with the communication scenario in smart grid. Communication is the backbone of Smart Grid and the thesis tries to highlight the available communication technologies for smart grid application. The thesis discuss most profitable communication technologies used for this purpose which are power line communication and wireless communication, in which power line communication aspects and characteristics are covered more than wireless communication for its use are seen more in upcoming days. In all the thesis will outline the opportunities and challenges of power line communication and wireless communication for smart grid application.
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Books on the topic "Smart Grid and Advancements"

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Ekanayake, Janaka, Kithsiri Liyanage, Jianzhong Wu, Akihiko Yokoyama, and Nick Jenkins. Smart Grid. John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119968696.

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Bush, Stephen F. Smart Grid. John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118820216.

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Momoh, James. Smart Grid. John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118156117.

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Abougreen, Arij Naser, Shilpa Mehta, and Cristina Costa, eds. Interdisciplinary Technological Advancements in Smart Cities. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-69441-7.

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Cuellar, Jorge, ed. Smart Grid Security. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38030-3.

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Stoustrup, Jakob, Anuradha Annaswamy, Aranya Chakrabortty, and Zhihua Qu, eds. Smart Grid Control. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-98310-3.

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Cuellar, Jorge, ed. Smart Grid Security. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10329-7.

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Goel, Sanjay, Yuan Hong, Vagelis Papakonstantinou, and Dariusz Kloza. Smart Grid Security. Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-6663-4.

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Hertzog, Christine. Smart grid dictionary. 5th ed. GreenSpring Marketing LLC, 2013.

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Hertzog, Christine. Smart grid dictionary. 6th ed. GreenSpring Marketing LLC, 2014.

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Book chapters on the topic "Smart Grid and Advancements"

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Nag, Titas Kumar, Rituparna Mitra, Suvraujjal Dutta, Rituparna Mukherjee, Avik Dutta, and Susmita Dhar Mukherjee Mukherjee. "Energizing smart grid." In Recent Advancements in Computational Intelligence and Design Engineering. CRC Press, 2024. https://doi.org/10.1201/9781003596745-53.

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Altin, Necmi, and Süleyman Emre Eyimaya. "Advancements in DC Microgrids: Integrating Machine Learning and Communication Technologies for a Decentralized Future." In Smart Grid 3.0. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-38506-3_14.

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Rajeev, T., and S. Ashok. "Smart Grid Environment with Effective Storage and Computational Facilities." In Recent Advancements in System Modelling Applications. Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1035-1_1.

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Tripathy, Manoj, and M. Suresh. "Smart Grid: A Cyber–Physical Infrastructure and Security." In Soft Computing Applications for Advancements in Power Systems. River Publishers, 2024. http://dx.doi.org/10.1201/9788770046862-8.

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Das, Ridoy, Yue Cao, and Yue Wang. "A Review of the Trends in Smart Charging, Vehicle-to-Grid." In Recent Advancements in Connected Autonomous Vehicle Technologies. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-5751-2_10.

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Rojas, Daniel Gutiérrez, and Gonçalo Pinto Mendes. "Smart Grid Prediction and Restoration Advancements for the Achievement of Sustainable Development Goals." In Industry, Innovation and Infrastructure. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-71059-4_12-1.

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Nag, Titas Kumar, Rituparna Mitra, Rituparna Mukherjee, Avik Dutta, Suvraujjal Dutta, and Promit Kumar Saha. "A evaluation of the integration of renewable energy sources and electric vehicles in the smart grid." In Recent Advancements in Computational Intelligence and Design Engineering. CRC Press, 2024. https://doi.org/10.1201/9781003596745-54.

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Triet, N. M., T. D. Khoa, H. N. Kha, et al. "Blockchain-Enhanced Energy Trading in Smart Cities and Grids: Advancements in Market Systems and Business Models." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-74741-0_6.

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Al Abri, Dawood, Arif S. Malik, Mohammed Albadi, Yassine Charabi, and Nasser Hosseinzadeh. "Smart Grid." In Handbook of Climate Change Mitigation and Adaptation. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-14409-2_78.

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Wunderlich, Philipp. "Smart Grid." In Green Information Systems in the Residential Sector. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36769-4_2.

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Conference papers on the topic "Smart Grid and Advancements"

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Basmenj, Maryam Adib, and Moein Moeini-Aghtaie. "Harnessing Solar Energy: Advancements in Electrolysis and Photocatalysis Technologies." In 2024 14th Smart Grid Conference (SGC). IEEE, 2024. https://doi.org/10.1109/sgc64640.2024.10983698.

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Cremer, Jochen L., Adrian Kelly, Ricardo J. Bessa, et al. "A Pioneering Roadmap for ML-Driven Algorithmic Advancements in Electrical Networks." In 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE). IEEE, 2024. https://doi.org/10.1109/isgteurope62998.2024.10863139.

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Akashpalaniappa, A., and S. Nithya Roopa. "AI-Enhanced Predictive Analytics for Fraud Detection in Smart Grid Systems." In 2025 3rd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA). IEEE, 2025. https://doi.org/10.1109/icaeca63854.2025.11012186.

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Pritish, V., Praneeth Kumar, K. Annapurani, and Anirban Choudhary. "Cybersecurity strategies for protecting smart grid in Residential building complex from attacks." In 2024 2nd International Conference on Advancements and Key Challenges in Green Energy and Computing (AKGEC). IEEE, 2024. https://doi.org/10.1109/akgec62572.2024.10868067.

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Du, Wanlin, Ling Wang, and Wei Luo. "Advancements and Challenges in Grid Voltage Control: A Comprehensive Review of Intelligent Technologies and Future Directions." In 2024 4th International Conference on Smart City and Green Energy (ICSCGE). IEEE, 2024. https://doi.org/10.1109/icscge64239.2024.11064262.

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Mishra, Debani Prasad, Barsa Preyaadarshini, Kriti Mishra, Ayush Kumar, and Rakesh Kumar Lenka. "Advancements in Smart Grids: Harnessing AI, IoT, and 5G Integration for Sustainable Energy Management." In 2024 IEEE 1st International Conference on Advances in Signal Processing, Power, Communication, and Computing (ASPCC). IEEE, 2024. https://doi.org/10.1109/aspcc62191.2024.10881213.

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Chingshom, M., B. Shakila, and M. Prakash. "Fault Detection and Classification in Smart Grid Using Machine Learning Approach." In 2024 International Conference on Advancement in Renewable Energy and Intelligent Systems (AREIS). IEEE, 2024. https://doi.org/10.1109/areis62559.2024.10893627.

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Goyal, Samaksh, Prateek Garg, Anoop Dev, A. Amudha, P. Karthigaikumar, and Tushar R. Jadhav. "Versatility of Wi-Fi & Narrowband PLC Connections for The Smart Grid." In 2024 5th IEEE Global Conference for Advancement in Technology (GCAT). IEEE, 2024. https://doi.org/10.1109/gcat62922.2024.10924130.

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Narendran, S., and Bhaskarrao Yakkala. "Advancing Smart Grid Stability Through Machine Learning and Principal Component Analysis." In 2024 13th International Conference on System Modeling & Advancement in Research Trends (SMART). IEEE, 2024. https://doi.org/10.1109/smart63812.2024.10882568.

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Mishra, Vinayak, Narendra Pal Singh, Umesh Kumar Singh, Akshit Jain, and Doshi Saumya Rakesh Kumar. "Neural Network Controlled Grid Synchronization of Single-Phase Inverter Using SOGI-PLL for Efficient Solar Power Integration." In 2024 13th International Conference on System Modeling & Advancement in Research Trends (SMART). IEEE, 2024. https://doi.org/10.1109/smart63812.2024.10882574.

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Reports on the topic "Smart Grid and Advancements"

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Pasupuleti, Murali Krishna. Smart Nanomaterials and AI-Integrated Grids for Sustainable Renewable Energy. National Education Services, 2025. https://doi.org/10.62311/nesx/rr1025.

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Abstract: The transition to sustainable and intelligent renewable energy systems is being driven by advancements in smart nanomaterials and AI-integrated smart grids. Nanotechnology has enabled the development of high-performance energy materials, such as graphene, perovskites, quantum dots, and MXenes, which enhance the efficiency, durability, and scalability of renewable energy solutions. Simultaneously, AI-driven smart grids leverage machine learning, deep learning, and digital twins to optimize energy distribution, predictive maintenance, and real-time load balancing in renewable energy networks. This research explores the synergistic integration of AI and nanomaterials to develop self-regulating, adaptive, and fault-tolerant energy infrastructures. The study examines AI-powered energy storage, decentralized smart microgrids, quantum AI for grid cybersecurity, and blockchain-integrated energy trading. Furthermore, the report assesses global industry adoption, policy frameworks, and economic growth trends, providing a strategic roadmap for the large-scale implementation of AI-enhanced nanomaterial-based energy systems. Through case studies and real-world applications, this research highlights how AI and nanotechnology will drive the next-generation sustainable energy revolution. Keywords Smart nanomaterials, AI-integrated grids, sustainable renewable energy, graphene-based solar cells, perovskite photovoltaics, quantum dots in energy, MXenes for energy storage, AI-driven energy optimization, machine learning for smart grids, deep learning energy forecasting, predictive maintenance in energy grids, digital twins for grid management, AI-powered decentralized microgrids, blockchain energy trading, hydrogen storage nanomaterials, AI-enhanced lithium-ion batteries, reinforcement learning in energy distribution, AI for demand-side energy management, quantum AI for grid cybersecurity, scalable nanomaterial-based energy solutions, AI-driven self-healing energy materials.
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Yinger, Robert, and Mark Irwin. Irvine Smart Grid Demonstration, a Regional Smart Grid Demonstration Project. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1234553.

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Miller, Craig, Paul Carroll, and Abigail Bell. Smart Grid Demonstration Project. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1222698.

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Rabari, Anil, and Oloruntomi Fadipe. NSTAR Smart Grid Pilot. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1210191.

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None, None. Smart Grid Enabled EVSE. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1173066.

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Beaulieu, R. National Smart Water Grid. Office of Scientific and Technical Information (OSTI), 2009. http://dx.doi.org/10.2172/963122.

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Troxell, Wade. Smart Grid Integration Laboratory. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1043680.

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Backhaus, Scott N., Russell W. Bent, and Michael Chertkov. Smart Grid Control and Optimization. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1079965.

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Rahman, Saifur. Smart Grid Information Clearinghouse (SGIC). Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1179178.

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Marron, Jeffrey, Avi Gopstein, Nadya Bartol, and Valery Feldman. Cybersecurity framework smart grid profile. National Institute of Standards and Technology, 2019. http://dx.doi.org/10.6028/nist.tn.2051.

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