Relevant bibliographies by topics / Intelligent energy management systems

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Intelligent energy management systems'

Author: Grafiati
Published: 7 September 2021
Last updated: 29 July 2025

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Journal articles on the topic "Intelligent energy management systems"

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Poplavskyi, O. A., O. I. Soroka, M. O. Litvin, and A. V. Poplavskyi. "Intelligent risk management systems in european energy markets." Optoelectronic Information-Power Technologies 47, no. 1 (2024): 233–39. http://dx.doi.org/10.31649/1681-7893-2024-47-1-233-239.

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Based on machine learning algorithms, a method for predicting risks in the European energy markets has been proposed. The work is aimed at developing intelligent risk management systems that utilize advanced artificial intelligence technologies for assessing and minimizing potential threats. Utilizing historical data and current market trends, a comprehensive approach to identifying price volatility and risk zones in the energy markets is presented. The study demonstrates how artificial intelligence can enhance the effectiveness of decisions made by managers in the energy markets and ensure mo
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Sechilariu, Manuela. "Intelligent Energy Management of Electrical Power Systems." Applied Sciences 10, no. 8 (2020): 2951. http://dx.doi.org/10.3390/app10082951.

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Smart grid implementation is facilitated by multi-source energy systems development, i.e., microgrids, which are considered the key smart grid building blocks. Whether they are alternative current (AC) or direct current (DC), high voltage or low voltage, high power or small power, integrated into the distribution system or the transmission network, multi-source systems always require an intelligent energy management that is integrated into the power system. A comprehensive intelligent energy system aims at providing overall energy efficiency with regard to the following: increased power genera
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Sanieva, Alina D. "LOAD FORECASTING MODELS FOR INTELLIGENT POWER GRID MANAGEMENT SYSTEMS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 11/7, no. 152 (2024): 104–14. https://doi.org/10.36871/ek.up.p.r.2024.11.07.011.

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The article is devoted to the analysis of electric load forecasting models for intelligent power grid management systems. Short-term and long-term approaches are consid-ered, as well as hybrid models combining machine learning and statistical methods to improve the accuracy of predictions. The difficulties encountered in the integration of renewable energy sources and the role of artificial intelligence in adaptive load management are described. The prospects of using intelligent systems to optimize energy consumption in real time are predicted.
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Khatuev, Deni I., and Petimat A. Bisultanova. "DEVELOPMENT OF INTELLIGENT ENERGY MANAGEMENT SYSTEMS IN AUTONOMOUS POWER PLANTS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 11/13, no. 152 (2024): 126–32. https://doi.org/10.36871/ek.up.p.r.2024.11.13.016.

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The article is devoted to the development of intelligent energy management systems in autonomous power plants. The key aspects of building such systems are considered, including the use of artificial intelligence, machine learning and forecasting methods. The main hardware components, such as sensors, controllers and actuators, are described, as well as their role in collecting and processing data for decision-making. The benefits of implementing intelligent systems, including automation, increased reliability and resource efficiency are emphasized. The challenges and prospects for further dev
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STADNIK, Mykola, Andrii SHTUTS, Mykola KOLISNYK, and Nazar HRYHORENKO. "RESEARCH ON THE IMPLEMENTATION OF INTELLIGENT SYSTEMS TO INCREASE THE RELIABILITY AND EFFICIENCY OF THE OPERATION OF ELECTRIC POWER COMPLEXES." ENGINEERING, ENERGY, TRANSPORT AIC, no. 1 (128) (March 31, 2025): 122–34. https://doi.org/10.37128/2520-6168-2025-1-14.

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Intelligent systems (Smart Systems) are an important element of modern electric power industry, which allows to increase the reliability, efficiency and stability of the functioning of electric networks. The article considers the implementation of intelligent technologies for monitoring, management and optimization of the operation of energy systems. The main attention is paid to the use of artificial intelligence (AI), Internet of Things (IoT) and automated control systems to solve the problems of accident prediction, adaptive management of energy flows and integration of renewable energy sou
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De Paola, Alessandra, Marco Ortolani, Giuseppe Lo Re, Giuseppe Anastasi, and Sajal K. Das. "Intelligent Management Systems for Energy Efficiency in Buildings." ACM Computing Surveys 47, no. 1 (2014): 1–38. http://dx.doi.org/10.1145/2611779.

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Alava, Lenin Agustin Cuenca, Miriam Vilaragut Llanes, Miguel Castro Fernandez, Jesus Alberto Perez-Rodriguez, and Ciaddy Gina Rodriguez-Borges. "Artificial Intelligence as a Technology for the Management of Isolated Microgrids." NeuroQuantology 20, no. 5 (2022): 959–72. http://dx.doi.org/10.14704/nq.2022.20.5.nq22347.

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The current electrical energy systems aim to guarantee greater reliability, safety, and energy efficiency, promoting environmental benefits, integrating renewable sources of distributed energy. These solutions are obtained by incorporating Artificial Intelligence, by virtue of the current development of this technology to have "more intelligent" electrical energy networks. A review of the different aspects of technology for the Management of Isolated Microgrids is presented, identifying the trends, problems, and challenges, with their characteristics, functionalities, and their implementations
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Shuklin, G. V., O. V. Barabash, and A. B. Grebennikov. "Functional stability of intelligent systems in decision-making." PROBLEMS IN PROGRAMMING, no. 4 (December 2024): 89–98. https://doi.org/10.15407/pp2024.04.089.

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The article describes the concept of functional sustainability of intelligent systems in decision-making as one of the main aspects in the creation of methods for formalizing and modelling knowledge and the possibility of using it for decision support in the energy sector.The concept of functional stability was introduced for dynamic objects. However, for intelligent systems this concept is significantly different.This is due to the fact that the functioning of intelligent systems cannot be considered as the movement of an object. The functions of artificial intelligence for the creation of in
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Dounis. "Special Issue “Intelligent Control in Energy Systems”." Energies 12, no. 15 (2019): 3017. http://dx.doi.org/10.3390/en12153017.

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The editor of this special issue on “Intelligent Control in Energy Systems” have made an attempt to publish a book containing original technical articles addressing various elements of intelligent control in energy systems. The response to our call had 60 submissions, of which 27 were published submissions and 33 were rejections. This book contains 27 technical articles and one editorial. All have been written by authors from 15 countries (China, Netherlands, Spain, Tunisia, United States of America, Korea, Brazil, Egypt, Denmark, Indonesia, Oman, Canada, Algeria, Mexico, and Czech Republic),
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Tietieriev, Vitalii. "Smart Grid Integration for Sustainable City Energy Management: A Paradigm Shift in Power Distribution Networks." Lighting Engineering & Power Engineering 62, no. 1 (2023): 1–11. http://dx.doi.org/10.33042/2079-424x.2023.62.1.01.

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This study focuses on the investigation of collective intelligent systems in the context of energy management in modern distribution networks. The main objective of the research is to explore the potential of utilizing collective intelligent systems for achieving sustainable and efficient energy management in cities. The study describes the concept of collective intelligent systems and their role in distribution networks. The research findings emphasize the importance of employing such systems for achieving optimal resource allocation, enhancing energy consumption efficiency, and promoting sus
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Dissertations / Theses on the topic "Intelligent energy management systems"

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Ma, Yingnan. "Intelligent energy management system : techniques and methods." Thesis, City University London, 2011. http://openaccess.city.ac.uk/1212/.

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ABSTRACT Our environment is an asset to be managed carefully and is not an expendable resource to be taken for granted. The main original contribution of this thesis is in formulating intelligent techniques and simulating case studies to demonstrate the significance of the present approach for achieving a low carbon economy. Energy boosts crop production, drives industry and increases employment. Wise energy use is the first step to ensuring sustainable energy for present and future generations. Energy services are essential for meeting internationally agreed development goals. Energy manageme
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Ali, Sadaqat. "Energy management of multi-source DC microgrid systems for residential applications." Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0159.

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Comparé au réseau électrique alternatif (AC), le réseau électrique en courant continu (DC) a démontré de nombreux avantages tels que son interface naturelle avec les RES, les systèmes de stockage d'énergie et les charges en courant continu, une efficacité supérieure avec moins d'étapes de conversion, et un contrôle plus simple sans effet de peau et sans considérations sur le flux de puissance réactive. Le micro-réseaux DC reste une technologie relativement nouvelle, et ses architectures de réseau, stratégies de contrôle, techniques de stabilisation méritent d'énormes efforts de recherche. Dans
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Miao, Hanjin. "Intelligent system methods for energy management system and sequence-of-events recorder information analysis /." Thesis, Connect to this title online; UW restricted, 1996. http://hdl.handle.net/1773/6133.

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Yang, Cheng. "Development of Intelligent Energy Management System Using Natural Computing." University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1341375203.

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Yang, Rui. "Development of Integrated Building Control Systems for Energy and Comfort Management in Intelligent Buildings." University of Toledo / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1384447299.

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Gonçalves, Diogo Antunes. "Energy management systems based on adaptive surrogate modelling." Doctoral thesis, Universidade de Aveiro, 2017. http://hdl.handle.net/10773/23559.

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Doutoramento em Sistemas Energéticos e Alterações Climáticas<br>Estima-se que o sector dos edifícios seja responsável por cerca de 40% da totalidade de energia consumida na União Europeia e Estados Unidos da América. 50% dessa energia está alocada a sistemas de aquecimento, ventilação e ar-condicionado (AVAC), dos quais 20% estimam-se ser desperdiçados devido a ineficiência na gestão de energia. Considera-se pertinente focar-se no melhoramento da eficiência energética do edificado, reduzindo o desperdício de forma a evitar a escassez de recursos fósseis, bem como para mitigar os problema
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Natsheh, Emad Maher. "Hybrid power systems energy management based on artificial intelligence." Thesis, Manchester Metropolitan University, 2013. http://e-space.mmu.ac.uk/314015/.

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This thesis presents a novel adaptive scheme for energy management in stand-alone hybrid power systems. The proposed management system is designed to manage the power flow between the hybrid power system and energy storage elements in order to satisfy the load requirements based on artificial neural network (ANN) and fuzzy logic controllers.  The neural network controller is employed to achieve the maximum power point (MPP) for different types of photovoltaic (PV) panels, based on Levenberg Marquardt learning algorithm. The statistical analysis of the results indicates that the R2 value for t
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Jose, Panangat James. "Simulation Validation with Real Measurements of an Intelligent Home Energy Management System." Thesis, Högskolan Dalarna, Energiteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:du-37214.

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This thesis's main objective is to conduct a comparison study between measured values and simulated results of a demonstrator, of the intelligent home energy management (iHEM) project. The comparison helps to validate the simulation. TRNSYS software is used for the design. In this study, only the thermal energy side of the project is considered. In which system-level (both domestic hot water (DHW), space heating (SH)) and component level (solar collector, gas boiler) are considered as the parameters to compare. An attempt is made to optimize both system-level and component-level simulation out
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Brka, Adel. "Optimisation of stand-alone hydrogen-based renewable energy systems using intelligent techniques." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2015. https://ro.ecu.edu.au/theses/1756.

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Wind and solar irradiance are promising renewable alternatives to fossil fuels due to their availability and topological advantages for local power generation. However, their intermittent and unpredictable nature limits their integration into energy markets. Fortunately, these disadvantages can be partially overcome by using them in combination with energy storage and back-up units. However, the increased complexity of such systems relative to single energy systems makes an optimal sizing method and appropriate Power Management Strategy (PMS) research priorities. This thesis contributes to the
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Ming-Chieh, Chen. "An Intelligent Lead Acid Battery Management System for Solar and Off-Peak Energy Storage." University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1333393743.

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Books on the topic "Intelligent energy management systems"

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Khan, Baseem, Sanjeevikumar Padmanaban, Hassan Haes Alhelou, Om Prakash Mahela, and S. Rajkumar. Artificial Intelligence-Based Energy Management Systems for Smart Microgrids. CRC Press, 2022. http://dx.doi.org/10.1201/b22884.

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Kostas, Metaxiotis, ed. Intelligent information systems and knowledge management for energy: Applications for decision support, usage, and environmental protection. Information Science Reference, 2010.

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Dam, Koen H. Agent-Based Modelling of Socio-Technical Systems. Springer Netherlands, 2013.

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Chmielowski, Wojciech Z. Management of Complex Multi-reservoir Water Distribution Systems using Advanced Control Theoretic Tools and Techniques. Springer International Publishing, 2013.

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Palensky, Peter, Miloš Cvetković, and Tamás Keviczky, eds. Intelligent Integrated Energy Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00057-8.

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Rigatos, Gerasimos. Intelligent Renewable Energy Systems. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39156-4.

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Aris, Dimeas, Tomtsi Thomai, Weidlich Anke, and SpringerLink (Online service), eds. Energy-Efficient Computing and Networking: First International Conference, E-Energy 2010, Athens, Greece, October 14-15, 2010, Revised Selected Papers. Springer Berlin Heidelberg, 2011.

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Shorif Uddin, Mohammad, Avdhesh Sharma, Kusum Lata Agarwal, and Mukesh Saraswat, eds. Intelligent Energy Management Technologies. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8820-4.

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Li, Kang. Life System Modeling and Intelligent Computing: International Conference on Life System Modeling and Simulation, LSMS 2010, and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, Wuxi, China, September 17-20, 2010, Proceedings, Part II. Springer Berlin Heidelberg, 2010.

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Casillas, Jorge, Francisco J. Martínez-López, and Juan Manuel Corchado Rodríguez, eds. Management Intelligent Systems. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30864-2.

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Book chapters on the topic "Intelligent energy management systems"

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Delfino, Federico, Mansueto Rossi, Fabio Pampararo, and Luca Barillari. "An Energy Management Platform for Smart Microgrids." In Intelligent Computing Systems. Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49179-9_10.

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Kandpal, Bakul, and Ashu Verma. "Electric vehicle energy management." In Intelligent Control for Modern Transportation Systems. CRC Press, 2023. http://dx.doi.org/10.1201/9781003436089-6.

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de Nijs, Frits, Mathijs M. de Weerdt, and Matthijs T. J. Spaan. "Multi-agent Planning Under Uncertainty for Capacity Management." In Intelligent Integrated Energy Systems. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00057-8_9.

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Rostampour, Vahab, Wicak Ananduta, and Tamás Keviczky. "Distributed Stochastic Thermal Energy Management in Smart Thermal Grids." In Intelligent Integrated Energy Systems. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00057-8_7.

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Abraham, Ajith, and Muhammad Riaz Khan. "Neuro-Fuzzy Paradigms for Intelligent Energy Management." In Innovations in Intelligent Systems. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-39615-4_12.

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Luo, Pan, Muyi Lin, Yong Chen, Li Zhao, and Bin Ma. "Energy Management Strategy for Hybrid Engineering Vehicles with Composite Energy Storage." In Green Intelligent Transportation Systems. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0302-9_15.

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Bosse, Stefan. "Energy Management and Distribution." In Material-Integrated Intelligent Systems - Technology and Applications. Wiley-VCH Verlag GmbH & Co. KGaA, 2017. http://dx.doi.org/10.1002/9783527679249.ch19.

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Cruz May, E., L. J. Ricalde, E. J. R. Atoche, A. Bassam, and E. N. Sanchez. "Forecast and Energy Management of a Microgrid with Renewable Energy Sources Using Artificial Intelligence." In Intelligent Computing Systems. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76261-6_7.

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Hirankitti, Visit. "An Intelligent Meter with Smart Home Ability for Intelligent Energy Management." In Intelligent Sustainable Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8111-3_3.

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Ritu, Ritu. "Concepts for Energy Management in the Evolution of Smart Grids." In Hybrid Intelligent Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27409-1_84.

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Conference papers on the topic "Intelligent energy management systems"

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Romdhani, Sameh, Monia Ben Khader Bouzid, and Rafik Absi. "Intelligent Energy Management Systems in Hybrid Renewable Energy Systems." In 2024 IEEE International Conference on Artificial Intelligence & Green Energy (ICAIGE). IEEE, 2024. https://doi.org/10.1109/icaige62696.2024.10776696.

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V, Raajavarthini, Archana T, Harini R S, and Inbamalar T M. "Intelligent Water Management System in Agricuture." In 2024 10th International Conference on Electrical Energy Systems (ICEES). IEEE, 2024. https://doi.org/10.1109/icees61253.2024.10776864.

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P, Rajakumar, K. Suresh, Gokul, Sivaram B. G, Shivaganesh S, and Uthama Raja M. "An Artificially Intelligent Battery Management System." In 2024 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS). IEEE, 2024. https://doi.org/10.1109/icpects62210.2024.10780298.

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Kanase, Digvijay B., Sachin P. Jadhav, Dushyant P. Patil, Shashikant Prasad, Swaraj Kadam, and Digambar P. Patil. "Energy Management Using Smart Inverter." In 2024 International Conference on Intelligent Systems and Advanced Applications (ICISAA). IEEE, 2024. https://doi.org/10.1109/icisaa62385.2024.10828712.

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S, Kiruppazhini, Krishnapriya K, Shrimukhi S, and Meera S. "Smart Park – An Intelligent Parking Management System." In 2024 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS). IEEE, 2024. https://doi.org/10.1109/icpects62210.2024.10780335.

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Karamsetty, Shouryadhar, Saif O. Husain, Thota Soujanya, S. Trisheela, and Abbas Hameed Abdul Hussein. "Adaptive Energy Management Strategies for Hybrid Energy Systems Using Multi Object Grey Wolf Optimization." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721993.

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Nanda, Simranjeet, Maddu Naveen Kumar, Paramjit Baxi, Monoo John, Manaswini R, and Dhananjay Kumar Yadav. "Intelligent Energy Management System for Microgrids with Energy Storage Integration." In 2025 International Conference on Automation and Computation (AUTOCOM). IEEE, 2025. https://doi.org/10.1109/autocom64127.2025.10957276.

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Pour, Reza Abbas, Morris Brenna, Alessandro Saldarini, Dario Zaninelli, Michela Longo, and Seyedmahdi Miraftabzadeh. "Development of Intelligent Models for Building Energy Management." In 2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). IEEE, 2024. http://dx.doi.org/10.1109/eeeic/icpseurope61470.2024.10751373.

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Siddula, Sundeep. "Efficiency Enhancement of Electric Vehicles with ANFIS-Based Energy Management." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721691.

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Aya, Benkhada, Obayd Merouane, Farajy Nouhaila, and Ouabida Elhoussaine. "Intelligent Control Systems for Power and Energy Management in Smart Buildings." In 2025 5th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET). IEEE, 2025. https://doi.org/10.1109/iraset64571.2025.11008203.

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Reports on the topic "Intelligent energy management systems"

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Miller, Craig, and Robert Larmouth. Energy Sector Security through a System for Intelligent, Learning Network Configuration Monitoring and Management (“Essence”). Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1360111.

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Tayeb, Shahab. Intelligent Blind Crossings for Suburban and Rural Intersections. Mineta Transportation Institute, 2025. https://doi.org/10.31979/mti.2024.2351.

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Blind intersections in suburban and rural areas pose significant safety challenges due to limited visibility and inadequate infrastructure. This project proposes an innovative solution leveraging the Internet of Vehicles (IoV) paradigm, utilizing connected and autonomous vehicles (CAVs) for seamless communication to enhance safety at these intersections. The research focuses on developing a specialized Road-Side Unit (RSU) system equipped with a Virtual Traffic Light Algorithm implemented on a Field-Programmable Gate Array (FPGA). Key stakeholders, including transportation authorities, vehicle
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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 ne
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Balali, Vahid. System-of-Systems Integration for Civil Infrastructures Resiliency Toward MultiHazard Events. Mineta Transportation Institute, 2023. http://dx.doi.org/10.31979/mti.2023.2245.

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Civil infrastructure systems—facilities that supply principal services, such as electricity, water, transportation, etc., to a community—are the backbone of modern society. These systems are frequently subject to multi-hazard events, such as earthquakes. The poor resiliency of these infrastructures results in many human casualties and significant economic losses every year. An outline of a holistic view that considers how different civil infrastructure systems operate independently and how they interact and communicate with each other is required to have a resilient infrastructure system. More
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Garrett, R. G., and A. G. Fabbri. Introduction, Intelligent information management: knowledge-based systems. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1994. http://dx.doi.org/10.4095/193922.

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Vermeychuk, Theodore J. Downstream Benefits of Energy Management Systems. Defense Technical Information Center, 2015. http://dx.doi.org/10.21236/ad1009321.

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Murray, William R. Control for Intelligent Tutoring Systems: A Comparison of Blackboard Architectures and Discourse Management Networks. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada201534.

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Tom Addison and Andrew Stanbury. Power Contro Energy Management and Market Systems. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/877380.

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Dean, Jesse, and James Dice. Energy Management Information Systems Technical Resources Report. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1806555.

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Rakutko, S. A., E. N. Rakutko, and N. Yu Ivannikova. OPTIMIZATION AND MANAGEMENT OF ENERGY SAVING IN AGRICULTURAL ENERGY SYSTEMS. ЭЛЕКТРООБОРУДОВАНИЕ: ЭКСПЛУАТАЦИЯ И РЕМОНТ, 2018. http://dx.doi.org/10.18411/0131-5226-2018-11984.

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