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Journal articles on the topic 'Intelligent energy management systems'

Author: Grafiati

Published: 7 September 2021

Last updated: 29 July 2025

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1

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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Liu, Wei. "Energy Project Management with Artificial Intelligence." International Journal of Electric Power and Energy Studies 2, no. 2 (2024): 10–16. http://dx.doi.org/10.62051/ijepes.v2n2.02.

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The integration of artificial intelligence (AI) technology into energy project management has emerged as a significant trend. This paper presents an extensive review and analysis of AI applications in this domain, emphasizing areas such as data analysis and prediction, intelligent optimization, risk management, and decision support systems. We systematically review the current literature, highlighting the critical role of AI in enhancing energy project management. Our discussion encompasses existing research outcomes and future development trajectories, aiming to furnish valuable insights and

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El-Zonkoly, Amany. "Intelligent energy management of optimally located renewable energy systems incorporating PHEV." Energy Conversion and Management 84 (August 2014): 427–35. http://dx.doi.org/10.1016/j.enconman.2014.04.050.

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Poplavskyi, Oleksandr. "Modern methods of risk management in Ukrainian energy markets." Management of Development of Complex Systems, no. 58 (June 28, 2024): 162–68. http://dx.doi.org/10.32347/2412-9933.2024.58.162-168.

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In the context of rapid technological development and increasing instability on global markets, the issue of developing effective risk management methods on Ukrainian energy markets becomes particularly important. Modern risk management methods include the use of machine learning algorithms to predict and minimize potential threats. This study focuses on the implementation of innovative machine learning and artificial intelligence technologies to anticipate risks in energy markets and respond timely to potential stresses. This paper explores the development of intelligent risk management syste

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Gong, Hesen. "The Analysis of the Application of Intelligent Energy Management System Based on BIM Technology." Applied and Computational Engineering 127, no. 1 (2025): 229–35. https://doi.org/10.54254/2755-2721/2025.20192.

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With the increase in building scale and complexity, traditional energy management methods are difficult to meet the requirements of modern buildings for energy conservation, efficiency and sustainability. Based on BIM (Building Information Modeling) technology and intelligent energy management systems, this paper explores ways to improve the accuracy and effectiveness of building energy management using data collection, energy consumption prediction, optimal control and 3D visualisation. This study also analyses the systematic integration of Internet of Things (IoT) and Artificial Intelligence

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Vemuri, Ratna kumari, Chinni Bala Vijaya Durga, Syed Abuthahir Syed Ibrahim, Nagaraju Arumalla, Senthilvadivu Subramanian, and Lakshmi Bhukya. "Intelligent-of-things multiagent system for smart home energy monitoring." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 3 (2024): 1858. http://dx.doi.org/10.11591/ijeecs.v34.i3.pp1858-1867.

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The proliferation of IoT devices has ushered in a new era of smart homes, where efficient energy management is a paramount concern. Multiagent artificial intelligence-of-things (MAIoT) has emerged as a promising approach to address the complex challenges of smart home energy management. This research study examines MAIoT's components, functioning, benefits, and drawbacks. MAIoT systems improve energy efficiency and user comfort by combining multiagent systems and IoT devices. However, privacy, security, interoperability, scalability, and user acceptability must be addressed. As technology adva

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Vemuri, Ratna kumari, Chinni Bala Vijaya Durga, Syed Abuthahir Syed Ibrahim, Nagaraju Arumalla, Senthilvadivu Subramanian, and Lakshmi Bhukya. "Intelligent-of-things multiagent system for smart home energy monitoring." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 3 (2024): 1858–67. https://doi.org/10.11591/ijeecs.v34.i3.pp1858-1867.

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The proliferation of IoT devices has ushered in a new era of smart homes, where efficient energy management is a paramount concern. Multiagent artificial intelligence-of-things (MAIoT) has emerged as a promising approach to address the complex challenges of smart home energy management. This research study examines MAIoT's components, functioning, benefits, and drawbacks. MAIoT systems improve energy efficiency and user comfort by combining multiagent systems and IoT devices. However, privacy, security, interoperability, scalability, and user acceptability must be addressed. As technology adva

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Bo-Wei Zhou, Bo-Wei Zhou, Yong Huang Bo-Wei Zhou, Bin Jiang Yong Huang, and Fei Geng Bin Jiang. "Optimization of Ship Power Supply Network and Intelligent Energy Management Strategy Under Multiple Energy Modes." 電腦學刊 35, no. 1 (2024): 217–25. http://dx.doi.org/10.53106/199115992024023501017.

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<p>Purpose: This article aims to address the issues of incomplete management models and slow convergence speed of optimization models in energy management in ship multi energy systems, and to construct a comprehensive dynamic optimization objective model. Method: Firstly, establish an optimization design model with the objective functions of energy storage system cost, grid power fluctuation smoothing, and energy supply and demand balance; Then, in the optimization process of the objective function, a bus voltage coordination control strategy is adopted, and for the parameter optimizatio

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18

Gupta, Richa. "Decision Support Systems for IoT Based Infrastructures." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 9, no. 3 (2018): 1074–81. http://dx.doi.org/10.17762/turcomat.v9i3.13896.

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Computation offloading divides enormous computational tasks across numerous computer resources, circumventing hardware limits. Edge computing can employ vast quantities of data, individual preferences, and clever algorithms by offloading smart models to high-performance cloud servers. We propose a getaway-centric IoT system to enable intelligent and autonomous IoT devices at the computer infrastructure's edge. Edge computing manages IoT devices by selecting and applying the best control factor from a pool of intelligent services. The cloud-based intelligent service engine provides intelligent

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19

Jing, Zhijun, Xingying Chen, Le Bu, et al. "Intelligent optimization for building energy management considering indoor heat transfer." Innovation Energy 1, no. 4 (2024): 100058. http://dx.doi.org/10.59717/j.xinn-energy.2024.100058.

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<p>To achieve green and low-carbon goals in the building energy sector, precise energy management strategies are essential to support user comfort and energy-saving needs during operation. However, the thermal comfort requirements of building users may conflict with societal demands for low-carbon and energy efficiency. This creates a challenge between the precision of energy use models and the speed of energy management strategies. It is necessary to combine the advantages of building physical models and deep reinforcement learning to develop faster and more accurate energy management s

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20

Mai, Hailin. "Research on Optimisation Methods of Intelligent Building Energy Management System." Transactions on Engineering and Technology Research 4 (December 20, 2024): 18–23. https://doi.org/10.62051/4j9n1n21.

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In recent years, the development of smart building management has gained significant momentum, driven by the increasing need for sustainable development and efficient resource utilization. This demand has led to advancements in technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), and Supervisory Control and Data Acquisition (SCADA) systems. This paper explores the optimisation methods for Intelligent Building Energy Management System (IBEMS) with a focus on the integration of IoT, AI, and SCADA systems. The study begins by defining IBEMS and its components, highligh

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21

Kazembe, Mangani Daudi. "Intelligent Transport Systems." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (2022): 488–92. http://dx.doi.org/10.22214/ijraset.2022.45271.

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Abstract: Growing economic activities aand others are among the factors that make many cities busy places today especially in traffic systems. Road networks that seem to be spacious sometimes become completely congested so much so that traffic mobility looks standstill. This impacts negatively on traffic users resources in terms of time management, fuel and other resource. This paper discusses the background trend in traffic activities amid congestion environment and proposes an Intelligent Traffic System that uses Machine Learning technique of predictive classification and regression to help

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22

Babu, Dr A. Mahesh, Barapati Akhil, and Naveen Kumar Pochampally. "Smart Cities and Intelligent Transport Systems." International Journal of Applied and Structural Mechanics, no. 31 (January 28, 2023): 22–25. http://dx.doi.org/10.55529/ijasm.31.22.25.

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The integration of technology into cities and transportation networks has the potential to improve the quality of life for residents, reduce congestion and pollution, and increase the overall efficiency of urban cities and their transportation system. Smart cities use technology to improve the efficiency and sustainability of urban areas. This can include things like smart lighting, the internet of things (IoT), energy management, artificial intelligence and smart transportation systems. An intelligent transport system is a component of a smart city that uses technology, to improve the efficie

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Melnychuk, H. "ENERGY MANAGEMENT OF SETTLEMENTS AND TERRITORIES BASED ON INTELLIGENT POWER MANAGEMENT SYSTEMS." POWER ENGINEERING: economics, technique, ecology, no. 4 (March 5, 2020): 88–98. http://dx.doi.org/10.20535/1813-5420.4.2019.200503.

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Singh, Prashant Kumar. "Volt Vision." International Journal for Research in Applied Science and Engineering Technology 13, no. 6 (2025): 1330–35. https://doi.org/10.22214/ijraset.2025.72388.

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Since the world is consuming more power and now it is much worried about sustainability, it is necessary to use intelligence in controlling and monitoring electricity. With a combination of intelligent automation and Internet of Things (IoT), we can monitor energy consumption in real time, automate the control systems, and make better use of energy. Since the world is consuming more power and now it is much worried about sustainability, it is necessary to use intelligence in controlling and monitoring electricity. With a combination of intelligent automation and Internet of Things (IoT), we ca

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Zhadaev, Dmitriy. "MODELS AND FUNCTIONS OF AN INTELLIGENT SYSTEM FOR SUPPORTING MANAGEMENT DECISIONS IN ENERGY SYSTEMS." Automation and modeling in design and management 2023, no. 4 (2023): 55–63. http://dx.doi.org/10.30987/2658-6436-2023-4-55-63.

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The aim of the work is to study models and intelligent systems for supporting management decisions in energy systems. The article is devoted to solving the problem of adequate description of systems for supporting management decision-making in energy systems, as well as analysing models and functions of intelligent system models for supporting management decision-making in energy systems. As part of the research, methods of generalization and systematization of models, functions of an intelligent management decision support system, as well as systemic, evolutionary, categorical and modelling m

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Elkazaz, Mahmoud H., Ayman Hoballah, and Ahmed M. Azmy. "Artificial intelligent-based optimization of automated home energy management systems." International Transactions on Electrical Energy Systems 26, no. 9 (2016): 2038–56. http://dx.doi.org/10.1002/etep.2195.

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Shingo, Prothick Kumar, Md Ijaj Ahmed, Pranto Das, and Rathujan Vijayanathan. "Advanced Computer Technologies in Enhancing New Energy Vehicles." European Journal of Theoretical and Applied Sciences 2, no. 6 (2024): 35–50. http://dx.doi.org/10.59324/ejtas.2024.2(6).02.

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The development of the new energy vehicle (NEV) industry is rapid, which has greatly promoted the progress of automotive technology through computer systems. In this paper, the potential nuclear effects of computer technology on NEVs are explored. This report analyses the development and comparative analysis of five key areas: Battery Management Systems (BMS), Charging Management Systems (CMS), autonomous driving technology, fault diagnosis systems, and intelligent control mechanisms. Utilising sophisticated algorithms, artificial intelligence (AI), machine learning and big data analytics allo

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Prothick, Kumar Shingo, Ijaj Ahmed Md, Das Pranto, and Vijayanathan Rathujan. "Advanced Computer Technologies in Enhancing New Energy Vehicles." European Journal of Theoretical and Applied Sciences 2, no. 6 (2024): 35–50. https://doi.org/10.59324/ejtas.2024.2(6).02.

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The development of the new energy vehicle (NEV) industry is rapid, which has greatly promoted the progress of automotive technology through computer systems. In this paper, the potential nuclear effects of computer technology on NEVs are explored. This report analyses the development and comparative analysis of five key areas: Battery Management Systems (BMS), Charging Management Systems (CMS), autonomous driving technology, fault diagnosis systems, and intelligent control mechanisms. Utilising sophisticated algorithms, artificial intelligence (AI), machine learning and big data analytics allo

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Hamed, Musa Abdullah, Esam Taha Yassin Hussein, and Wesam Mohammed Jasim Abd. "A survey of intelligent energy management based on learning heuristic." Indonesian Journal of Electrical Engineering and Computer Science 30, no. 2 (2023): 1242. http://dx.doi.org/10.11591/ijeecs.v30.i2.pp1242-1249.

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Human activities are dependent on energy and lifestyles that important provide services on a daily basis. Currently, polluting and energy consumption worldwide is dominated by sources non-renewable, for instance fossil fuels. Due to their environmental impact, research and investment have increased in alternative and renewable energy sources, such as photovoltaic and wind energy. Buildings use energy management systems to monitor real-time consumption and plan the operation of appliances so that the energy bill is minimized or based on other factors. The purpose of energy management systems in

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Musa, Abdullah Hameed, Taha Yassin Hussein Essam, and Mohammed Jasim Abd Wesam. "A survey of intelligent energy management based on learning heuristic." A survey of intelligent energy management based on learning heuristic 30, no. 2 (2023): 1242–49. https://doi.org/10.11591/ijeecs.v30.i2.pp1242-1249.

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Human activities are dependent on energy and lifestyles that important provide services on a daily basis. Currently, polluting and energy consumption worldwide is dominated by sources non-renewable, for instance fossil fuels. Due to their environmental impact, research and investment have increased in alternative and renewable energy sources, such as photovoltaic and wind energy. Buildings use energy management systems to monitor real-time consumption and plan the operation of appliances so that the energy bill is minimized or based on other factors. The purpose of energy management systems in

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31

FOIDAȘ, Andrei-Daniel, and Stefan GHEORGHE. "THE ROLE OF ARTIFICIAL INTELLIGENCE ON POWER QUALITY MANAGEMENT – POWER QUALITY INDICATORS." EMERG - Energy. Environment. Efficiency. Resources. Globalization 11, no. 2 (2025): 26–50. https://doi.org/10.37410//emerg.2025.2.02.

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Abstract: The paper examines artificial intelligence (AI) functions in power quality (PQ) management of modern power systems. AI provides real-time monitoring capabilities and instant PQ disturbance identification and response functions. AI integration enhances both reliability and efficiency while facilitating the shift toward sustainable intelligent energy systems. The established grid stability together with operational efficiency, cost savings and environmental benefits represent the advantages of this system. The paper examines upcoming obstacles and patterns in AI technologies which will

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Thow Yick, Liang. "Nurturing intelligent human systems: the nonlinear perspective of the human minds*." Human Systems Management 20, no. 4 (2001): 281–89. http://dx.doi.org/10.3233/hsm-2001-20401.

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Organizing around intrinsic intelligence is a new paradigm that all human organizations must adopt if they wish to evolve successfully in the emerging intelligence revolution. This fresh mindset perceives human systems as intelligent corporate beings possessing an orgmind and a collective intelligence of their own. Intelligence is the entity that drives the universe and its microcosms. Some attributes associated with human intelligence are mindfulness, information processing, knowledge structuring, and nonlinearity. Nonlinearity, in particular, is manifested because the inherent sources of int

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Sommavilla, J. "EnExpert’s intelligent energy solutions: EMS and CMS." QualEnergia Science, no. 1 (2025): 137. https://doi.org/10.63111/qes-2025.1.0017.

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As the demand for sustainable and efficient energy grows, EnExpert leads with its innovative Energy Management System (EMS) and Carbon Management System (CMS). These solutions optimize energy use and sustainability, making them essential for modern businesses. Energy Management Systems (EMS). EnExpert’s EMS helps companies monitor, control, and optimize energy consumption. By providing real-time data and advanced analytics, EMS reduces energy waste, lowers costs, and improves sustainability. It also integrates renewable energy sources like solar and wind, helping companies transition to greene

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Novita, Nanda, Nurul Khairina, Suendri ., Amir Saleh, and Fadhillah Azmi. "Fuzzy Logic Controller Design for Intelligent Lighting and Air-Conditioning Management Systems." International Journal of Innovative Research in Computer Science and Technology 12, no. 3 (2024): 81–86. http://dx.doi.org/10.55524/ijircst.2024.12.3.13.

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In an effort to conserve energy and optimize the use of resources, this research explores the application of fuzzy logic control techniques to improve energy efficiency in intelligent lighting and air conditioning (AC) management systems. This research aims to investigate how fuzzy logic control strategies can be incorporated into intelligent systems to regulate lighting and air conditioning operations with greater precision, adaptability, and energy efficiency. By utilizing a fuzzy logic algorithm, this research develops a model that is able to dynamically adjust lighting levels and AC settin

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Nikita Shivaji, More. "Intelligent library management system." Trends in Computer Science and Information Technology 9, no. 1 (2024): 001–9. http://dx.doi.org/10.17352/tcsit.000074.

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A library is a collection of sources of information and similar other resources. The emergence of Intelligent Library Management Systems (ILMS) is a key trend in library automation. In libraries, the management of the book is a very complicated and time-consuming process. A Library includes books, question papers, newspaper journals, and previous year’s project details, etc. The integration of emerging technologies beyond RFID in academic libraries. The introduction lays the groundwork for exploring innovative solutions such as AI, machine learning, and data analytics, aiming to optimize libra

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Liu, Siqi, Zhiyuan Xie, and Zhengwei Hu. "Research on Distributed Smart Home Energy Management Strategies Based on Non-Intrusive Load Monitoring (NILM)." Electronics 14, no. 9 (2025): 1719. https://doi.org/10.3390/electronics14091719.

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Home energy optimization management improves energy utilization efficiency and reduces electricity costs through intelligent load control, strategic utilization of time-of-use pricing, and optimized integration of energy storage and distributed energy systems. Simultaneously, it enhances energy autonomy, lowers carbon emissions, and promotes sustainable low-carbon lifestyles. By coordinating demand response programs with flexible load scheduling strategies, this approach effectively reduces peak loads and improves grid stability, thereby advancing smart grid development. This paper investigate

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Fayyazi, Mojgan, Paramjotsingh Sardar, Sumit Infent Thomas, et al. "Artificial Intelligence/Machine Learning in Energy Management Systems, Control, and Optimization of Hydrogen Fuel Cell Vehicles." Sustainability 15, no. 6 (2023): 5249. http://dx.doi.org/10.3390/su15065249.

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Environmental emissions, global warming, and energy-related concerns have accelerated the advancements in conventional vehicles that primarily use internal combustion engines. Among the existing technologies, hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles may have minimal contributions to greenhouse gas emissions and thus are the prime choices for environmental concerns. However, energy management in fuel cell electric vehicles and fuel cell hybrid electric vehicles is a major challenge. Appropriate control strategies should be used for effective energy management

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Safiullin, Ravil, Aleksandr Marusin, Ruslan Safiullin, and Timur Ablyazov. "Methodical approaches for creation of intelligent management information systems by means of energy resources of technical facilities." E3S Web of Conferences 140 (2019): 10008. http://dx.doi.org/10.1051/e3sconf/201914010008.

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As part of the development of the digital economy both abroad and in the Russian Federation, the management of energy resources based on the use of digital technologies is one of the key tasks in improving infrastructure in order to ensure the efficient functioning of technical facilities providing the operation of capital construction projects. Currently, the spread of information and communication technologies is the basis for the development of intelligent management information systems for energy resources, which requires further theoretical and practical studies and the development of con

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Cao, Yongsheng, Caiping Zhao, and Demin Li. "Carbon Management for Intelligent Community with Combined Heat and Power Systems." Sustainability 15, no. 17 (2023): 13257. http://dx.doi.org/10.3390/su151713257.

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In recent years, solar power technology and energy storage technology have advanced, leading to the increased use of solar power devices and energy storage systems in residential areas. Carbon management has become an important method to help the community manager guide energy consumption in a timely manner, effectively reduce the carbon emissions of the community, and reduce the substantial harm to the environment. This paper aims to study the issue of carbon management and resource allocation in an intelligent community with combined heat and power (CHP) systems and solar power. The presence

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Atanasov, Ivaylo, Anastas Nikolov, and Evelina Pencheva. "Reducing Energy Consumption by Using Smart Metering Intelligent Systems." Cybernetics and Information Technologies 16, no. 2 (2016): 113–24. http://dx.doi.org/10.1515/cait-2016-0024.

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Abstract Smart metering is aimed at efficient energy management. Its potential may be revealed using recent advances in machine type communications. This paper presents an approach to design web services for residential power control with prepaid functionality. The reduction in energy consumption is estimated for typical households applying heating control.

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Casteleiro-Roca, José-Luis, José Gómez-González, José Calvo-Rolle, et al. "Short-Term Energy Demand Forecast in Hotels Using Hybrid Intelligent Modeling." Sensors 19, no. 11 (2019): 2485. http://dx.doi.org/10.3390/s19112485.

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The hotel industry is an important energy consumer that needs efficient energy management methods to guarantee its performance and sustainability. The new role of hotels as prosumers increases the difficulty in the design of these methods. Also, the scenery is more complex as renewable energy systems are present in the hotel energy mix. The performance of energy management systems greatly depends on the use of reliable predictions for energy load. This paper presents a new methodology to predict energy load in a hotel based on intelligent techniques. The model proposed is based on a hybrid int

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Cui, Jiajun. "Research on human-computer interaction and user experience of smart home system." Applied and Computational Engineering 40, no. 1 (2024): 234–41. http://dx.doi.org/10.54254/2755-2721/40/20230657.

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This article aims to present a perceptive summary of cutting-edge home automation systems, exploring basic topics including human-computer interaction, communication technologies, networking protocols, and the fascinating science underlying the industry's most well-known applicationthe robotic vacuum cleaner. Put succinctly, using intelligent sweeping robots in smart homes signifies a significant advancement in machine autonomy and artificial intelligence. Furthermore, integrating renewable energy and grid management solutions with smart home systems will be fueled by the pursuit of sustainabi

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Al-Saadi, Ziad, Duong Phan Van, Ali Moradi Amani, et al. "Intelligent Driver Assistance and Energy Management Systems of Hybrid Electric Autonomous Vehicles." Sustainability 14, no. 15 (2022): 9378. http://dx.doi.org/10.3390/su14159378.

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Automotive companies continue to develop integrated safety, sustainability, and reliability features that can help mitigate some of the most common driving risks associated with autonomous vehicles (AVs). Hybrid electric vehicles (HEVs) offer practical solutions to use control strategies to cut down fuel usage and emissions. AVs and HEVs are combined to take the advantages of each kind to solve the problem of wasting energy. This paper presents an intelligent driver assistance system, including adaptive cruise control (ACC) and an energy management system (EMS), for HEVs. Our proposed ACC dete

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Wyrzykowska, Barbara, Hubert Szczepaniuk, Edyta Karolina Szczepaniuk, Anna Rytko, and Marzena Kacprzak. "Intelligent Energy Management Systems in Industry 5.0: Cybersecurity Applications in Examples." Energies 17, no. 23 (2024): 5871. http://dx.doi.org/10.3390/en17235871.

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The article examines modern approaches to energy management in the context of the development of Industry 5.0 with a particular focus on cybersecurity. Key tenets of Industry 5.0 are discussed, including the integration of advanced technologies with intelligent energy management systems (IEMSs) and the growing need to protect data in the face of increasing cyber threats. The challenges faced by small and medium-sized enterprises (SMEs) using solutions based on renewable energy sources, such as photovoltaic farms, are also analyzed. The article presents examples of IEMS applications and discuss

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Zamith, Marcelo, Luis Valente, Mark Joselli, José Ricardo Silva Junior, Esteban Clua, and Bruno Feijó. "Exploring Energy Management on GPUs in Game Architectures." Journal on Interactive Systems 5, no. 2 (2014): 1. http://dx.doi.org/10.5753/jis.2014.646.

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CPUs and GPUs have been evolving rapidly over time regarding their capabilities and processing power. This has opened many new possibilities for interactive and real time systems, such as more sophisticated scene realism, more precise and complex artificial intelligence, and better physical simulations. However, these improvements come at a cost: increase of energy consumption. Energy management in interactive and real time architectures have not been receiving much attention over the years, but this issue is likely to become important in the near future due to the increasing energy demand and

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Hamidi, Meryem, Abdelhadi Raihani, and Omar Bouattane. "Sustainable Intelligent Energy Management System for Microgrid Using Multi-Agent Systems: A Case Study." Sustainability 15, no. 16 (2023): 12546. http://dx.doi.org/10.3390/su151612546.

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In this paper, a sustainable, intelligent energy management system for a microgrid based on a multi-agent system (MAS) is studied. The system is designed to address the challenges posed by the intermittence of renewable energy sources. Also, the system optimizes the use of available AC–DC renewable energy sources by utilizing load flexibility and the complementarity of renewable sources. To evaluate the effectiveness of this proposed multi-agent framework, a co-simulation using MATLAB and JADE platforms is conducted for a microgrid connected to the main grid. The results show that the proposed

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Kamali, Saeed, Golrokh Khakzar, and Soolmaz Abdali Hajiabadi. "Effect of Building Management System on Energy Saving." Advanced Materials Research 856 (December 2013): 333–37. http://dx.doi.org/10.4028/www.scientific.net/amr.856.333.

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Without any doubt, one of the most worldwide challenging and controversial issues in the current century is the energy problem. In most countries, the increase of energy consumption, especially in building, has made energy saving and efficiency strategies important target for energy policies. In general, there are many ways to save energy. The most common method of economizing is within culturalization. For such purpose, building energy management system (BEMS) is considered as the latest idea of energy. Having a dynamic environment, smart buildings are affordable by the integration of four ma

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Manic, Milos, Dumidu Wijayasekara, Kasun Amarasinghe, and Juan J. Rodriguez-Andina. "Building Energy Management Systems: The Age of Intelligent and Adaptive Buildings." IEEE Industrial Electronics Magazine 10, no. 1 (2016): 25–39. http://dx.doi.org/10.1109/mie.2015.2513749.

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Palensky, Peter, and Dietmar Dietrich. "Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads." IEEE Transactions on Industrial Informatics 7, no. 3 (2011): 381–88. http://dx.doi.org/10.1109/tii.2011.2158841.

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Collotta, Mario, Yunchuan Sun, Luca Persio, Emad Ebeid, and Riccardo Muradore. "Smart Green Applications: From Renewable Energy Management to Intelligent Transportation Systems." Energies 11, no. 5 (2018): 1317. http://dx.doi.org/10.3390/en11051317.

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