[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119988-en":3,"doc-seo-119988-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119988,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","Advancing energy efficiency - harnessing machine learning for smart grid management","Smart grids (SG) are presented as a response to inefficiencies, reliability problems, and instability in traditional power systems. The integration of information communication and automation with legacy electrical infrastructure improves efficiency, reliability, and sustainability, while enabling renewable generation and data-driven optimization of energy distribution and consumption. Machine learning supports consumption prediction, optimization, anomaly detection, and fault diagnosis. The work reviews deep learning, reinforcement learning, and IoT integration for energy management, highlighting the promise of deep CNNs and the need to address model complexity and data requirements.","Advancing energy efficiency: harnessing machine learning for smart grid management  \nNSh Babanazarov1*, A I Matkarimov1, and IS Ilyasov 1  \n1Turkmen state institute of economics and management, Ashgabat, Turkmenistan  \nAbstract. The concept of Smart Grids (SG) has emerged as a solution to address challenges in traditional power systems, including resource inefficiency, reliability issues, and instability. Since its inception in the early 21st century, Smart Grid technology has undergone significant development, integrating advanced information communication and automation technologies with conventional power infrastructure. This integration enhances efficiency, reliability, and sustainability, while enabling the integration of renewable energy sources and optimizing energy distribution and consumption. Machine learning algorithms play a pivotal role in the development of Smart Grids, facilitating energy consumption prediction, optimization, anomaly detection, and fault diagnosis. This paper explores methodologies for developing and improving machine learning algorithms for efficient energy consumption prediction and management within Smart Grids. It discusses the application of deep learning techniques, reinforcement learning, and integration with the Internet of Things (IoT) to enhance energy management systems. The study highlights the potential impact of deep convolutional neural networks (CNNs) on energy consumption regulation and emphasizes the need for further research to address challenges associated with model complexity and data requirements in Smart Grid  \ncontexts.  \n1 Introduction  \nThe concept of smart grids, or Smart Grids (SG), stems from the need to address the challenges faced by traditional power systems, such as inefficient resource utilization, insufficient reliability and instability. The first mentions of this concept appeared in the early 21st century, and since then it has been actively developing, attracting considerable attention from energy researchers and developers around the world.  \nThis direction in energy engineering has become the subject of in-depth analytical research and practical developments aimed at creating intelligent power grid management systems. One of the key features of smart grids is the integration of advanced information communication and automation technologies with traditional power supply infrastructure. This results in improved efficiency, reliability and sustainability of energy systems. In addition, smart grids facilitate the integration of renewable energy sources, optimize load  \n* [Corresponding author: ](Corresponding author: narly233@gmail.com)[narly233@gmail.com](Corresponding author: narly233@gmail.com)  \n© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 ([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)).  \ndistribution and manage energy consumption based on data and analytics. Pilot projects and commercial solutions based on smart grids are being actively implemented to ensure sustainable and efficient operation of energy infrastructure.  \nThe first definition of the SG concept in the energy sector cannot be clearly attributed toa specific person or source, as the idea of smart grids for electricity supply emerged gradually and evolved over several decades. However, it is possible to identify a number of organizations, scientists, and engineers who have made significant contributions to shaping the concept. For example, some of the earliest mentions of the smart grid concept can be found in documents and publications from organizations such as the Electric Power Research Institute (EPRI), the Institute of Electrical and Electronics Engineers (IEEE), and in the works of prominent energy professionals, including professors and engineers who have studied automation, power system control, and grid technology development.  \nIn t","cbCaitLBPfIzgTTU","https://ap.wps.com/l/cbCaitLBPfIzgTTU","pdf",2104547,1,7,"English","en",105,"# Introduction\n## Motivation and concept of smart grids\n## Role of machine learning in smart grid management\n## Related work and algorithms\n## Classification of smart grid solutions","[{\"question\":\"Why are smart grids needed compared with traditional power systems?\",\"answer\":\"Smart grids address inefficient resource utilization, insufficient reliability, and instability in conventional power networks.\"},{\"question\":\"How does machine learning contribute to smart grid energy management?\",\"answer\":\"Machine learning enables energy consumption prediction, optimization, anomaly detection, and fault diagnosis to improve control of grid operation.\"},{\"question\":\"Which advanced AI approaches and integrations are discussed for improving energy management?\",\"answer\":\"The paper discusses deep learning, reinforcement learning, and integration with the Internet of Things (IoT) to enhance energy management systems.\"}]","Advancing energy efficiency - harnessing machine learning for smart grid management | PDF",1785727513,18,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"advancing-energy-efficiency-harnessing-machine-learning-for-smart-grid-management","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/advancing-energy-efficiency-harnessing-machine-learning-for-smart-grid-management/119988/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why are smart grids needed compared with traditional power systems?","Question",{"text":75,"@type":76},"Smart grids address inefficient resource utilization, insufficient reliability, and instability in conventional power networks.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does machine learning contribute to smart grid energy management?",{"text":80,"@type":76},"Machine learning enables energy consumption prediction, optimization, anomaly detection, and fault diagnosis to improve control of grid operation.",{"name":82,"@type":73,"acceptedAnswer":83},"Which advanced AI approaches and integrations are discussed for improving energy management?",{"text":84,"@type":76},"The paper discusses deep learning, reinforcement learning, and integration with the Internet of Things (IoT) to enhance energy management systems.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]