LAPSE:2023.18262
Published Article

LAPSE:2023.18262
A Survey on Energy Efficiency in Smart Homes and Smart Grids
March 7, 2023
Abstract
Empowered by the emergence of novel information and communication technologies (ICTs) such as sensors and high-performance digital communication systems, Europe has adapted its electricity distribution network into a modern infrastructure known as a smart grid (SG). The benefits of this new infrastructure include precise and real-time capacity for measuring and monitoring the different energy-relevant parameters on the various points of the grid and for the remote operation and optimization of distribution. Furthermore, a new user profile is derived from this novel infrastructure, known as a prosumer (a user that can produce and consume energy to/from the grid), who can benefit from the features derived from applying advanced analytics and semantic technologies in the rich amount of big data generated by the different subsystems. However, this novel, highly interconnected infrastructure also presents some significant drawbacks, like those related to information security (IS). We provide a systematic literature survey of the ICT-empowered environments that comprise SGs and homes, and the application of modern artificial intelligence (AI) related technologies with sensor fusion systems and actuators, ensuring energy efficiency in such systems. Furthermore, we outline the current challenges and outlook for this field. These address new developments on microgrids, and data-driven energy efficiency that leads to better knowledge representation and decision-making for smart homes and SGs.
Empowered by the emergence of novel information and communication technologies (ICTs) such as sensors and high-performance digital communication systems, Europe has adapted its electricity distribution network into a modern infrastructure known as a smart grid (SG). The benefits of this new infrastructure include precise and real-time capacity for measuring and monitoring the different energy-relevant parameters on the various points of the grid and for the remote operation and optimization of distribution. Furthermore, a new user profile is derived from this novel infrastructure, known as a prosumer (a user that can produce and consume energy to/from the grid), who can benefit from the features derived from applying advanced analytics and semantic technologies in the rich amount of big data generated by the different subsystems. However, this novel, highly interconnected infrastructure also presents some significant drawbacks, like those related to information security (IS). We provide a systematic literature survey of the ICT-empowered environments that comprise SGs and homes, and the application of modern artificial intelligence (AI) related technologies with sensor fusion systems and actuators, ensuring energy efficiency in such systems. Furthermore, we outline the current challenges and outlook for this field. These address new developments on microgrids, and data-driven energy efficiency that leads to better knowledge representation and decision-making for smart homes and SGs.
Record ID
Keywords
communication, detection, encryption, Energy Efficiency, fraud, knowledge graphs, microgrid, security, semantic technology, smart grid, smart home
Subject
Suggested Citation
Prieto González L, Fensel A, Gómez Berbís JM, Popa A, de Amescua Seco A. A Survey on Energy Efficiency in Smart Homes and Smart Grids. (2023). LAPSE:2023.18262
Author Affiliations
Prieto González L: Software Architect Group, Department of Computer Science, Carlos III University of Madrid, 28911 Leganés, Spain [ORCID]
Fensel A: Wageningen Data Competence Center (WDCC), Wageningen University and Research, 6708 PB Wageningen, The Netherlands; Consumption & Healthy Lifestyles Group, Wageningen University and Research, 6708 PB Wageningen, The Netherlands; STI (Semantic Technology In
Gómez Berbís JM: Software Architect Group, Department of Computer Science, Carlos III University of Madrid, 28911 Leganés, Spain
Popa A: STI (Semantic Technology Institute) Innsbruck, Department of Computer Science, University of Innsbruck, 6020 Innsbruck, Austria
de Amescua Seco A: Software Architect Group, Department of Computer Science, Carlos III University of Madrid, 28911 Leganés, Spain
Fensel A: Wageningen Data Competence Center (WDCC), Wageningen University and Research, 6708 PB Wageningen, The Netherlands; Consumption & Healthy Lifestyles Group, Wageningen University and Research, 6708 PB Wageningen, The Netherlands; STI (Semantic Technology In
Gómez Berbís JM: Software Architect Group, Department of Computer Science, Carlos III University of Madrid, 28911 Leganés, Spain
Popa A: STI (Semantic Technology Institute) Innsbruck, Department of Computer Science, University of Innsbruck, 6020 Innsbruck, Austria
de Amescua Seco A: Software Architect Group, Department of Computer Science, Carlos III University of Madrid, 28911 Leganés, Spain
Journal Name
Energies
Volume
14
Issue
21
First Page
7273
Year
2021
Publication Date
2021-11-03
ISSN
1996-1073
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Original Submission
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PII: en14217273, Publication Type: Review
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LAPSE:2023.18262
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https://doi.org/10.3390/en14217273
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Mar 7, 2023
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