LAPSE:2023.28808v1
Published Article
LAPSE:2023.28808v1
Dependability Impact in the Smart Solar Power Systems: An Analysis of Smart Buildings
Eltton Araujo, Paulo Pereira, Jamilson Dantas, Paulo Maciel
April 12, 2023
Abstract
The Internet has been going through significant transformations and changing the world around us. We can also see the Internet to be used in many areas, for innumerable purposes, and, currently, it is even used by objects. This evolution leads to the Internet of Things (IoT) paradigm. This new concept can be defined as a system composed of storage resources, sensor devices, controllers, applications, and network infrastructure, in order to provide specific services to its users. Since IoT comprises heterogeneous components, the creation of these systems, the communication, and maintenance of their components became a complex task. In this paper, we present a dependability model to evaluate an IoT system. Amid different systems, we chose to assess availability in a smart building. The proposed models allow us to calculate estimations of other measures besides steady-state availability, such as reliability. Thus, it was possible to notice that there was no considerable gain of availability in the system when applying grid-tie solar power or off-grid solar power. The grid-tie solar power system is cheaper than the off-grid solar power system, even though it produces more energy. However, in our research, we were able to observe that the off-grid solar power system recovers the applied financial investment in smaller interval of time.
Keywords
dependability model, internet of things, smart building, solar power
Suggested Citation
Araujo E, Pereira P, Dantas J, Maciel P. Dependability Impact in the Smart Solar Power Systems: An Analysis of Smart Buildings. (2023). LAPSE:2023.28808v1
Author Affiliations
Araujo E: Informatics Center, Federal University of Pernambuco, Recife 50740-560, Brazil [ORCID]
Pereira P: Informatics Center, Federal University of Pernambuco, Recife 50740-560, Brazil
Dantas J: Computing Department, Federal University of Vale do São Francisco, Salgueiro 56000-000, Brazil
Maciel P: Informatics Center, Federal University of Pernambuco, Recife 50740-560, Brazil
Journal Name
Energies
Volume
14
Issue
1
Article Number
E124
Year
2020
Publication Date
2020-12-29
ISSN
1996-1073
Version Comments
Original Submission
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PII: en14010124, Publication Type: Journal Article
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LAPSE:2023.28808v1
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https://doi.org/10.3390/en14010124
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