Cloud Monitoring for Solar Plants with Support Vector Machine Based Fault Detection System
Joint Authors
Chang, Hong-Chan
Lin, Shang-Chih
Yu, Hao-Ping
Kuo, Cheng-Chien
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-03
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
This study endeavors to develop a cloud monitoring system for solar plants.
This system incorporates numerous subsystems, such as a geographic information system, an instantaneous power-consumption information system, a reporting system, and a failure diagnosis system.
Visual C# was integrated with ASP.NET and SQL technologies for the proposed monitoring system.
A user interface for database management system was developed to enable users to access solar power information and management systems.
In addition, by using peer-to-peer (P2P) streaming technology and audio/video encoding/decoding technology, real-time video data can be transmitted to the client end, providing instantaneous and direct information.
Regarding smart failure diagnosis, the proposed system employs the support vector machine (SVM) theory to train failure mathematical models.
The solar power data are provided to the SVM for analysis in order to determine the failure types and subsequently eliminate failures at an early stage.
The cloud energy-management platform developed in this study not only enhances the management and maintenance efficiency of solar power plants but also increases the market competitiveness of solar power generation and renewable energy.
American Psychological Association (APA)
Chang, Hong-Chan& Lin, Shang-Chih& Kuo, Cheng-Chien& Yu, Hao-Ping. 2014. Cloud Monitoring for Solar Plants with Support Vector Machine Based Fault Detection System. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-481139
Modern Language Association (MLA)
Chang, Hong-Chan…[et al.]. Cloud Monitoring for Solar Plants with Support Vector Machine Based Fault Detection System. Mathematical Problems in Engineering No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-481139
American Medical Association (AMA)
Chang, Hong-Chan& Lin, Shang-Chih& Kuo, Cheng-Chien& Yu, Hao-Ping. Cloud Monitoring for Solar Plants with Support Vector Machine Based Fault Detection System. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-481139
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-481139