NDLI: Reliability enhancement of power systems through a mean

Content Provider	Springer Nature Link
Author	Yaakob, Shamshul Bahar Watada, Junzo Takahashi, Tsuguhiro Okamoto, Tatsuki
Copyright Year	2011
Abstract	Recently, power-supply failures have caused major social losses. Therefore, power-supply systems need to be highly reliable. The objective of this study is to present a significant and effective method of determining a productive investment to protect a power-supply system from damage. In this study, the reliability and risks of each of the units are evaluated with a variance–covariance matrix, and the effects and expenses of replacement are analyzed. The mean–variance analysis is formulated as a mathematical program with the following two objectives: (1) to minimize the risk and (2) to maximize the expected return. Finally, a structural learning model of a mutual connection neural network is proposed to solve problems defined by mixed-integer quadratic programming and is employed in the mean–variance analysis. Our method is applied to a power system network in the Tokyo Metropolitan area. This method enables us to select results more effectively and enhance decision making. In other words, decision-makers can select the investment rate and risk of each ward within a given total budget.
Starting Page	1363
Ending Page	1373
Page Count	11
File Format	PDF
ISSN	09410643
Journal	Neural Computing and Applications
Volume Number	21
Issue Number	6
e-ISSN	14333058
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-03-29
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Boltzmann machine Mean–variance analysis Neural network Power system reliability Simulation and Modeling
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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