A methodology for assessing the reliability and security of cascade reservoir systems

Ying Tian, Qingwen Ren, Yin Yang and Yao Xiong

Journal of Risk and Reliability, 2017, vol. 231, issue 6, 680-690

Abstract: The scale of cascade reservoir systems is increasing rapidly along with the development of hydroelectric projects in these systems. Related security problems are receiving increasing public attention. However, no security evaluation method for this type of system can be found in the literature. Reliability is an essential indicator to measure system security. Because of the brittleness, complexity, and polymorphism of the system, a Bayesian network and set pair analysis theory–based methodology suitable for the reliability analysis of cascade reservoir systems is suggested in this article. First, the topological structure of the Bayesian network is constructed, and the brittle effect is measured using the powerful probabilistic inference capability of the Bayesian network. Then, the probability distribution of each subsystem is obtained, and probabilities of the system in all states are integrated using set pair analysis theory. Furthermore, the composite reliability is proposed as a generic reliability representation for cascade reservoir systems. On this basis, through constructing a composite probability vector and composite probability matrix, the Bayesian network and set pair analysis theory–based reliability measure models for both subsystems and the whole system are proposed. Finally, the effectiveness and practicability of the method described above are verified by introducing an example application. The results show that this research provides a theoretical basis and practical method for assessing the reliability and security of cascade reservoir systems.

Keywords: Cascade reservoir system; brittle and polymorphic; probability metric; bayesian network; set pair analysis; reliability measure (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1748006X17726945 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:231:y:2017:i:6:p:680-690

DOI: 10.1177/1748006X17726945

Access Statistics for this article

More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().