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28510

ASSESSMENT OF OFFSITE POWER RELIABILITY FOR NUCLEAR POWER PLANTS BY FAULT TREE ANALYSIS

Article

Last updated: 03 Jan 2025

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Abstract

The reliability of offsite power for a nuclear power plant (NPP) is
assessed using fault tree (FT) analysis. The method combines alternating
current (AC) load flow analysis with FT technique. The probability of loss
of offsite power (LOOP) initiating event is assessed based on the
unreliability of the power delivered to the house load of the NPP. Based on
the quantitative and qualitative analysis of the constructed FT, the
probability of the LOOP initiating event is assessed. The FT results
include the importance measures which enable identification of the most
important elements of the power system from the aspect of nuclear safety.
The impact of changes in the power system to the safety of the NPP is
evaluated. The verification of the method was performed on the IEEE test
system.

DOI

10.21608/auej.2019.28510

Keywords

Nuclear power plant, Loss of Offsite Power, Fault Tree

Authors

First Name

A

Last Name

Agwa

MiddleName

M

Affiliation

Faculty of Engineering - Al-Azhar University

Email

-

City

-

Orcid

-

First Name

E

Last Name

Eisawy

MiddleName

A

Affiliation

Nuclear and Radiological Regulatory Authority

Email

-

City

-

Orcid

-

First Name

H

Last Name

Hassan

MiddleName

M

Affiliation

Nuclear and Radiological Regulatory Authority

Email

-

City

-

Orcid

-

Volume

14

Article Issue

50

Related Issue

5077

Issue Date

2019-01-01

Receive Date

2019-03-07

Publish Date

2019-01-01

Page Start

99

Page End

107

Print ISSN

1687-8418

Link

https://jaes.journals.ekb.eg/article_28510.html

Detail API

https://jaes.journals.ekb.eg/service?article_code=28510

Order

28

Type

Original Article

Type Code

706

Publication Type

Journal

Publication Title

Journal of Al-Azhar University Engineering Sector

Publication Link

https://jaes.journals.ekb.eg/

MainTitle

ASSESSMENT OF OFFSITE POWER RELIABILITY FOR NUCLEAR POWER PLANTS BY FAULT TREE ANALYSIS

Details

Type

Article

Created At

22 Jan 2023