Identification of good practices in the operation of nuclear power plants

This work developed an approach to diagnose problems and identify good practices in the operation of nuclear power plants using the system dynamics technique. The research began with construction of the ORSIM (Nuclear Power Plant Operations and Risk Simulator) model, with its operational component modified from an existing model, and its risk component newly created in this research. A matrix of high-level performance indices was also created to measure plant performance as a function of continuous operation. The research continued with development of an interface program to provide a user-friendly environment, and then culminated with a report of the results obtained from a pilot project, and a demonstration of using ORSIM to investigate EPRI (Electric Power Research Institute) good practices. Both problem diagnosis and policy investigations were conducted in the pilot project. It was found that the performance matrix developed in this work was able to measure stability, reliability, and economic performance in a concise and clear manner. With this matrix, ORSIM was able to pinpoint bottlenecks of current operations and to project into the future what would be the implications of various policy changes.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Nuclear Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2005

Author dc:creator

• Chen, Haibo, 1975-

Advisor dc:contributor.advisor

• Michael W. Golay.

• Nuclear Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/34431

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/34431