Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Study of combinations of site operating states for multi-unit PSA

  • Received : 2020.11.27
  • Accepted : 2021.04.12
  • Published : 2021.10.25
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Abstract

As Probabilistic Safety Assessments (PSAs) are thoroughly conducted for the Site Operating States (SOSs) for a single unit, multi-unit Probabilistic Safety Assessments (MUPSAs) are ongoing worldwide to address new technical challenges or issues. In South Korea, the determination of the site operating states for a single site requires a logical approach with reasonable assumptions due to the fact that there are 4-8 operating units for each site. This paper suggests a simulation model that gives a reasonable expectation of the site operation states using the Monte-Carlo method as a stochastic approach and deterministic aspects such as operational policies. Statistical hypothesis tests were conducted so that the reliance of the simulation results can be guaranteed. In this study, 7 units of the Kori site were analysed as a case study. The result shows that the fraction of full power for all 7 units is nearly 0.45. For situations when more than two units are not in operation, the highest fraction combination was obtained for Plant Operation State (POS) 8, which is the stage of inspection and repairment. By entering various site operation scenarios, the simulation model can be used for the analysis of other site operation states.

Keywords

Acknowledgement

This work was supported by the Nuclear Safety Research Program through the Korea Foundation Of Nuclear Safety (KOFONS) with a financial grant from the Nuclear Safety and Security Commission (NSSC) of the Republic of Korea (No. 1705001). Additional support was provided by the Human Resources Program in Energy Technology of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) with a financial grant from the Ministry of Trade, Industry & Energy (MOTIE), Republic of Korea (No. 20184030202170).

References

  1. san Kim Dong, Hoon Han Sang, Hee Park Jin, Go-Gon Lim, Han Kim Jung, Multi-unit Level 1 probabilistic safety assessment: approaches and their application to a six-unit nuclear power plant site, Nuclear Engineering and Technology 50 (8) (2018) 1217-1233. https://doi.org/10.1016/j.net.2018.01.006
  2. Marko Cepin, Application of shutdown probabilistic safety assessment, Reliab. Eng. Syst. Saf. 178 (2018) 147-155. https://doi.org/10.1016/j.ress.2018.05.012
  3. T.-L. Chu, R.G. Fitzpatrick, W.H. Yoon, A. Tingle, An assessment of the core damage frequency of a PWR at shutdown, Reliab. Eng. Syst. Saf. 26 (3) (1989) 197-229. https://doi.org/10.1016/0951-8320(89)90012-4
  4. Ho-Gon Lim, Jin-Hee Park, Sang-Hoon Han, Seong-Cheol Jang, Fault tree conditioning methods to trace system configuration changes for the application to low-power/shutdown PSA, Reliab. Eng. Syst. Saf. 94 (10) (2009) 1666-1675. https://doi.org/10.1016/j.ress.2009.04.005
  5. Korea Atomic Energy Research Institute, Improvement of Initiating Events Analysis in Low-Power and Shutdown PSA for Korea Standard Nuclear Power Plant, KAERI/TR-2986/2005, 2005, p. 76.
  6. D.I. Gertman, L.N. Haney, N.O. Siu, Representing context, cognition, and crew performance in a shutdown risk assessment, Reliab. Eng. Syst. Saf. 52 (3) (1996) 261-278. https://doi.org/10.1016/0951-8320(95)00138-7
  7. Pavol Zvoncek, Olivier Nusbaumer, Alfred Torri, Development of a fully-coupled, all states, all hazards level 2 PSA at leibstadt nuclear power plant, Nuclear Engineering and Technology 49 (2) (2017) 426-433. https://doi.org/10.1016/j.net.2017.01.016
  8. Marko Cepin, The extended living probabilistic safety assessment, Proc. Inst. Mech. Eng. O J. Risk Reliab. 234 (1) (2019) 183-192.
  9. Inn Seock Kim, Misuk Jang, Seoung Rae Kim, Holistic approach to multi-unit site risk assessment: status and issues, Nuclear Engineering and Technology 49 (2) (2017) 286-294. https://doi.org/10.1016/j.net.2017.01.003
  10. Sang Hoon Han, Kyemin Oh, Joon-Eon Yang, AIMS-MUPSA software package for multi-unit PSA, Nuclear Engineering and Technology 50 (8) (2018) 1255-1265. https://doi.org/10.1016/j.net.2018.06.012
  11. Sunghyon Jang, Akira Yamaguchi, Development of Multi-Unit Dependency Evaluation Model Using Markov Process and Monte Carlo Method, Probabilistic Safety Assessment and Management 14 (PSAM 14), 2018, pp. 16-21. Los Angeles, USA, September.
  12. Korea Institution of Nuclear Safety, Operation performance information system for nuclear power plant. http://opis.kins.re.kr/opis?act=KROBA4500R.
  13. Korea Institution of Nuclear Safety, Nuclear power plant operation annual report. http://opis.kins.re.kr/opis?act=KROEA4100R&type=C.
  14. Korea Hydro, Nuclear Power, Open operational performance information system for nuclear power plant. https://npp.khnp.co.kr/board/list.khnp?boardId=BBS_0000002&menuCd=DOM_000000101001000000&contentsSid=2.
  15. International Atomic Energy Agency. Country statistics, IAEA Power Reactor Information System. https://pris.iaea.org/PRIS/CountryStatistics/CountryDetails.aspx?current=KR.
  16. Kurt Binder, Dieter W. Heemann, Monte Carlo Simulation in Statistical Physics, fifth ed., Springer, 2010.