Ensembles of climate change models for risk assessment of nuclear power plants

Matteo Vagnoli (1) , Francesco Di Maio (2) , Enrico Zio (3, 4, 5)

1 Faculty of Engineering [Nottingham]
2 Dipartimento di Energia [Milano]
3 SSEC - Chaire Sciences des Systèmes et Défis Energétiques EDF/ECP/Supélec
4 LGI - Laboratoire Génie Industriel - EA 2606
5 CentraleSupélec

Climate change affects technical Systems, Structures and Infrastructures (SSIs), changing the environmental context for which SSI were originally designed. In order to prevent any risk growth beyond acceptable levels, the climate change effects must be accounted for into risk assessment models. Climate models can provide future climate data, such as air temperature and pressure. However, the reliability of climate models is a major concern due to the uncertainty in the temperature and pressure future projections. In this work, we consider five climate change models (individually unable to accurately provide historical recorded temperatures and, thus, also future projections), and ensemble their projections for integration in a probabilistic safety assessment, conditional on climate projections. As case study, we consider the Passive Containment Cooling System (PCCS) of two AP1000 Nuclear Power Plants (NPPs). Results provided by the different ensembles are compared. Finally, a risk-based classification approach is performed to identify critical future temperatures, which may lead to PCCS risks beyond acceptable levels.

Keywords: Probabilistic safety assessment; Climate change; Ensemble of climate models; Risk-based classification; Passive Containment Cooling System (PCCS); Nuclear power plant (NPP)

Domains: Engineering Sciences [physics]

Matteo Vagnoli, Francesco Di Maio, Enrico Zio. Ensembles of climate change models for risk assessment of nuclear power plants. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2018, 232 (2), pp.185 - 200. ⟨10.1177/1748006X17734946⟩. ⟨hal-01786584⟩