A Bayesian Neural Network (BNN) Machine Learning (ML) Surrogate Modelling Framework for High-Fidelity Thermal Fatigue Modelling of Components

发达国家和发展中国家的国家能源电网和配电基础设施目前正在进行重大改造，以生产所谓的智能电网基础设施。在这些智能电网中，将有动态发展的或间歇性的可再生能源供应的混合，并增加一定比例的基本负荷电力。有一种普遍的误解，认为核电站只能向任何国家的能源电网提供相对僵化的基本负荷电力。然而，这严重影响了核电部门在世界各地正在演变的更加多样化和混合的发电环境中提供具有成本效益的电力的作用的长期前景。不断增加的发电量正被间歇性可再生能源形式所主导。核能发电将需要适应这种新的智能电网基础设施。

National energy grid and power distribution infrastructure, within developed and developing countries, are currently undergoing significant modification to produce so-called smart grid infrastructure. In these smart grids there will be a mixture of dynamically evolving or intermittent renewable energy supply augmented by a proportion of base-load electrical power. There is a widespread misconception that nuclear power plants (NPPs) can only provide relatively inflexible base-load power to any national energy grid networks. However, this is significantly affecting the long-term prospects of the nuclear sector's role in delivering cost effective electrical power within the more heterogeneous and mixed power generation environment that is evolving around the world. Increasing electrical power generation is being dominated by intermittent renewable energy forms. Nuclear power generation will need to adapt to this new smart grid infrastructure.