Modeling the safety and security status of a converter platform using Bayesian networks

Abstract

In 2020, 5.5 % of the German electricity mix has been produced by the offshore wind industry. It can be expected that the amount of offshore wind energy will increase in medium term due to the change in the German public opinion after nuclear disaster in Fukushima in 2011. Based on their function within a Offshore Windfarm (OWF) the high voltage direct current converterplatform (HVDC converterplatform) are a key infrastructure. When the HVDC converterplatform stops operating the energy production of multiple Offshore Windfarms (OWFs) cannot be submitted to the shore. Therefore, selected safety and security scenarios should be studied. This study introduces a method to transform a process model into a Bayesian network. The developed method can also be applied for the modelling of countermeasures. With Bayesian networks, it is possible to quantify the safety and security status of a offshore platforms. It has been shown that the scenario "unauthorised access" is more likely than the scenario "hard landing of a helicopter at the landing deck". It has also be shown that countermeasures can only partly be modelled.