13:30 - 14:15
Assurance of Digital Twins
A digital twin is a virtual representation of a system or asset, that calculates system states and makes system information available, through integrated
models and data, with the purpose of providing decision support, over its lifecycle. The Energy industry has used digital twins for a long time, be it under
different names, for example grid modelling tools, SCADA systems, and power flow models. Upcoming capabilities related to sensoring, data storage and
data analytics (AI/ML) will enable Digital Twins to play an ever increasing role in efficient decision support for saving cost and driving innovation.
Examples of key drivers include:
Operational efficiency
Remote operations
Supporting sustainability goals
The market for digital twins is likely to grow with a factor of 3 from 2021 to 2026. Digital twins differ in scale and complexity. Different capability levels can
be defined for the functional element of a digital twin mapped to the previously mentioned evolution of the functional element. The higher capability, the
more value. But as the complexity increases, so does the risk that the digital twin may not deliver what buyers expect, and could leave operators
wondering if they can trust information from a twin. DNV recommends that the following four aspects should be considered when assessing
trustworthiness of a digital twin:
The organizational maturity – an assessment of the organization’s capabilities to transform digitally, including people, tools, technology, processes and
competence to develop and maintain qualified digital twins.
The quality of the digital twin – assess that the digital twin meets the stated requirements and with the right quality.
Risk of use – assess the risk of using digital twins to support decisions.
Continuous assurance – ensure and assess that digital twins remain qualified over the lifetime of the asset
