Digital twins and predictive models in energy operation do not yet meet expectations

Energy operators are not yet satisfied with the performance of digital twins and predictive models in their operations.

Energy operators are exploring the use of digital twins and predictive models to optimize their operations, but results are not yet meeting expectations, according to a recent report. Digital twins are virtual replicas of physical systems that can be used to simulate and analyze performance. Predictive models use data from these twins to forecast future events and optimize decision-making.

While some energy operators have reported successful implementations of digital twins and predictive models, others have encountered technical and integration challenges.

To overcome these challenges, energy operators are working with technology providers to develop more sophisticated digital twins and predictive models that can better meet their needs.