Cosmo Tech

From Complexity to Clarity: How RTE Reinvented Asset Management with AI Simulation

From Complexity to Clarity: How RTE Reinvented Asset Management with AI Simulation

RTE is one of the largest high and extra-high voltage electricity transmission networks in Europe. It is also among the most advanced in terms of thinking about asset management strategy and the use of simulation. 

Since 2015, RTE teams have been using Cosmo Tech Asset Simulation Twins to transform their approach to asset investment planning and optimize network maintenance and investment. 

Through simulation, RTE enhanced the dialogue with the regulator, demonstrating the effects on and contributions to changes in technical policies on the network and investments over time. The regulator understood not only the impacts of the proposed strategy but also the reasons behind the requested spend by comparing the results of different scenario simulations.

Results

  • 15% budget allocation: Effectively demonstrated to the regulator an optimized Asset investment and maintenance strategy to manage the growth of the investment wall while strengthening network performance and robustness.       
  • -€700M extra maintenance cost avoided: Simulations showed that increasing short-term painting maintenance for tower anti-corrosion would avoid far more costly maintenance in the long term.
  • -300,000 Tons of CO₂: Simulations confirmed the need to accelerate gas-insulated substation renewals, reducing nearly 13 tons of SF6 emissions with a significant CO₂-equivalent impact.

RTE Customer Story 1-pager

RTE Customer Story 1-pager

See How RTE Reinvented Asset Management with Simulation-Driven Approach.
RTE Full Customer Story

RTE Full Customer Story

Explore the challenges RTE faced and the strategic thinking behind their shift from traditional methods to a simulation-driven approach to asset management.

There are different ways to calculate optimal strategies, but only simulation can reassure us or, on the contrary, alert us to potential pitfalls.