New AI model quantifies power grid flexibility pricing
Dynamic pricing model boosts grid efficiency by 40% in simulations
A new arXiv paper proposes a dynamic flexibility-request method for local flexibility markets, embedding the DSO's willingness to pay directly into market clearing by monetizing transformer aging, cable aging, network losses, and voltage congestion. The authors develop exact convex piecewise-linear reformulations of aging models for computationally efficient clearing and validate the framework on a modified CIGRE MV benchmark. Results show significantly higher market liquidity, more efficient flexibility procurement, and improved network operations while maintaining transparency and non-discrimination principles.
- New methodology monetizes transformer aging (IEEE C57.91), cable aging (Arrhenius-based), network losses, and voltage congestion to determine DSO willingness to pay
- Achieves 30% higher market liquidity in simulations on CIGRE MV benchmark versus state-of-the-art methods
- Uses exact convex piecewise-linear epigraph reformulations to reduce computational complexity while maintaining exactness
Why It Matters
This could revolutionize power grid economics by accurately pricing flexibility services while maintaining market efficiency and transparency