Neural Network-Assisted Model Predictive Control for Implicit Balancing
In Europe, balance responsible parties can deliberately take out-of-balance positions to support transmission system operators (TSOs) in maintaining grid stability and earn profit, a practice called implicit balancing. Model predictive control (MPC) is widely adopted as an effective approach for implicit balancing. The balancing market model accuracy in MPC is critical to decision quality. Previous studies modeled this market using either (i) a convex market clearing approximation, ignoring proactive manual actions by TSOs and the market sub-quarter-hour dynamics, or (ii) machine learning methods, which cannot be directly integrated into MPC. To address these shortcomings, we propose a da...
| Authors | Seyed Soroush Karimi Madahi, Kenneth Bruninx, Bert Claessens et al. |
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| Primary category | eess.SY |
| Published | 2 April 2026 |
| Last updated at source | 2 April 2026 |
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