Model Predictive Control of Security in Real-Time via AC Security Constrained Optimal Power Flow

The ongoing energy transition to renewable supply increases volatility and uncertainty in power systems operation. Adaptating to these prevailing conditions requires managing dynamically security in real-time to ensure cost efficiency. To this end, we propose to leverage AC Security-Constrained Optimal Power Flow (SCOPF) to form a novel model predictive control (MPC)-inspired approach to security in future power systems called MPC-SCOPF. This paper presents a benchmark mathematical framework of MPC-SCOPF, that takes into account: contingencies, a look ahead horizon of multiple time periods, and time-coupled constraints. The MPC-SCOPF re-dispatches the output of controllable assets to maintain security at minimum cost. A full-day rolling horizon simulation of re-dispatch for a modified Nordic32 system demonstrates that the MPC approach outperforms the single-period SCOPF in terms of re-dispatch cost.