# Robust MPC for temperature management on electrical transmission lines

## TL;DR

This paper presents a robust Model Predictive Control framework for real-time temperature management of electrical transmission lines, integrating production curtailment and battery storage to optimize network capacity and prevent congestion.

## Contribution

It introduces a novel temperature management model combining control variables and a tube-based MPC approach for enhanced transmission line safety and efficiency.

## Key findings

- Effective temperature regulation in simulations
- Reduced congestion and curtailment risks
- Improved utilization of transmission capacity

## Abstract

In the current context of high integration of renewable energies, maximizing infrastructures capabilities for electricity transmission is a general need for Transmission System Operators (TSO). The French TSO, RTE, is developing levers to control power flows in real-time: renewable production curtailment is already employed and large battery storage systems are planned to be installed for congestion management in early 2020. The combination of these levers with the use of Dynamic Line Rating (DLR) helps exploiting the lines at the closest of their limit by managing their temperature in real-time. Unnecessary margins can be reduced, avoiding congestion and excessive generation curtailment. In particular, there is a possible interesting correlation between the transits increase due to high wind farms generation and the cooling effect of wind on power lines in the same area. In order to optimize the electrical transmission network capacities, the present paper advocates the use of a temperature management model, mixing production curtailment and large batteries as control variables. A robust Model Predictive Control framework for local control on electrical lines temperature is presented based on the regulation within tubes of trajectories. Simulations on the French electrical network are conducted to show the effectiveness of the optimization-based control design.