Data-driven Inverse Optimization with Application to Dynamic Line Rating in Russian Power Grid

Dynamic line rating technology has been evolving since the late nineteen seventies. However, it is not used to its full extend. This study presents a methodology for calculating the benefits of dynamic line rating in the Russian power grid. The economic benefits of using a dynamic line rating instead of a conventional static line rating are estimated for a simple but representative two-zone network representing a multi-unit Russian energy corridor connecting the Siberian and European zones. Due to the lack of precise information on the generation units’ costs and capacity, we present an inverse optimization model to infer these parameters from the available electricity price and aggregated consumption. Our simulations show that using dynamic line rating versus static rating results in savings of up to 1.65% per day.