Simplifying the Computation of Shapley Values for Allocating Congestion Costs in Large Power Grid Models

Abstract

The ongoing transformation of the energy system challenges the electricity grids throughout Europe, increasing the costs of congestion management. Because the interconnected electricity grids are operated by many different grid operators, fairly allocating these costs is essential. A long-established method for fairly allocating costs is the Shapley value. Based on Voswinkel et al. (2022) this contribution investigates the applicability of a simplification approach for calculating the Shapley value to a realistic grid model, covering the German extra high voltage grid. This analytical method using non-binding constraints is applied to a whole year of hourly grid load cases and the factors that govern the efficiency of the algorithm are analyzed. Results show that the effectiveness of the algorithm increases substantially when more overloaded elements are present in a given grid load case, with more than 99% of computational effort being saved in grid load cases with many overloaded elements. Regression analyses indicate that the effectiveness is governed by the extent to which redispatch measures can alleviate multiple overloads at once - the situations where fairly sharing the costs is most important. This contribution thus demonstrates that previously evoked computational difficulties may be overcome and that the operational implementation of the Shapley value should be seriously considered.

Keywords: Congestion Management, Redispatch, Shapley Value, Cost Sharing, Power Grids, Game Theory