Endogenous price zones and investment incentives in electricity markets: An application of multilevel optimization with graph partitioning

In the course of the energy transition, load and supply centers are growing apart in electricity markets worldwide, rendering regional price signals even more important to provide adequate locational investment incentives. In this paper, we focus on electricity markets with zonal pricing from a long-run perspective, i.e., we include capacity investment decisions. For a fixed number of zones, we endogenously derive the optimal configuration of price zones and available transfer capacities. We build on the multilevel mixed-integer nonlinear model with graph partitioning on the first level developed in Grimm et al. (2019) and adapt it to be able to solve the model to global optimality even for large instances. By applying the model to the German electricity market, we find that a considerable share of the maximum possible welfare gains can already be achieved by implementing a few (two or three) optimally configured price zones with restrictive inter-zonal ATCs. Moreover, ATCs between zones are an important influencing factor for the achievable welfare gains and investment incentives. Finally, our results show that hypothetical nodal prices are not a good guidance to partition nodes into optimal zones. (C) 2020 Published by Elsevier B.V.