Advanced Model-based Approaches to be Applied in the Context of a Bidding Zone Review

This paper presents advanced model-based algorithms to be applied for identifying alternative configurations in the context of a bidding zone review process. Two main steps are foreseen in these approaches: in the first step, nodal indicators are computed for a sufficiently large set of power system scenarios; in the second step, nodes are grouped to form candidate bidding zones with the adoption of advanced clustering algorithms. In this paper, relevant proposals for improving existing methodologies are presented, with the aim of improving the reliability and robustness of the proposed alternative configurations. In particular, an advanced Security Constrained Unit Commitment algorithm is adopted for computing the Locational Marginal Prices. These prices are then processed using dedicated clustering algorithms to propose alternative bidding zones configurations. Relevant results are presented applying the proposed approach on a large-scale model and extended data set related to the Italian power system.