This paper focuses on model-based approaches that could be adopted for identifying alternative configurations to be considered in a bidding zone review process. Considering the complexity of this task, automated procedures can significantly help transmission system operators, allowing them to assess a large amount of possible system conditions and future scenarios. These methodologies are based on a 2-step approach: in the first step relevant nodal quantities are computed; then, in the second step, nodes are aggregated into zones using proper clustering algorithms. This paper starts with a critical review of the existing proposals, highlighting advantages and disadvantages of each of them, focusing on their practical implementation on a wide-area power system and in the context of the current electricity market framework. Some promising options are then identified for the Italian Power System case. In particular, an improved security constrained optimal power flow algorithm for computing Locational Marginal Prices (LMPs) and for identifying relevant critical branches (to be considered in the Power Transfer Distribution Factors computation) has been developed. Then, a selected set of clustering algorithms has been implemented and tested to check their effectiveness in forming LMP-based bidding zones.