A scale space based hierarchical clustering method of network partitioning for zonal pricing

In order to reduce the difficulty in using nodal pricing, the notion of zone is widely adopted in actual pricing scheme. The key to establishing a simple and efficient zonal pricing scheme is to accurately partition transmission network in the presence of congestion. Unfortunately, in actual power market operation, the operators usually establish zones based on their experiences, considering the locations of congested lines, without mathematical analysis. In order to achieve accurate network partitioning without any a priori partitioning knowledge, this paper firstly extracts the sensitivities of the nodal power injections to power flows on all congested lines as nodal features for clustering. Secondly, the scale space theory that simulates human visual system is introduced, and a scale space based hierarchical clustering method for network partitioning is proposed. Finally, test results on IEEE 118-node system show the validity and feasibility of the method proposed.