A RBFN hierarchical clustering based network partitioning method for zonal pricing

In order to overcome the difficulty in using nodal pricing, the notion of zone is widely adopted in actual pricing scheme. The key for establishing a simple and efficient zonal pricing scheme is to accurately partition transmission network in the presence of congestion. Unfortunately, in actual powe...

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Bibliographic Details
Main Authors: Hongming Yang, Renjun Zhou, Jianhua Liu
Format: Conference Proceeding
Language:English
Subjects:
Cities and towns
Clustering algorithms
Educational institutions
Equations
Hierarchical clustering
Humans
IEEE catalog
Joining processes
Kernel
power market
price zone
Pricing
radial basis function network
Radial basis function networks
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Summary:In order to overcome the difficulty in using nodal pricing, the notion of zone is widely adopted in actual pricing scheme. The key for 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 price zone partition without any priori partition knowledge, this paper firstly extracts the sensitivities of nodal power injections to power flows on all congested lines as cluster features of nodal price. Secondly, a scale hierarchical clustering method based the radial basis function network (RBFN) for price zone partition is proposed. Finally, test results on IEEE 118-node system show the validity and feasibility of the proposed method.
DOI:10.1109/ICEEE.2005.1529627