Fuzzy regression models to represent electricity market data in deregulated power industry

TitleFuzzy regression models to represent electricity market data in deregulated power industry
Publication TypeJournal Article
Year of Publication2001
AuthorsNiirmura, T., M. Dhaliwal, and K. Ozawa
Secondary AuthorsSmith, M. H., W. A. Gruver, and L. O. Hall
JournalJoint 9TH IFSA World Congress and 20TH NAFIPS International Conference, Proceedings, Vols. 1-5
Pagination2556–2561
Abstract

In this paper the authors present a flexible model that represents the relation of electricity price and demand in a electrical power market. Power market data are first analyzed by regression analysis. The price data show upward trend as the demand volume increases. We have divided the regression model into two regions: low demand and high demand. Two curves are smoothly connected by a TSK-fuzzy model noting the fact that the "low" demand and "high" demand regions are not distinct but overlapping. The fuzzy model is further extended to encompass the data region indicating the degree of possibility. California Power Exchange data are analyzed as an example.

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