Deregulated electricity market data representation by fuzzy regression models
作者： T. Niimura , T. Nakashima
DOI: 10.1109/5326.971659
关键词: Fuzzy set 、 Electric power industry 、 Market data 、 Regression analysis 、 Simple linear regression 、 Econometrics 、 Electricity market 、 Electricity 、 Fuzzy number 、 Computer science 、 Electricity generation
摘要: In this paper, the authors present a fuzzy set-based model that represents relation of electricity demand and price in recently deregulated market. A simple regression analysis shows data's nonlinear trend as volume increases. We have divided data cluster into two overlapping regions: low high demand. Regression curves, obtained for clusters, are smoothly connected by Takagi-Sugeno-Kang (TSK)-fuzzy model. The is further expanded to encompass volatile region introducing numbers parameters. developed can indicate possibility distribution prices given value. also has flexibility narrowing its focus modifying numbers. California Power Exchange market analyzed numerical example.
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