DocumentCode :
2338277
Title :
Fuzzy modeling for electrical market price forecasting
Author :
Pingan, Zhang ; Xiaohong, Guan
Author_Institution :
Inst. of Syst. Eng., Xi´´an Jiaotong Univ., China
Volume :
3
fYear :
2000
fDate :
2000
Firstpage :
2262
Abstract :
In the paper, market clearing price (MCP) short-term forecasting implementation using advanced fuzzy modeling technique is presented. The described approach uses the well-known Takagi-Sugeno-Kang (TSK) fuzzy model with scatter partition structure. A modified structure identification algorithm for the TSK model is introduced in detail. Particularly, since the presented algorithm is computationally simple and partitively accurate, we can set the good initial parameters and build the MCP forecasting fuzzy models rapidly. Retrospective MCP real-world data was used for modeling and testing the TSR model. The results presented in the paper confirm considerable value of the fuzzy modeling based approach in forecasting the MCP
Keywords :
electricity supply industry; forecasting theory; fuzzy set theory; power system economics; Takagi-Sugeno-Kang fuzzy model; electrical market price forecasting; fuzzy modeling; market clearing price short-term forecasting; modified structure identification algorithm; scatter partition structure; Economic forecasting; Electricity supply industry; Fuzzy sets; Partitioning algorithms; Predictive models; Scattering; Systems engineering and theory; Takagi-Sugeno model; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
Type :
conf
DOI :
10.1109/WCICA.2000.863007
Filename :
863007
Link To Document :
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