DocumentCode :
3110500
Title :
Study on bidding strategies of Gencos based on cumulative prospect theory and Bayesian learning model
Author :
Li, Chunjie ; Wu, Junyou ; Cheng, Yancong
Author_Institution :
North China Electr. Power Univ., Beijing, China
fYear :
2011
fDate :
26-28 March 2011
Firstpage :
958
Lastpage :
963
Abstract :
Because generators are limited rationality and their bidding strategies exist risk and uncertainty, this paper proposes a generators´ bidding model which is constructed by value function and weight function based on cumulative prospect theory. Value function shows the changes of losses and gains, and weight function reflects players´ psychological risk factors. The prospect value of bidding strategy is decided by value function and weight function, and the optimal bidding strategy is the biggest one among these prospect values. Finally, an example is employed, and the numerical results tell us that this method is feasible.
Keywords :
Bayes methods; commerce; higher order statistics; power markets; risk management; Bayesian learning model; Gencos; bidding strategy; cumulative prospect theory; psychological risk factor; value function; weight function; Bayesian methods; Biological system modeling; Electricity; Generators; Power systems; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Technology (ICIST), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9440-8
Type :
conf
DOI :
10.1109/ICIST.2011.5765132
Filename :
5765132
Link To Document :
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