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