LAPSE

LAPSE:2019.0278
Published Article
LAPSE:2019.0278
Long Term Expected Revenue of Wind Farms Considering the Bidding Admission Uncertainty
Mazaher Haji Bashi, Gholamreza Yousefi, Claus Leth Bak, Jayakrishnan Radhakrishna Pillai
February 5, 2019
As a long term bidding behavior, bid shading is exhibited by wind farms participating in real Uniform Price (UP) markets. This signifies that the wind farm owners bid far below their true long run marginal cost. In this paper, a method is proposed to consider the uncertainty of bidding admission in the long term expected revenue of wind farms. We show that this consideration could perfectly explain the observed bid shading behavior of wind farm owners. We use a novel market price model with a stochastic model of a wind farm to derive indices describing the uncertainty of bidding admission. The optimal behavior of the wind farm is then obtained by establishing a multi objective optimization problem and subsequently solved using genetic algorithm. The method is applied to the analysis of long term bidding behavior of a wind farm participating in a Pay-as-Bid (PAB) auction such as Iran Electricity Market (IEM). The results demonstrate that wind farm owners change their bid shading behavior in a PAB Auction. However, the expected revenue of the wind farm will also decrease in a PAB auction. As a result, it is not recommended to make an obligation for the wind farms to participate in a PAB auction as a normal market player.
Keywords
bidding Admission uncertainty, Genetic Algorithm, long term bidding behavior, market price uncertainty, PAB and UP auctions, wind farm expected revenue
Suggested Citation
Haji Bashi M, Yousefi G, Bak CL, Radhakrishna Pillai J. Long Term Expected Revenue of Wind Farms Considering the Bidding Admission Uncertainty. (2019). LAPSE:2019.0278
Author Affiliations
Haji Bashi M: Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran
Yousefi G: Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran
Bak CL: Energy Technology Department, Aalborg University of Denmark, 9100 Aalborg, Denmark
Radhakrishna Pillai J: Energy Technology Department, Aalborg University of Denmark, 9100 Aalborg, Denmark
[Login] to see author email addresses.
Journal Name
Energies
Volume
9
Issue
11
Article Number
E945
Year
2016
Publication Date
2016-11-19
Published Version
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en9110945, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2019.0278
This Record
External Link

doi:10.3390/en9110945
Publisher Version
Download
Files
[Download 1v1.pdf] (1.4 MB)
Feb 5, 2019
Main Article
License
CC BY 4.0
Meta
Record Statistics
Record Views
105
Version History
[v1] (Original Submission)
Feb 5, 2019
 
Verified by curator on
Feb 5, 2019
This Version Number
v1
Citations
Most Recent
This Version
URL Here
http://psecommunity.org/LAPSE:2019.0278
 
Original Submitter
Calvin Tsay
Links to Related Works
Directly Related to This Work
Publisher Version