LAPSE:2018.0638
Published Article
LAPSE:2018.0638
An Extreme Scenario Method for Robust Transmission Expansion Planning with Wind Power Uncertainty
Zipeng Liang, Haoyong Chen, Xiaojuan Wang, Idris Ibn Idris, Bifei Tan, Cong Zhang
September 21, 2018
The rapid incorporation of wind power resources in electrical power networks has significantly increased the volatility of transmission systems due to the inherent uncertainty associated with wind power. This paper addresses this issue by proposing a transmission network expansion planning (TEP) model that integrates wind power resources, and that seeks to minimize the sum of investment costs and operation costs while accounting for the costs associated with the pollution emissions of generator infrastructure. Auxiliary relaxation variables are introduced to transform the established model into a mixed integer linear programming problem. Furthermore, the novel concept of extreme wind power scenarios is defined, theoretically justified, and then employed to establish a two-stage robust TEP method. The decision-making variables of prospective transmission lines are determined in the first stage, so as to ensure that the operating variables in the second stage can adapt to wind power fluctuations. A Benders’ decomposition algorithm is developed to solve the proposed two-stage model. Finally, extensive numerical studies are conducted with Garver’s 6-bus system, a modified IEEE RTS79 system and IEEE 118-bus system, and the computational results demonstrate the effectiveness and practicability of the proposed method.
Keywords
benders’ decomposition, load shedding, transmission network expansion planning, uncertainty, wind power
Suggested Citation
Liang Z, Chen H, Wang X, Ibn Idris I, Tan B, Zhang C. An Extreme Scenario Method for Robust Transmission Expansion Planning with Wind Power Uncertainty. (2018). LAPSE:2018.0638
Author Affiliations
Liang Z: School of Electric Power, South China University of Technology, Guangzhou 510641, China
Chen H: School of Electric Power, South China University of Technology, Guangzhou 510641, China
Wang X: School of Electric Power, South China University of Technology, Guangzhou 510641, China
Ibn Idris I: School of Electric Power, South China University of Technology, Guangzhou 510641, China
Tan B: School of Electric Power, South China University of Technology, Guangzhou 510641, China
Zhang C: School of Electrical and Information Engineering, Hunan University, Changsha 410082, China [ORCID]
[Login] to see author email addresses.
Journal Name
Energies
Volume
11
Issue
8
Article Number
E2116
Year
2018
Publication Date
2018-08-14
Published Version
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en11082116, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2018.0638
This Record
External Link

doi:10.3390/en11082116
Publisher Version
Download
Files
[Download 1v1.pdf] (1.3 MB)
Sep 21, 2018
Main Article
License
CC BY 4.0
Meta
Record Statistics
Record Views
553
Version History
[v1] (Original Submission)
Sep 21, 2018
 
Verified by curator on
Sep 21, 2018
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2018.0638
 
Original Submitter
Calvin Tsay
Links to Related Works
Directly Related to This Work
Publisher Version