Two-Stage Adaptive Restoration Decision Support System For A Self-Healing Power Grid
Keywords
Adaptive restoration; dynamic reserve; integer L-shaped algorithm; mixed-integer linear programming; two-stage optimization
Abstract
Power outages cost American industries and businesses billions of dollars and jeopardize the lives of hospital patients. The losses can be greatly reduced with a fast, reliable, and flexible self-healing tool. This paper is aimed to tackle the challenging task of developing an adaptive restoration decision support system (RDSS). The proposed RDSS determines restoration actions both in planning and real-time phases and adapts to constantly changing system conditions. The comprehensive formulation encompasses practical constraints including ac power flow, dynamic reserve, and load modeling. The combinatorial problem is decomposed into a two-stage formulation solved by an integer L-shaped algorithm. The two stages are then executed online in the RDSS framework employing a sliding window method. The IEEE 39-bus system has been studied under normal and contingency conditions to demonstrate the effectiveness and efficiency of the proposed online RDSS.
Publication Date
12-1-2017
Publication Title
IEEE Transactions on Industrial Informatics
Volume
13
Issue
6
Number of Pages
2802-2812
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/TII.2017.2712147
Copyright Status
Unknown
Socpus ID
85040081965 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85040081965
STARS Citation
Golshani, Amir; Sun, Wei; Zhou, Qun; Zheng, Qipeng P.; and Tong, Jianzhong, "Two-Stage Adaptive Restoration Decision Support System For A Self-Healing Power Grid" (2017). Scopus Export 2015-2019. 5643.
https://stars.library.ucf.edu/scopus2015/5643