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

Socpus ID

85040081965 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85040081965

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