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Large Scale Bilevel Optimization for N-K SCOPF Using Adversarial Robustness

Journal Article · · IEEE Transactions on Power Systems
 [1];  [2];  [1];  [1]
  1. Carnegie Mellon University, Pittsburgh, PA (United States)
  2. Massachusetts Institute of Technology, Cambridge, MA (United States)
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Ensuring a secure dispatch against multiple simultaneous outages has long been desired to maintain grid security in the presence of severe events, such as extreme weather phenomena. Traditionally denoted as N-k security constrained optimal power flow (N-k SCOPF), this problem is intractable to solve due to its size being combinatorial in the number of simultaneous outages and due to the non-convex nature of the AC network constraints. This hinders the use of N-k SCOPF for operating realistic-scale systems. In this paper, we introduce a methodology to scalably solve an AC-feasible dispatch that improves security over k simultaneous outages. Our methodology poses N-k SCOPF as a bilevel optimization problem and solves it using an adversarial robustness approach. We develop new efficient methods to solve each level of the bilevel optimization by employing knowledge of the physics of the underlying system. This yields significant improvements in speed and convergence that enable us to address the N-k SCOPF problem at scale. We demonstrate the effectiveness of our method by conducting a comprehensive analysis of an N-3 SCOPF for a 500-bus network. Furthermore, we emphasize the ability of our physics-driven techniques to handle larger systems by successfully scaling up to 12,000 buses.

Research Organization:
Carnegie Mellon University, Pittsburgh, PA (United States); Massachusetts Institute of Technology, Cambridge, MA (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Hydrogen Fuel Cell Technologies Office (HFTO)
Grant/Contract Number:
EE0010724
OSTI ID:
2569194
Journal Information:
IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems; ISSN 1558-0679; ISSN 0885-8950
Publisher:
IEEECopyright Statement
Country of Publication:
United States
Language:
English

Figures / Tables (8)

Fig. 1(p. 4)figure Fig. 1
Fig. 2(p. 5)figure Fig. 2
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Fig. 4(p. 9)figure Fig. 4
Fig. 5(p. 10)figure Fig. 5
TABLE I(p. 10)table TABLE I
TABLE II(p. 10)table TABLE II
TABLE III(p. 12)table TABLE III

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Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
bilevel optimization
optimal power flow
power systems
robust optimization
security-constrained optimal power flow