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Chance Constraints for Improving the Security of AC Optimal Power Flow

Journal Article · · IEEE Transactions on Power Systems
 [1];  [2];  [3]
  1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  2. New York Univ. (NYU), NY (United States)
  3. Univ. of Wisconsin, Madison, WI (United States)
+ Show Author Affiliations
This paper introduces a scalable method for improving the solutions of ac optimal power flow (AC OPF) with respect to deviations in predicted power injections from wind and other uncertain generation resources. The aim of this paper is on providing solutions that are more robust to short-term deviations, and that optimize both the initial operating point and a parametrized response policy for control during fluctuations. We formulate this as a chance-constrained optimization problem. To obtain a tractable representation of the chance constraints, we introduce a number of modeling assumptions and leverage recent theoretical results to reformulate the problem as a convex, second-order cone program, which is efficiently solvable even for large instances. Our experiments demonstrate that the proposed procedure improves the feasibility and cost performance of the OPF solution, while the additional computation time is on the same magnitude as a single deterministic AC OPF calculation.
Research Organization:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
89233218CNA000001
OSTI ID:
1525830
Report Number(s):
LA-UR--18-22568
Journal Information:
IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems Journal Issue: 3 Vol. 34; ISSN 0885-8950
Publisher:
IEEECopyright Statement
Country of Publication:
United States
Language:
English

Figures / Tables (10)

Table I(p. 5)table Table I
Table II(p. 8)table Table II
Table III(p. 8)table Table III
Figure 1(p. 9)figure Figure 1
Table IV(p. 9)table Table IV
Table V(p. 9)table Table V
Table IX(p. 10)table Table IX
Table VI(p. 10)table Table VI
Table VII(p. 10)table Table VII
Table VIII(p. 10)table Table VIII

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Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
Generators
Load flow
Mathematical model
Production
Reactive power
Uncertainty
Voltage control