DocumentCode :
2037
Title :
Interval Power Flow Analysis Using Linear Relaxation and Optimality-Based Bounds Tightening (OBBT) Methods
Author :
Tao Ding ; Rui Bo ; Fangxing Li ; Qinglai Guo ; Hongbin Sun ; Wei Gu ; Gan Zhou
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Volume :
30
Issue :
1
fYear :
2015
fDate :
Jan. 2015
Firstpage :
177
Lastpage :
188
Abstract :
With increasingly large scale of intermittent and non-dispatchable resources being integrated into power systems, the power flow problem presents greater uncertainty. In order to obtain the upper and lower bounds of power flow solutions including voltage magnitudes, voltage angles and line flows, Cartesian coordinates-based power flow is utilized in this paper. A quadratically constrained quadratic programming (QCQP) model is then established to formulate the interval power flow problem. This non-convex QCQP model is relaxed to linear programming problem by introducing convex and concave enclosures of the original feasible region. To improve the solutions bounds while still encompassing the true interval solution, optimality-based bounds tightening (OBBT) method is employed to find a better outer hull of the feasible region. Numerical results on IEEE 9-bus, 30-bus, 57-bus, and 118-bus test systems validate the effectiveness of the proposed method.
Keywords :
concave programming; linear programming; load flow; quadratic programming; Cartesian coordinates based power flow; OBBT Methods; concave enclosure; convex enclosure; interval power flow analysis; interval power flow problem; line flows; linear programming problem; linear relaxation methods; nonconvex QCQP model; optimality based bounds tightening methods; quadratically constrained quadratic programming; voltage angles; voltage magnitudes; Equations; Linear programming; Mathematical model; Reactive power; Sparse matrices; Uncertainty; Vectors; Convex/concave envelopes; interval power flow; linear relaxation; optimality-based bounds tightening (OBBT); quadratically constrained quadratic programming (QCQP); uncertainty;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2014.2316271
Filename :
6814337
Link To Document :
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