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arXiv · 2005.13428

Chance Constraint Tuning for Optimal Power Flow

Ashley M. Hou·Line A. Roald
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Abstract

In this paper, we consider a chance-constrained formulation of the optimal power flow problem to handle uncertainties resulting from renewable generation and load variability. We propose a tuning method that iterates between solving an approximated reformulation of the optimization problem and using a posteriori sample-based evaluations to refine the reformulation. Our method is applicable to both single and joint chance constraints and does not rely on any distributional assumptions on the uncertainty. In a case study for the IEEE 24-bus system, we demonstrate that our method is computationally efficient and enforces chance constraints without over-conservatism.

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Ashley M. Hou, Line A. Roald. 2020-05-27. Chance Constraint Tuning for Optimal Power Flow. https://arxiv.org/abs/2005.13428

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