Computationally Efficient Solutions for Large-Scale Security-Constrained Optimal Power Flow

Mohammadhafez Bazrafshan; Kyri Baker; Javad Mohammadi

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arXiv · 2006.00585

Computationally Efficient Solutions for Large-Scale Security-Constrained Optimal Power Flow

Mohammadhafez Bazrafshan·Kyri Baker·Javad Mohammadi

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Abstract

In this paper, we discuss our approach and algorithmic framework for solving large-scale security constrained optimal power flow (SCOPF) problems. SCOPF is a mixed integer non-convex optimization problem that aims to obtain the minimum dispatch cost while maintaining the system N-1 secure. Finding a feasible solution for this problem over large networks is challenging and this paper presents contingency selection, approximation methods, and decomposition techniques to address this challenge in a short period of time. The performance of the proposed methods are verified through large-scale synthetic and actual power networks in the Grid Optimization (GO) competition organized by the U.S. Advanced Research Projects Agency-Energy (ARPA-E). As many prior works focus on small-scale systems and are not benchmarked using validated, publicly available datasets, we aim to present a practical solution to SCOPF that has been proven to achieve good performance on realistically sized (30,000 buses) networks.

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BibTeX RIS

Mohammadhafez Bazrafshan, Kyri Baker, Javad Mohammadi. 2020-05-31. Computationally Efficient Solutions for Large-Scale Security-Constrained Optimal Power Flow. https://arxiv.org/abs/2006.00585

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