论文标题
大规模安全约束最佳功率流的计算有效解决方案
Computationally Efficient Solutions for Large-Scale Security-Constrained Optimal Power Flow
论文作者
论文摘要
在本文中，我们讨论了解决大规模安全性最佳功率流（SCOPF）问题的方法和算法框架。 SCOPF是一个混合整数非凸优化问题，旨在在保持系统N-1安全的同时获得最低调度成本。在大型网络上为此问题找到可行的解决方案是具有挑战性的，本文提出了应急选择，近似方法和分解技术，以在短时间内应对这一挑战。通过大规模的合成和实际功率网络在网格优化（GO）竞争中通过美国高级研究项目机构 - 能源（ARPA-E）组织的大规模合成和实际功率网络来验证所提出的方法的性能。由于许多先前的作品着重于小型系统，并且没有使用经过验证的公开数据集对基准进行基准测试，因此我们旨在为SCOPF提供一种实用的解决方案，该解决方案已被证明可以在现实尺寸的（30,000辆公交车）网络上实现良好的性能。
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.
