We present a decomposition approach for obtaining good feasible solutions for the security-constrained alternating-current optimal power flow (SCACOPF) problem at an industrial scale and under real-world time and computational limits. The approach aims at complementing the existing body of literature on bounding the problem via convex relaxations. It was designed for the participation in ARPA-E's Grid Optimization (GO) Competition Challenge 1. The challenge focused on a near-real-time version of the SCACOPF problem where a base case operating point is optimized taking into account possible single-element contingencies, after which the system adapts its operating point following the response of automatic frequency drop controllers and voltage regulators. Our solution approach for this problem relies on state-of-the-art nonlinear programming algorithms and employs nonconvex relaxations for complementarity constraints, a specialized two-stage decomposition technique with sparse approximations of recourse terms, and contingency ranking and pre-screening. The paper also outlines the salient features of our implementation, such as fast model functions and derivatives evaluation, warm-starting strategies, and asynchronous parallelism. We discuss the results of the independent benchmark of our approach done by ARPA-E's GO team in Challenge 1, which found that our methodology consistently produces high quality solutions across a wide range of network sizes and difficulty. Finally, we conclude by outlining potential extensions and improvements of our methodology.
翻译:1. 我们提出了一个分解方法,以便在工业规模和现实世界时间和计算限度下,为安全受限制的交替最佳电力流动问题找到可行的妥善解决办法,在工业规模和现实世界时间和计算限度下,在工业规模和现实世界时间和电压调控器的响应下,为获得安全受限制的最佳电流问题找到可行的可行解决办法; 这种方法旨在补充关于通过Convex放松将问题捆绑起来的现有文献; 旨在参与ARPA-E网最佳化(GO)竞争挑战1 。 挑战侧重于SCCOPF问题的近实时版本,即考虑到可能的单一因素意外事件,使一个基本案件运行点得到优化,之后,系统在自动频率降压控制器和电压调控器的响应下,调整其运作点。 我们解决这一问题的方法依靠最新的非线性非线性编程编程算算法,利用零星两阶段专用的分解配置技术,在追索条件、应急分级和预检中进行优化。 文件还概述了我们执行工作的突出特点,例如快速模型功能和衍生物评估,启动战略,以及不断调整的AR-A系统升级的升级方法,我们通过平行的升级方法,在最后制定一个核心的升级方法中,从而得出了我们最终的升级的方法。