论文标题
功率网格问题中的空间内点方法降低
Reduced-Space Interior Point Methods in Power Grid Problems
论文作者
论文摘要
由于关键的环境问题，电力系统必须适应可再生生成的大量渗透水平，这需要智能的方法来控制电网。相关的最佳控制问题是大规模的非线性优化问题，其中有多达数亿个变量和约束。内点方法在计算上棘手，主要是由于大型线性系统的解决方案。 本文档通过应用减少空间Quasi-Newton IPM解决了安全性最佳功率流问题期间内部点方法的计算瓶颈，由于邻接方法中固有的并行性，该材料可以利用高性能计算机。在解决（安全约束）最佳功率流问题方面，降低空间IPM方法和伴随方法是一种新颖的方法。这些以前是在PDE受限的优化中使用的。呈现的方法适用于梯度评估期间伴随方法中固有的并行性引起的高性能体系结构，因为各个偶然性方案是由独立的约束集建模的。对性能和收敛进行初步评估以研究降低的空间方法。
Due to critical environmental issues, the power systems have to accommodate a significant level of penetration of renewable generation which requires smart approaches to the power grid control. Associated optimal control problems are large-scale nonlinear optimization problems with up to hundreds of millions of variables and constraints. The interior point methods become computationally intractable, mainly due to the solution of large linear systems. This document addresses the computational bottlenecks of the interior point method during the solution of the security constrained optimal power flow problems by applying reduced space quasi-Newton IPM, which could utilize high-performance computers due to the inherent parallelism in the adjoint method. Reduced space IPM approach and the adjoint method is a novel approach when it comes to solving the (security constrained) optimal power flow problems. These were previously used in the PDE-constrained optimization. The presented methodology is suitable for high-performance architectures due to inherent parallelism in the adjoint method during the gradient evaluation, since the individual contingency scenarios are modeled by independent set of the constraints. Preliminary evaluation of the performance and convergence is performed to study the reduced space approach.
