电力系统自动化Issue(22)：90-97,8.DOI:10.7500/AEPS20150126012
基于GPU的分块约化算法在小干扰稳定分析中的应用
Application of GPU-based Block Reduction Algorithm in Power System Small-signal Stability Analysis
摘要
Abstract
To enhance the computational efficiency of complete eigenvalue analysis in power system small-signal stability analysis,the parallelization of upper Hessenberg reduction algorithm in the QR method is studied.A block reduction algorithm is utilized to integrate the floating-point operations into high-level basic linear algebraic subprograms (BLAS).The block reduction algorithm is parallelized on hybrid CPU/GPU (graphic processing unit) system and applied to the complete eigenvalue analysis of large-scale power system small-signal stability analysis.Simulation results show that,compared with multi-core CPU parallelization,the GPU-based block upper Hessenberg reduction algorithm is able to obtain a speed-up ratio up to 5 times the original.The overall computing speed of the complete eigenvalue analysis,including the method proposed, has achieved remarkable acceleration improvement.The applicability of the QR method to large-scale power system simulation analysis is increased.关键词
电力系统/小干扰稳定分析/QR算法/并行计算/图形处理器/分块算法Key words
power system/small-signal stability analysis/QR method/parallel computation/graphic processing unit(GPU)/block algorithm引用本文复制引用
张逸飞,严正,赵文恺,曹路,李建华..基于GPU的分块约化算法在小干扰稳定分析中的应用[J].电力系统自动化,2015,(22):90-97,8.基金项目
国家电网公司大电网重大专项资助项目(SGCC-MPLG018-2012) （SGCC-MPLG018-2012）
高等学校博士学科点专项科研基金资助项目(20120073110020)。This work is supported by State Grid Corporation of China,Major Projects on Planning and Operation Control of Large Scale Grid (No.SGCC-MPLG018-2012) and Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP)of China(No.20120073110020) （20120073110020）
