Fast Newton-Raphson Power Flow Analysis Based on Sparse Techniques and Parallel Processing

被引：16

作者：

Ahmadi, Afshin ^{[1
]}

Smith, Melissa C. ^{[1
]}

Collins, Edward R. ^{[1
]}

Dargahi, Vahid ^{[3
]}

Jin, Shuangshuang ^{[2
]}

机构：

[1] Clemson Univ, Holcombe Dept Elect & Comp Engn, Clemson, SC 29634 USA

[2] Clemson Univ, Sch Comp, N Charleston, SC 29405 USA

[3] Univ Washington, Sch Engn & Technol, Tacoma, WA 98402 USA

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2022年 / 37卷 / 03期

基金：

美国国家科学基金会;

关键词：

Mathematical models; Newton method; Multicore processing; Voltage; Sparse matrices; Graphics processing units; Power systems; Parallel; multicore; sparse; power flow; newton-raphson; OpenMP; SIMD;

D O I：

10.1109/TPWRS.2021.3116182

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Power flow (PF) calculation provides the basis for the steady-state power system analysis and is the backbone of many power system applications ranging from operations to planning. The calculated voltage and power values by PF are essential to determining the system condition and ensuring the security and stability of the grid. The emergence of multicore processors provides an opportunity to accelerate the speed of PF computation and, consequently, improve the performance of applications that run PF within their processes. This paper introduces a fast Newton-Raphson power flow implementation on multicore CPUs by combining sparse matrix techniques, mathematical methods, and parallel processing. Experimental results validate the effectiveness of our approach by finding the power flow solution of a synthetic U.S. grid test case with 82,000 buses in just 1.8 seconds.

引用

页码：1695 / 1705

页数：11

共 30 条

[1] GPU-OpenCL accelerated probabilistic power flow analysis using Monte-Carlo simulation [J].