A parallel power flow algorithm for large-scale grid based on stratified path trees and its implementation on GPU

For the demand on fast power flow calculation for large-scale power grid analysis and energy management systems, a sparse matrix factorization algorithm for graphic processing unit (GPU) based on stratified path trees is proposed. By referring to the algorithm, the Newton-Raphson method for solving the power-flow problem is implemented on GPU. To improve the efficiency, the calculation of the right-hand side of equation and the Jacobian matrix, LU decomposition and forward-back substitution are implemented on GPU, which reduces the data transfer time between GPU and central processing unit (CPU). Then, considering the multi-level memory architecture with registers, cache and global memory, a special data structure is designed to decrease the latency of data access. Moreover, considering the feature of threads arrangement on GPU, the task allocation is optimized, while the efficiency of parallelism is improved. Finally, compared with the power flow calculation module of power system analysis software package (PSASP) ran on CPU, numerical simulation test is conducted. The results show that the more the nodes, the more advantages GPU will get. In the test on a system with 43 602 nodes, the program is able to provide a 5.172 times speed-up ratio, which proves the effectiveness and practicality of the algorithm proposed. ©2014 State Grid Electric Power Research Institute Press.