Parallel power flow solutions using a biconjugate gradient algorithm and a Newton method: A GPU-based approach

Optimal power flow based on parallel metaheuristics for graphics processing units

“…Like ours, there exist some implementations on GPUs that also use sparse matrices such as in [39][40][41]. However, these cannot be used here as they are limited to the solution of the linear system and do not consider the other operations involved in the PF analysis such as building the admittance matrix, building the Jacobian matrix or computing the bus complex power injection.…”

“…However, these cannot be used here as they are limited to the solution of the linear system and do not consider the other operations involved in the PF analysis such as building the admittance matrix, building the Jacobian matrix or computing the bus complex power injection. Finally, the approach we selected based on [35] also has the advantage of exploiting a much high level of parallelism compared to [36][37][38][39][40][41] as it is specially designed for the concurrent evaluation of a large number of networks which is critical to the development of a fast OPF solver as we just explained it.…”

A novel GPU-accelerated strategy for contingency screening of static security analysis

“…In order to reduce the SLS solving time, Refs. [4][5][6][7][8][9][10] studied the GPU-accelerated strategies for common SLS solving algorithms, such as LU factorization, conjugate gradient (CG) iteration method, Jacobi iteration and multifrontal method. In those literatures, 3-10 times speedup has been reported.…”

Massive Jacobi power flow based on SIMD-processor

“…Another approach for accelerating a power flow was published in [5], where Gauss-Jacobi and Newton-Raphson algorithms are used, with a speed-up of 10 times in a largescale system. A Newton method and a biconjugate gradient algorithm are described in [6]. This author parallelizes one power flow obtaining an improvement of 2.1 times.…”

“…Additionally, in [6] Amdahl's law is used to establish an acceleration limit in the load flow parallelization.…”