Abstract
With the increasing requirements for power grid stability and reliability, improving the efficiency and accuracy of steady-state power system simulation has become an important research content. Considering the rapid development in the field of parallel computation, this paper introduced a fine-grained parallelism holomorphic embedding load flow method to accelerate steady-state power system simulation. First, GPU is selected as a computing hardware device due to its large amount of cores and shared memory. Second, this paper proposed two acceleration skills and algorithms to parallelize the holomorphic embedding load flow method. Compared with the original holomorphic embedding load flow method, it greatly improves efficiency while ensuring the accuracy of the calculation.
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