Efficient GPU-Based Electromagnetic Transient Simulation for Power Systems With Thread-Oriented Transformation and Automatic Code Generation

Abstract

Electromagnetic transients (EMT) simulation is the most accurate and intensive computation for power systems. Past research has shown the potential of accelerating such simulations using graphics processing units (GPUs). In this paper, an efficient GPU-based parallel EMT simulator is designed. Thread-oriented model transformations are first proposed for the electrical and control systems. Following the transformations, the electrical system is represented by connected networks of massive primitive electrical elements, the computations of which can be constructed as massive fused multiply-add operations and solutions to a linear equation. The control systems are represented by a layered directed acyclic graph with primitive control elements that can be dealt with using single-instruction-multiple-threads groups. Finally, code automation tools are designed to form the GPU kernels. Compared with past work, the proposed model transformations improve the degree of parallelism. Most importantly, the code automation tools improve computational efficiency by substantially reducing addressing and memory access, and render the implementation of the algorithm more general and convenient. Test systems of different sizes were created by connecting multiple IEEE 33-bus distribution systems and adding distributed generators. Simulations were performed on NVIDIA’s K20 $\times$ and P100 cards. The results indicate that the proposed method significantly accelerates EMT simulations compared with a CPU-based program. Real-time performance was also achieved under certain conditions.