.png){kind=icon}
Return
Fully GPU‐based electromagnetic transient simulation considering large‐scale control systems for system‐level studies
.png){kind=icon}
PRE
AI
DOI：10.1049/iet-gtd.2016.2078.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
As more generators and loads are integrated by power electronic converters with complicated controls, electromagnetic transients (EMTs) simulation becomes an important tool for studying dynamic characteristics of large‐scale power systems. To accelerate system‐level EMT simulations, a fine‐grained parallel algorithm on graphics processing units (GPU) is proposed. By decomposing the computational models of the EMT simulation into heterogeneous, homogeneous and network solution computations, the simulations are mapped into three unified GPU kernels. To incorporate control signals and non‐linear features of electrical components, heterogeneous computations are formulated as layered direct acyclic graphs (LDAG) of primitive operations. An LDAG kernel is designed to carry out theses primitive operations efficiently by grouped threads. Then, homogeneous computations for state updates of electrical components are modelled as sets of fused multiply‐add (FMA) operations, which are concurrently processed by an FMA kernel. Moreover, a hybrid network solution kernel is designed to solve the network equations, which can adaptively select dense or sparse solvers. Large‐scale test systems are created and simulated on an NVIDIA K20x GPU. The results show that the proposed GPU‐based EMT simulations are accurate and achieve 10x speedups over the CPU‐based ones.
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
No journal information available
Organization
No organization information available
Cited Papers
No cited papers available