基于 FPGA 的 EMT 仿真初始化方法

IF 3.3 Q3 ENERGY & FUELS
Xin Ma;Xiao-Ping Zhang
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引用次数: 0

摘要

与其他现有的实时平台相比,FPGA 的投资成本更低,因此已成为提供实时电磁瞬态(EMT)解决方案的强大平台。由于时序限制和资源利用问题,现有的离线初始化方法无法直接应用于实时 FPGA。如果没有适当的初始化,就会导致基于 FPGA 的 EMT 仿真出现偏差,造成不准确的仿真结果。为了提供实时初始化,本文提出了四种基于 FPGA 的 EMT 初始化方法,即物理接口(方法 1)、信号声明(方法 2)、信号分配(方法 3)和系数(COE)文件(方法 4)。这四种方法的性能也进行了比较,其中方法 4 可以用最简单的代码即时初始化。为了提高硬件适应性,还针对地址序列、接口、更新模式和数据流制定了优化策略。为加速初始化,开发了软件到硬件的算法和结构,以自动处理不同拓扑结构的初始化数据源。案例研究表明,方法 2-4 都能在 FPGA 平台上成功初始化,而方法 4 则实现了最佳时序和路由性能。为了验证可扩展性,方法 4 被扩展到初始化 4 机 11 总线系统,并消除了显著误差,误差小于 5%,时序限制为 0.005 ns。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Initialization Methods for FPGA-Based EMT Simulations
FPGA has become a very powerful platform to provide real-time Electromagnetic Transient (EMT) solutions due to the much lower investment costs in comparison to the other existing real-time platform. Existing off-line initialization methods cannot be applied to real-time FPGA directly owing to timing constraints and resource utilization. Without appropriate initialization, it can lead to divergence for FPGA-based EMT simulations and cause inaccurate simulation results. To provide real-time initialization, this paper presents four initialization methods for FPGA-based EMT, namely, physical interface (Method 1), signal declaration (Method 2), signal assignment (Method 3) and Coefficient (COE) file (Method 4). The performance of these four methods are also compared, and Method 4 can initialize instantly with the simplest code. To improve hardware adaptability, optimized strategies are developed for address sequence, interface, update modes and dataflow. To accelerate initialization, software-to-hardware algorithm and structure are developed to automate initialization data sources for different topologies. Case study shows Method 2–4 can both initialize successfully on FPGA platform, while Method 4 achieves the best timing and routing performance. To verify scalability, Method 4 is expanded to initialize 4-machine 11-bus system and eliminate significant error to less than 5%, with a timing constraint of 0.005 ns.
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来源期刊
CiteScore
7.80
自引率
5.30%
发文量
45
审稿时长
10 weeks
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