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新能源电力系统细粒度并行与多速率电磁暂态仿真

王啟国 徐晋 汪可友 周建其 樊涛

电力系统自动化2024,Vol.48Issue(3):113-121,9.
电力系统自动化2024,Vol.48Issue(3):113-121,9.DOI:10.7500/AEPS20230426002

新能源电力系统细粒度并行与多速率电磁暂态仿真

Fine-grained Parallel and Multi-rate Electromagnetic Transient Simulation for Power System with Renewable Energy

王啟国 1徐晋 1汪可友 1周建其 2樊涛3

作者信息

  • 1. 电力传输与功率变换控制教育部重点实验室(上海交通大学),上海市 200240
  • 2. 国网浙江省电力有限公司嘉兴供电公司,浙江省嘉兴市 314000
  • 3. 国家电网有限公司数字化工作部,北京市 100032
  • 折叠

摘要

Abstract

With the rapid development of renewable energy,the types of power system equipment are increasing,and the oscillation characteristics are more complex,which puts forward higher requirements on accuracy and efficiency of the electromagnetic transient simulation.A fine-grained modeling method for the power system with renewable energy is proposed based on the latency insertion method(LIM)which is used in the design of large-scale integrated circuits.Combined with the resource advantages of the graphics processor unit(GPU),the parallel solution of the algorithm is realized.The proposed method can decouple the traditional power grid and the power electronic equipment.The step sizes of sub-systems can be obtained according to the mixed numerical stability criterion and the local truncation error.Then,the multi-rate simulation of the power system with renewable energy is realized by interpolation.Finally,based on the GPU hardware platform,an improved 39-node system with renewable energy integration is taken as a case to verify the accuracy of the proposed method,and its advantages of simulation efficiency are verified by the simulation of systems with different scales and different combinations of step sizes.

关键词

可再生能源/电力系统/电磁暂态仿真/并行计算/细粒度仿真/多速率仿真/延迟插入法/图形处理器

Key words

renewable energy/power system/electromagnetic transient simulation/parallel computing/fine-grained simulation/multi-rate simulation/latency insertion method/graphics processor unit

引用本文复制引用

王啟国,徐晋,汪可友,周建其,樊涛..新能源电力系统细粒度并行与多速率电磁暂态仿真[J].电力系统自动化,2024,48(3):113-121,9.

基金项目

国家重点研发计划资助项目(2022YFE0105200). 本文研究得到国网浙江省电力有限公司嘉兴供电公司项目(5211JX230004)的资助,谨此致谢! This work is supported by National Key R&D Program of China(No.2022YFE0105200). (2022YFE0105200)

电力系统自动化

OA北大核心CSTPCD

1000-1026

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