Next generation electromagnetic transient simulation tool for large-scale power systems with detailed equipment models
用于大型电力系统的下一代电磁暂态仿真工具,具有详细的设备模型
基本信息
- 批准号:515592-2017
- 负责人:
- 金额:$ 6.67万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Collaborative Research and Development Grants
- 财政年份:2018
- 资助国家:加拿大
- 起止时间:2018-01-01 至 2019-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Electrical power systems are the largest man-made geographically distributed nonlinear structures that are**composed of a variety of equipment such as generators, transformers, transmission lines, customer loads,**spanning thousands of kilometers. Electromagnetic transient simulation (EMT) tools are used analyze and**solve major operational and control problems in power systems. EMT simulation of large-scale power systems**consumes so much computational power that parallel programming techniques are urgently needed in this area.**Currently available EMT simulation tools were designed to run on single-core CPUs, and therefore, cannot**take advantage of the multi-core CPUs and many-core graphics processors (GPUs) to manage computational**load. Massive-thread computing is one of the key developments that can increase the EMT computational**capabilities substantially when the processing unit has enough hardware cores. The aim of this project is to**develop a host of innovations towards implementing a parallel massive-thread EMT simulator for large-scale**power systems on the GPU and multi-core CPU hardware architectures. The main features of this work is to**design and build massive-thread models for various power system and power electronic components, finite**element and finite difference time domain models, efficient numerical algorithms, advanced data analysis and**visualization, and validation of the simulator.**The project results are expected to prove the feasibility of a functional parallel massive-thread EMT simulator**that can achieve computational speed-up in large-scale system simulation while using very detailed system**component models. The main beneficiary of this project will be Manitoba HVDC Research Centre (MHRC)**which can integrate the developed innovations into their flagship EMT simulation tool PSCAD/EMTDC. The**experienced team of highly qualified engineers trained in this project will contribute to the ongoing**advancement of the EMT simulation technology and may prove to be valuable future employees for MHRC.
电力系统是最大的人造地理分布的非线性结构,该结构由各种设备组成,例如发电机,变压器,传输线,客户负载,**跨越数千公里。电磁瞬态仿真(EMT)工具用于分析,并且**解决了电源系统中的主要操作和控制问题。大规模电源系统的EMT模拟**消耗了太多的计算能力,以至于在该领域迫切需要并行编程技术。多核CPU和多核图形处理器(GPU)的优势来管理计算**负载。大型线程计算是当处理单元具有足够的硬件核心时,可以大大增加EMT计算**功能的关键发展之一。该项目的目的是**开发大量创新,以在GPU和多核CPU硬件体系结构上实现平行的大规模电线EMT模拟器。这项工作的主要特征是**设计和建立针对各种电源系统和电源电源组件,有限的**元素和有限差差时域模型,有效的数值算法,高级数据分析和**可视化以及**可视化以及有限的差异时间域模型的大型线程模型**预计项目结果将证明功能并行巨大的线程EMT模拟器**的可行性可以实现大规模系统仿真中的计算加速,同时使用非常详细的系统**组件模型。该项目的主要受益人将是曼尼托巴HVDC研究中心(MHRC)**,它可以将开发的创新集成到其旗舰EMT仿真工具PSCAD/EMTDC中。经验丰富的高素质工程师团队接受了该项目的培训,将有助于EMT模拟技术的持续发展,并可能被证明是MHRC的宝贵未来员工。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Dinavahi, Venkata其他文献
Real-Time Hierarchical Neural Network Based Fault Detection and Isolation for High-Speed Railway System Under Hybrid AC/DC Grid
- DOI:
10.1109/tpwrd.2020.3022750 - 发表时间:
2020-12-01 - 期刊:
- 影响因子:4.4
- 作者:
Liu, Qin;Liang, Tian;Dinavahi, Venkata - 通讯作者:
Dinavahi, Venkata
Robust Forecasting-Aided State Estimation for Power System Against Uncertainties
针对不确定性的电力系统鲁棒预测辅助状态估计
- DOI:
10.1109/tpwrs.2019.2936141 - 发表时间:
2020-01-01 - 期刊:
- 影响因子:6.6
- 作者:
Wang, Yi;Sun, Yonghui;Dinavahi, Venkata - 通讯作者:
Dinavahi, Venkata
Multi-group particle swarm optimisation for transmission expansion planning solution based on LU decomposition
- DOI:
10.1049/iet-gtd.2016.0923 - 发表时间:
2017-04-20 - 期刊:
- 影响因子:2.5
- 作者:
Huang, Shengjun;Dinavahi, Venkata - 通讯作者:
Dinavahi, Venkata
FPGA-Based Real-Time Wrench Model of Direct Current Driven Magnetic Levitation Actuator
基于FPGA的直流驱动磁悬浮执行器实时扳手模型
- DOI:
10.1109/tie.2018.2811364 - 发表时间:
2018-12-01 - 期刊:
- 影响因子:7.7
- 作者:
Xu, Fengqiu;Lv, Yun;Dinavahi, Venkata - 通讯作者:
Dinavahi, Venkata
Direct Interval Forecast of Uncertain Wind Power Based on Recurrent Neural Networks
- DOI:
10.1109/tste.2017.2774195 - 发表时间:
2018-07-01 - 期刊:
- 影响因子:8.8
- 作者:
Shi, Zhichao;Liang, Hao;Dinavahi, Venkata - 通讯作者:
Dinavahi, Venkata
Dinavahi, Venkata的其他文献
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{{ truncateString('Dinavahi, Venkata', 18)}}的其他基金
Real-Time Digital Simulation and Control of Multi-Terminal Direct Current Grids
多端直流电网实时数字仿真与控制
- 批准号:
RGPIN-2017-03733 - 财政年份:2021
- 资助金额:
$ 6.67万 - 项目类别:
Discovery Grants Program - Individual
Next generation electromagnetic transient simulation tool for large-scale power systems with detailed equipment models
用于大型电力系统的下一代电磁暂态仿真工具,具有详细的设备模型
- 批准号:
515592-2017 - 财政年份:2020
- 资助金额:
$ 6.67万 - 项目类别:
Collaborative Research and Development Grants
Real-Time Digital Simulation and Control of Multi-Terminal Direct Current Grids
多端直流电网实时数字仿真与控制
- 批准号:
RGPIN-2017-03733 - 财政年份:2020
- 资助金额:
$ 6.67万 - 项目类别:
Discovery Grants Program - Individual
Real-Time Digital Simulation and Control of Multi-Terminal Direct Current Grids
多端直流电网实时数字仿真与控制
- 批准号:
RGPIN-2017-03733 - 财政年份:2019
- 资助金额:
$ 6.67万 - 项目类别:
Discovery Grants Program - Individual
Real-Time Digital Simulation and Control of Multi-Terminal Direct Current Grids
多端直流电网实时数字仿真与控制
- 批准号:
507961-2017 - 财政年份:2019
- 资助金额:
$ 6.67万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
Real-Time Digital Simulation and Control of Multi-Terminal Direct Current Grids
多端直流电网实时数字仿真与控制
- 批准号:
RGPIN-2017-03733 - 财政年份:2018
- 资助金额:
$ 6.67万 - 项目类别:
Discovery Grants Program - Individual
Real-Time Digital Simulation and Control of Multi-Terminal Direct Current Grids
多端直流电网实时数字仿真与控制
- 批准号:
507961-2017 - 财政年份:2018
- 资助金额:
$ 6.67万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
Next generation electromagnetic transient simulation tool for large-scale power systems with detailed equipment models
用于大型电力系统的下一代电磁暂态仿真工具,具有详细的设备模型
- 批准号:
515592-2017 - 财政年份:2017
- 资助金额:
$ 6.67万 - 项目类别:
Collaborative Research and Development Grants
Real-Time Digital Simulation and Control of Multi-Terminal Direct Current Grids
多端直流电网实时数字仿真与控制
- 批准号:
RGPIN-2017-03733 - 财政年份:2017
- 资助金额:
$ 6.67万 - 项目类别:
Discovery Grants Program - Individual
Real-Time Digital Simulation and Control of Multi-Terminal Direct Current Grids
多端直流电网实时数字仿真与控制
- 批准号:
507961-2017 - 财政年份:2017
- 资助金额:
$ 6.67万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
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