An Algorithm Suite for Computational Nonlinear Analysis of Power Systems

用于电力系统计算非线性分析的算法套件

• 批准号: 1016467
• 负责人: Harry Dankowicz
• 金额: $ 47.79万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1016467&HistoricalAwards=false
• 关键词: Algorithm; Suite; Computational; Nonlinear; Analysis

An Algorithm Suite for Computational Nonlinear Analysis of Power SystemsThis effort targets the original development of CNAPS, an innovative suite of numerical algorithms for continuation analysis of multi-segment trajectories in large-scale, nonlinear dynamical systems with multiple slow and fast timescales, coupled components, and with triggers, resets and switches. Continuation methods have proven very successful for analyzing system behavior of low-dimensional systems. In CNAPS, we aim to dramatically scale continuation methods to complex networked systems with hybrid system trajectories and tens of thousands of states, by developing new multiscale, multisegment, trajectory-discretization algorithms based on asynchronous collocation methods; developing new mesh adaptation algorithms suitable for the asynchronous collocation methods, which accommodate segment-specific discretization error bounds; and constructing domain decomposition methods particular to the network topology and the asynchronous collocation formulation, which enable efficient parallel execution.The core application of CNAPS considered in this multidisciplinary effort is modern power systems that include renewable sources of generation, specifically wind power, and newer forms of load, characterized by multiple coexisting time scales and trigger-induced switching behavior. Analysis of large-disturbance dynamic phenomena in such systems currently relies almost exclusively on forward simulation. While such tools may reveal complex behavior, they offer little help in the design process required to address unacceptable behavior, especially emerging phenomena associated with the increased use of power electronic converters. The development of CNAPS enables intelligent and efficient exploration of transient and steady-state responses of complex power systems, aimed at quantifying design and uncertainty margins for stable, faultless operation.

电力系统计算非线性分析的算法套件这项工作针对CNAPS的原始开发，CNAPS是一套创新的数值算法，用于大规模、具有多个慢和快时间尺度、耦合组件以及具有触发器、重置和开关的非线性动力系统中的多段轨迹的连续性分析。连续化方法在分析低维系统的系统行为方面已被证明是非常成功的。在CNAPS中，我们的目标是通过开发基于异步配置方法的新的多尺度、多分段、轨迹离散化算法，开发适合于异步配置方法的新的网格自适应算法，以适应特定于段的离散化误差界限，以及构建特定于网络拓扑和异步配置公式的区域分解方法，从而实现高效并行执行。在这项多学科努力中，CNAPS的核心应用是现代电力系统，包括可再生能源，特别是风电，以及具有多个共存时间尺度和触发诱导切换行为的新形式的负荷。目前对这类系统中的大扰动动态现象的分析几乎完全依赖于正向仿真。虽然这些工具可能会揭示复杂的行为，但它们在解决不可接受的行为所需的设计过程中几乎没有帮助，特别是与电力电子转换器的使用增加相关的新现象。CNAPS的开发使得能够智能、高效地探索复杂电力系统的暂态和稳态响应，旨在量化稳定、无故障运行的设计和不确定性裕度。