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的目标是 CNAPS 的原始开发，这是一套创新的数值算法，用于对具有多个慢速和快速时间尺度、耦合组件的大规模非线性动力系统中的多段轨迹进行连续分析，并带有触发器、重置和开关。事实证明，连续方法对于分析低维系统的系统行为非常成功。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、多段、轨迹离散化算法，将连续方法显着扩展到具有混合系统轨迹和数万个状态的复杂网络系统；开发适用于异步配置方法的新网格自适应算法，该算法适应特定于段的离散化误差范围；构建特定于网络拓扑和异步配置公式的域分解方法，从而实现高效的并行执行。在这项多学科工作中考虑的 CNAPS 的核心应用是现代电力系统，包括可再生能源发电，特别是风能和更新形式负载的特征是多个共存的时间尺度和触发引起的开关行为。目前，对此类系统中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提供任何帮助，特别是与电力电子转换器的使用增加相关的新兴现象。 CNAPS 的开发能够智能、高效地探索复杂电力系统的瞬态和稳态响应，旨在量化设计和不确定性裕度，以实现稳定、无故障的运行。