Stability of Large Scale Systems With Order Model Reduction

阶次模型缩减的大规模系统的稳定性

• 批准号: 9803055
• 负责人: M. Pai
• 金额: $ 12.5万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-08-15 至 2001-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9803055&HistoricalAwards=false
• 关键词: Stability; Large; Scale; Systems; Order

ECS-9803055 Pai Stability of large scale systems with model reduction is going to be important in the emerging new structure of power systems. Faster and reliable tools for computing dynamic available transfer capabilities (DATC) will be needed. This proposal addresses three aspects which will impact this area. Firstly, trajectory sensitivities which have yielded reliable results for dynamic security assessment (DSA) based on post-fault systems only, will now be extended to cover both faulted and post-fault dynamics. This will imply formulating dynamic sensitivity functions for systems of differential algebraic equations with discontinuities in the algebraic portion. This will enable the direct computation of sensitivities to critical clearing time as well to changes in load, tap settings, etc. A second objective is to find better and robust preconditioners for solving large sparse systems of the type Ax = b by iterative methods. This will then be used as part of the fast dynamic simulation algorithm using the simultaneous implicit method. Finally two new approaches to model reduction will be taken. First, we will use trajectory sensitivities of the nonlinear dynamic response to identify coherent generators. To date only linearized models around an operating point have been used for coherency grouping or some other heuristic criteria. Secondly, we will use the Krylov projector technique to develop reduced order dynamic models. This is a recently developed tool in numerical linear algebra for DAE systems.

ECS-9803055派 在电力系统新结构的出现中，模型降阶的大系统稳定性将是一个重要的问题。 需要更快、更可靠的工具来计算动态可用传输能力（DATC）。 这项建议涉及影响这一领域的三个方面。 首先，轨迹灵敏度，产生了可靠的结果，动态安全评估（DSA）的基础上故障后系统，现在将扩展到故障和故障后的动态。 这将意味着制定动态灵敏度函数的微分代数方程系统的代数部分中的不连续性。 这将使得能够直接计算对临界清除时间以及对负载、抽头设置等的变化的灵敏度。 第二个目标是找到更好的和强大的预处理器解决大型稀疏系统的类型Ax = B的迭代方法。 然后，这将被用作使用同时隐式方法的快速动态模拟算法的一部分。 最后，将采取两种新的方法来减少模型。 首先，我们将使用非线性动态响应的轨迹灵敏度来识别相干发电机。 到目前为止，只有线性模型周围的一个操作点已被用于一致性分组或一些其他的启发式标准。 其次，我们将使用Krylov投影技术来开发降阶动态模型。 这是一个最近开发的工具，在数值线性代数的DAE系统。