BCU Classifiers for On-line Dynamic Contingency of Electric Power Systems: Design, Developments and Applications

ECS-9812139 Chiang这项建议提出了一种在线DSA的体系结构，并试图开发一种基于直接法的动态事故筛选方案，以使在线DSA适用于当前或近期的电力系统运行环境。特别是，这项提议将开发BCU分类器，以满足在线DSA的以下基本要求：(1)(可靠性衡量)绝对捕获不稳定的意外情况；即不遗漏不稳定的(单摆动或多摆动)意外事件。换言之，捕获的不稳定或有事件与实际临界或有事件的比率为1。(2)(效率度量)筛选稳定或有事件的高收益，即检测到的稳定或有事件与实际稳定或有事件的比率尽可能接近1。(3)(在线计算)几乎不需要离线计算和/或调整，以满足不断变化和不确定的运行条件。(4)(速度度量)高速，即对每个应急情况进行快速分类。(5)(性能衡量)针对电力系统运行条件变化的稳健性能。为了满足这五个基本要求，我们建议首先执行以下任务：(1)对数值指数的发展进行一些理论研究，(2)构造改进的数值能量函数，(3)发展更可靠的BCU方法的数值实现，(4)开发用于检测偶然的、无效的数值能量函数的数值指数，以及(5)开发用于检测偶然的控制UEPP的数值指数。收敛问题。然后，将这些任务的结果集成到BCU分类器的初步版本中，形成改进版本的BCU分类器，该版本将满足执行在线动态事故筛选的五个要求。该项目的成功与否直接影响到在当前或不久的将来电力系统运行环境下进行在线DSA的可行性。

ECS-9812139 Chiang This proposal presents an architecture for on-line DSA and seeks to develop a dynamic contingency screening scheme based on the direct method to make on-line DSA feasible for current or near future power system operating environments. In particular, this proposal will develop BCU classifiers to satisfy the following essential requirements for on-line DSA: (1) (reliability measure) absolute capture of unstable contingencies; i.e. no unstable (single-swing or multi-swing) contingencies are missed. In other words, the ratio of the captured unstable contingencies to the actual critical contingencies is 1. (2) (efficiency measure) high yield of screening out stable contingencies, i.e. the ratio of the stable contingencies detected to the actual stable contingency cases is as close to 1 as possible. (3) (on-line computation) little need of off-line computations and/or adjustments in order to meet with the constantly changing and uncertain operating conditions. (4) (speed measure) high speed, i.e. fast classification for each contingency case. (5) (performance measure) robust performance with respect to changes in power system operating conditions. To meet the five essential requirements, we propose to first perform the following tasks: (1) to conduct some theoretical study for development of numerical indices, (2) to construct improved numerical energy functions, (3) to develop a more reliable numerical implementation of the BCU method, (4) to develop numerical indices for detecting the occasional, invalid numerical energy functions, and (5) to develop numerical indices to detect the occasional controlling u.e.p. convergence problem. Then, the results of these tasks will be integrated into the preliminary version of BCU classifiers to form an improved version of BCU classifiers which will satisfy the five requirements for performing on-line dynamic contingency screening. The success of this proposed project has a direct impact on making the task of performing on-line DSA feasible for current or near-future power system operating environments.