NSF Young Investigator

目前正在提出两个项目。 第一个是在 稳健估计理论应用于 电力系统 安全监测和控制 电力系统依赖于可靠的数据 基地 不幸的是，在典型的电力系统中， 存在不良测量，参数误差， 和/或拓扑错误。 目前的工业 实践是使用加权最小二乘法 它不能容忍大的错误， 经常失败。 在这方面， 估计理论具有优势，但工作需要 使该方法切实可行。 之间 这些是需要进一步扩大 稀疏矩阵理论，并确定 适当的"高崩溃点"估计。 其他需要解决的问题包括实时 估计和最佳传感器位置。 第二个研究领域涉及使用 实时相量测量电压和 暂态稳定监测和控制，包括 动态安全分析与自动控制 在电力系统的紧急状态下。

Two projects are being proposed. The first is in the area of robust estimation theory as applied to power systems. Security monitoring and control of an electric power system depend on a reliable data base. Unfortunately, in a typical power system there are bad measurements, parameter errors, and/or topology errors. The present industry practice is to use a weighted least squares approach which has no tolerance for large errors and frequently fails. In this connection robust estimation theory has advantages but work needs to be done to make the method practical. Among these are the need to further the extension of the theory to sparse matrices and to determine appropriate "high breakdown point" estimators. Other issues to be addressed include real-time estimation and optimal sensor location. The second area of research concerns the use of real-time phasor measurements for voltage and transient stability monitoring and control, including dynamic security analysis and automatic control during an emergency state of a power system.