对故障敏感的负荷节点和关键节点的辨识

电力系统中许多大扰动都会导致系统负荷降低。对于系统调度员来说，了解和掌握系统中是否存在一些受故障扰动影响而负荷降低始终是最严重的节点、变电站，是相当有用的，同时也是一个具有挑战性的工作。文中将数据挖掘技术用于识别香港电力系统中与故障相关的最敏感的变电站。定义了量度负荷降低严重性程度的两个指标。基于数据统计分析找到了对故障扰动最敏感的变电站，其正确性得到了实际电力系统专家的证实。此外，通过对电压曲线的相关分析，找出了系统中的关键节点，对这些节点实施有效的电压调节，将有助于故障后敏感节点电压的恢复。

DETECTION OF SENSITIVE AND INFLUENTIAL BUSES IN A POWER SYSTEM SUBJECTED TO DISTURBANCES

Many kinds of major disturbances in a power system may lead to system load reduction. It is very useful but a challenging job for the system dispatcher to grasp the knowledge about whether there exist some substations whose load reductions resulting from the disturbances are consistently more serious than others. In this paper, data-mining technique is applied to a power system in Hong Kong to detect the substations most sensitive to the disturbances. Two indices are defined to measure the severity of load reduction. By statistical analysis, the most sensitive substations can be found, which have been confirmed to be the case by the experts working in the power system. Furthermore, based on the voltage-profile correlation analysis, the influential buses where the most effective voltage adjustment may be strategically applied to assist a sensitive bus to recover from the severe voltage fluctuation arising from the disturbance can be deduced.