论文标题
有效使用同步量数据对总线分裂事件进行有效识别
Efficient Identification of Bus Split Events Using Synchrophasor Data
论文作者
论文摘要
准确的网格拓扑信息对于常规电源系统操作至关重要，而同步声数据的越来越多的可用性为实时识别拓扑变化提供了机会。识别变电站发生电离的总线拆分事件，对于维持电力系统的安全性变得越来越重要。本文旨在通过使用简洁的公交分支表示形式为总线拆分事件提供有效的建模和监视框架。首先进行线性灵敏度分析以快速评估此类事件的网格影响。此外，通过匹配总线相角（以及可能的线流）的变化，可以提出同步量的数据启用识别问题。为了解决涉及二元连通性变量的结果双线性乘法，麦考米克松弛技术被杠杆化以获得等效的混合组合线性程序重新印度，可有效解决。关于IEEE 14总线和300个总线系统的数值研究证明了拟议的识别算法对实时实施的有效性和效率。
Accurate grid topology information is of paramount importance for routine power system operations, while the growing availability of synchrophasor data offers the opportunity to identify topology changes in real time. Identification of bus split events, where the substation becomes electrically disconnected, is becoming increasingly important for maintaining the security of power systems. This paper aims to provide an efficient modeling and monitoring framework for bus split events by using a concise bus-branch representation. The linear sensitivity analysis is first performed to quickly evaluate the grid-wide impact of such events. Furthermore, the synchrophasor data enabled identification problem is formulated by matching the changes in bus phase angles (and possibly line flows). To address the resultant bilinear multiplication involving the binary connectivity variables, the McCormick relaxation technique is leveraged to attain an equivalent mixed-integer linear program reformulation that is efficiently solvable. Numerical studies on the IEEE 14-bus and 300-bus systems demonstrate the validity and efficiency of the proposed identification algorithm towards real-time implementation.
