利用同步相量数据有效识别母线分裂事件
Efficient Identification of Bus Split Events Using Synchrophasor Data
摘要：
准确的电网拓扑信息对于电力系统的日常运行至关重要，而同步相量数据的日益增长的可用性提供了实时识别拓扑变化的机会。母线分裂事件的识别，其中变电站成为电气断开，是维护电力系统的安全变得越来越重要。本文的目的是提供一个有效的建模和监测框架总线分裂事件，通过使用一个简洁的总线分支表示。首先进行线性灵敏度分析，以快速评估此类事件对电网范围的影响。此外，同步相量数据使能识别问题制定通过匹配总线相位角（和可能的线路流量）的变化。为了解决所得到的双线性乘法涉及的二进制连接变量，麦考密克松弛技术被利用，以获得一个等效的混合整数线性规划重新制定，是有效地可解的。IEEE 14节点和300节点系统的数值研究表明，所提出的识别算法的有效性和效率的实时实现。
英文摘要：
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.
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