提出并建立了在线评估电力系统安全性的方法.首先建立电力系统元件的模糊隶属度函数,获取其安全隶属度(SMG)；然后通过建立的2阶模糊控制器,分别得到发电方,输电方和负荷部分的最小安全隶属度( SSMG),最后综合输出全局模糊指标.其中运用梯形模糊集求取系统关键元件模糊隶属度,不同于针对最脆弱系统状态进行离线筛选的传统方法,适应电力系统多样性特点,能连续不断量化电力系统的安全状态,可根据潮流实时数据、状态估计和潮流分析程序对系统安全水平进行不断跟踪.全局模糊指标能比较直观地使系统运行员识别不安全状态,连续监控系统实际运行到不安全状态的距离.对IEEE30节点系统进行的仿真计算证明了所提出模型和算法的有效性.%The paper proposes a new on-line assessment method for power system security. First, the fuzzy membership function of power system components is established to obtain each security membership grade (SMG) value; and then the proposed two first-order fuzzy controllers are used to get the smallest security membership grade (SSMG) of the segment of generation, transmission and load nodes, finally comprehensively output the global fuzzy index. Trapezoid fuzzy sets are used for obtaining the fuzzy membership of key components of system. It can adapt to the diversity characteristics of power system, which is different from the traditional method which screens offline according to the most vulnerable systems. It can continuously quantify the state of power system security and can track the system safety level continuously according to the flow real-time data, state estimation and power flow analysis program. The global fuzzy index let the system operator vividly identify the unsafe condition and continuously monitor the distance between the real state and unsafe state. Simulation results of IEEE30-bus system prove that both the proposed model and method are effective.
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