摘要
设计了一个多输入单输出的模糊神经网络,通过计算带静止无功补偿器电力系统的负荷能力极限,对系统的电压稳定性进行评估,有功与无功负载的不确定性、有功与无功发生器、母线电压以及SVC的参数都被考虑进来。首先,Kohonen自组织变换聚类所有节点的有功和无功负荷来减少输入量个数,这样就限定了网络的大小减少了计算量。其次,采用一种混合非线性隶属度函数,将输入变量模糊化。最后,设计一个模糊输入的三层前馈神经网络进行训练评定电力系统的负荷能力裕度。
In this paper, multi input amd single output fuzzy neural network is developed for voltage stability evaluation of the power systems with SVC by calculating the loadability margin. Uncertainties of real and reactive loads, real and reactive generations, bus voltages and SVC parameters are taken into account. In the first stage, Kohonen self-organizing map is developed to cluster the real and reactive loads at all the buses to reduce the input features, thus limiting the size of the network and reducing computational burden. In the second stage, combination of different non-linear membership functions is proposed to transform the input variables into fuzzy domains. Then a three-layered feed forward neural network with fuzzy input variables is developed to evaluate the loadability margin.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2009年第11期40-44,53,共6页
Power System Protection and Control
