On-line Voltage Stability Assessment by a New Neural Network
Publish place: 14th International Power System Conference
Publish Year: 1378
Type: Conference paper
Language: English
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PSC14_120
Index date: 21 September 2007
On-line Voltage Stability Assessment by a New Neural Network abstract
Voltage stability problems have been one of the major concerns for electric utilities as a result of system heavy loading. This paper reports on an investigation on the application of a new neural network (NN) in on-line voltage stability assessment. The proposed NN is a functional link net with an efficient functional expansion model for learning. This NN is used for estimation of voltage stability margins (VSM). A comparison between the proposed NN and a multi-layer perceptron (MLP) with standard error back-propagation learning (EBPL) is presented, which indicates efficiency of this NN. Based on the energy method, a direct mapping relation between system loading onditions and the VSMs is set up via the designed NN. A systematic method for selecting the NN's input variables was developed using sensitivity analysis. The proposed method has been tested on the WEE test systems and a portion of the Iran's power system network. Obtained results confirm the validity of thedeveloped approach.
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On-line Voltage Stability Assessment by a New Neural Network authors
NIMA AMJADY
National Dispatching Department, Tavanir, Tehran, Iran
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