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On-line voltage stability assessment using radial basis function network model with reduced input features
| Content Provider | Semantic Scholar |
|---|---|
| Author | Devaraj, D. Roselyn, J. Preetha |
| Copyright Year | 2011 |
| Abstract | 0142-0615/$ see front matter 2011 Elsevier Ltd. A doi:10.1016/j.ijepes.2011.06.008 ⇑ Corresponding author. E-mail addresses: deva230@yahoo.com (D. Devaraj (J. Preetha Roselyn). In recent years, voltage instability has become a major threat for the operation of many power systems. This paper presents an artificial neural network (ANN)-based approach for on-line voltage security assessment. The proposed approach uses radial basis function (RBF) networks to estimate the voltage stability level of the system under contingency state. Maximum L-index of the load buses in the system is taken as the indicator of voltage stability. Pre-contingency state power flows are taken as the input to the neural network. The key feature of the proposed method is the use of dimensionality reduction techniques to improve the performance of the developed network. Mutual information based technique for feature selection is proposed to enhance overall design of neural network. The effectiveness of the proposed approach is demonstrated through voltage security assessment in IEEE 30-bus system and Indian practical 76 bus system under various operating conditions considering single and double line contingencies and is found to predict voltage stability index more accurate than feedforward neural networks trained by back propagation algorithm and AC load flow. Experimental results show that the proposed method reduces the training time and improves the generalization capability of the network than the multilayer perceptron networks. 2011 Elsevier Ltd. All rights reserved. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.researchgate.net/profile/D_Devaraj4/publication/232382714_On-line_voltage_stability_assessment_using_radial_basis_function_network_model_with_reduced_input_features/links/0deec526b72b9612da000000.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Algorithm Artificial neural network Backpropagation Computer simulation Dimensionality reduction Email Feature selection Feedforward neural network Flow Generalization (Psychology) IBM Power Systems Instability Mail (macOS) Multilayer perceptron Mutual information Network model Nonlinear system Online and offline Radial (radio) Radial basis function network Software propagation voltage |
| Content Type | Text |
| Resource Type | Article |
