Voltage ranking using artificial neural network
Voltage ranking attempts to rank busbar voltage deviations from their normally accepted security margins based on a set of performance indices (PI), without performing a full load flow. Existing methods suffer from either masking effects or long computation time. In this paper, an artificial neural...
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| Veröffentlicht in: | Compel 1999-12, Vol.18 (4), p.587-599 |
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| container_title | Compel |
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| creator | Lo, K.L. Luan, W.P. Given, M. Macqueen, J.F. Ekwue, A.O. Chebbo, A.M. |
| description | Voltage ranking attempts to rank busbar voltage deviations from their normally accepted security margins based on a set of performance indices (PI), without performing a full load flow. Existing methods suffer from either masking effects or long computation time. In this paper, an artificial neural network method is proposed for voltage ranking. Counterpropagation network (CPN) has been employed to overcome the problems listed above. A variety of input features are used with the aim of lowering the dimension of the proposed ANN to make it applicable for large power systems. The method is tested on two example systems, a five-bus system and a 71-bus system with very encouraging results. |
| doi_str_mv | 10.1108/03321649910296618 |
| format | Article |
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Existing methods suffer from either masking effects or long computation time. In this paper, an artificial neural network method is proposed for voltage ranking. Counterpropagation network (CPN) has been employed to overcome the problems listed above. A variety of input features are used with the aim of lowering the dimension of the proposed ANN to make it applicable for large power systems. 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| source | Emerald A-Z Current Journals |
| subjects | Accuracy Algorithms Artificial neural networks Buses Electrical engineering Feature selection Networks Neural networks Neurons Propagation Ratings & rankings Studies Violations Voltage |
| title | Voltage ranking using artificial neural network |
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