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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mathur, Hitesh Dutt | - |
dc.date.accessioned | 2023-02-16T06:03:36Z | - |
dc.date.available | 2023-02-16T06:03:36Z | - |
dc.date.issued | 2006 | - |
dc.identifier.uri | https://ieeexplore.ieee.org/abstract/document/1632619 | - |
dc.identifier.uri | http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9255 | - |
dc.description.abstract | This paper presents summaries of novel approaches of artificial intelligence (AI) techniques, like fuzzy logic, artificial neural network (ANN), hybrid fuzzy neural network (HFNN), genetic algorithm (GA) for the load frequency control of electrical power system. The limitations of conventional controls such as proportional, integral and derivative are slow and lack of efficiency in handling system nonlinearities. Since high frequency deviation may lead to system collapse, this necessitates an accurate and fast acting controller to maintain the constant nominal system frequency. The intelligent controllers are used for load frequency control for the single area system, multi area interconnected system. The performance of intelligent controllers with the conventional controllers has been thoroughly compared and analyzed | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.subject | EEE | en_US |
dc.subject | Frequency control | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Control systems | en_US |
dc.subject | Artificial Neural Networks | en_US |
dc.subject | Hybrid power systems | en_US |
dc.subject | Fuzzy logic | en_US |
dc.subject | Fuzzy neural networks | en_US |
dc.title | A comprehensive analysis of intelligent controllers for load frequency control | en_US |
dc.type | Article | en_US |
Appears in Collections: | Department of Electrical and Electronics Engineering |
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