Performance neuro-fuzzy for power system fault location
This paper is proposed for power systems fault location using Neuron Fuzzy (NF). The NF consists of approaching architecture Neural Network and Fuzzy Sets. The Neural Network is being responsible for detecting faults involving a limited number of components. The fuzzy sets represented diagram consis...
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| Format: | Article |
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2013
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| _version_ | 1796857977890668544 |
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| author | Azhari Zakri, Azriyenni Mustafa, Mohd. Wazir |
| author_facet | Azhari Zakri, Azriyenni Mustafa, Mohd. Wazir |
| author_sort | Azhari Zakri, Azriyenni |
| collection | ePrints |
| description | This paper is proposed for power systems fault location using Neuron Fuzzy (NF). The NF consists of approaching architecture Neural Network and Fuzzy Sets. The Neural Network is being responsible for detecting faults involving a limited number of components. The fuzzy sets represented diagram consisting of three node, that are; node1 for the system components, and node 2 for relays, node 3 for the circuit breakers. The NF uses primary and backup information to protective devices and to set generate training. The NF can be retained and estimated effectively. The software was conducted to show the effectiveness of the proposed NF is tested by using 13 bus test system. |
| first_indexed | 2024-03-05T19:05:51Z |
| format | Article |
| id | utm.eprints-40986 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:05:51Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | utm.eprints-409862017-08-30T07:39:08Z http://eprints.utm.my/40986/ Performance neuro-fuzzy for power system fault location Azhari Zakri, Azriyenni Mustafa, Mohd. Wazir TK Electrical engineering. Electronics Nuclear engineering This paper is proposed for power systems fault location using Neuron Fuzzy (NF). The NF consists of approaching architecture Neural Network and Fuzzy Sets. The Neural Network is being responsible for detecting faults involving a limited number of components. The fuzzy sets represented diagram consisting of three node, that are; node1 for the system components, and node 2 for relays, node 3 for the circuit breakers. The NF uses primary and backup information to protective devices and to set generate training. The NF can be retained and estimated effectively. The software was conducted to show the effectiveness of the proposed NF is tested by using 13 bus test system. 2013 Article PeerReviewed Azhari Zakri, Azriyenni and Mustafa, Mohd. Wazir (2013) Performance neuro-fuzzy for power system fault location. International Journal of Engineering and Technology (IJET), 3 (4). pp. 497-501. ISSN 2049-3444 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Azhari Zakri, Azriyenni Mustafa, Mohd. Wazir Performance neuro-fuzzy for power system fault location |
| title | Performance neuro-fuzzy for power system fault location |
| title_full | Performance neuro-fuzzy for power system fault location |
| title_fullStr | Performance neuro-fuzzy for power system fault location |
| title_full_unstemmed | Performance neuro-fuzzy for power system fault location |
| title_short | Performance neuro-fuzzy for power system fault location |
| title_sort | performance neuro fuzzy for power system fault location |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| work_keys_str_mv | AT azharizakriazriyenni performanceneurofuzzyforpowersystemfaultlocation AT mustafamohdwazir performanceneurofuzzyforpowersystemfaultlocation |