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    A fuzzy neural network approach to estimate PMSG based and DFIG based wind turbines' power generation
    (Institute of Electrical and Electronics Engineers Inc., 2017) Demirdelen, Tu?çe; Bakmaz, Emel; Tumay, Mehmet
    Neural networks and fuzzy systems are amalgamate their advantages and to eliminate its individual disadvantages. Neural networks have its computational characteristics of learning in the fuzzy systems and receive from them the interpretation and clarity of systems representation. Thus, the disadvantages of the fuzzy systems are fulfilled by the capacities of the neural networks. These techniques are complementary, which prove its use together. This is called fuzzy neural networks In this paper, a fuzzy neural network is applied to estimate PMSG based and DFIG based wind turbines' power generation. The obtained results showed that this model can be used to predict wind turbine power generation and performance analysis both two type turbines in a simple, reliable and accurate way. © 2017 IEEE.
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    Öğe
    A Fuzzy Neural Network Approach to Estimate PMSG based and DFIG based Wind Turbines' Power Generation
    (IEEE, 2017) Demirdelen, Tugce; Bakmaz, Emel; Tumay, Mehmet
    Neural networks and fuzzy systems are amalgamate their advantages and to eliminate its individual disadvantages. Neural networks have its computational characteristics of learning in the fuzzy systems and receive from them the interpretation and clarity of systems representation. Thus, the disadvantages of the fuzzy systems are fulfilled by the capacities of the neural networks. These techniques are complementary, which prove its use together. This is called fuzzy neural networks In this paper, a fuzzy neural network is applied to estimate PMSG based and DFIG based wind turbines' power generation. The obtained results showed that this model can be used to predict wind turbine power generation and performance analysis both two type turbines in a simple, reliable and accurate way.