Transactions of China Electrotechnical Society  2018, Vol. 33 Issue (11): 2545-2553    DOI: 10.19595/j.cnki.1000-6753.tces.170477
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Eddy Current Loss Calculation of Dry-Type Air-Core Reactor Based on Radial Basis Function Neural Network
Chen Feng1, Wang Jiawei1, Wu Menghan2, Ma Xikui1
1.State Key Laboratory of Electrical Insulation and Power Equipment Xi’an Jiaotong University Xi’an 710049 China ;
2. Shanghai Sieyuan Electric Corporation Limited Shanghai 201100 China

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Abstract  

Based on numerical simulations,the structural parameters of dry-type air-core reactor were analyzed for the effect on eddy current losses. A unified model in engineering practice was then proposed to consider the fit scheme of winding cross section, the shape of conductor cross section, the airway width, and the number of layers per package. In order to improve the computational accuracy of reactor eddy current losses, a radial basis function(RBF) neural network model was established, in which the exponential function was determined as the activation function according to the relationship between the input and output variables. Moreover, an improved particle swarm algorithm for optimizing network parameters was presented. Numerical results indicate that the proposed model exhibits the highest precision and best computational performance. As a result, this model applies especially to the optimum design of dry-type air-core reactors.

Key wordsAC resistance      dry-type air-core reactor      radial basis function      neural network      particle swarm algorithm     
Received: 19 April 2017      Published: 13 June 2018
PACS: TM472  
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ChenFeng,WangJiawei,Wu Menghan等. Eddy Current Loss Calculation of Dry-Type Air-Core Reactor Based on Radial Basis Function Neural Network[J]. Transactions of China Electrotechnical Society, 2018, 33(11): 2545-2553.
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