Selection and development of neural network architecture for finding the maximum mechanical power of the propeller.

Abstract

An example of using a neural network for finding the value of the point of maximum power in a power supply system with an alternative energy source (wind generator) is given in this work. The main feature of the built neural network is its structure. Neural network-multilayer (the first two layers have the activation function - hyperbolic tanges, and the third - a linear function). For the successful integration of the network into the system was considered the process of learning NM, construction of it is carried out in the application package Matlab. In this paper, a neural network was developed and modeled to find the maximum value of the mechanical power of the wind wheel. This network is multi-layered; weight coefficients and bias obtained by experiment were used for construction. This network takes into account the change in coefficients, which means it can be retrained. This property is very useful when an error occurs in the real equipped, caused by the aging of the equipment.

Authors and Affiliations

Dmytro Ostrenko, Oleksandr Kollarov

Keywords

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  • EP ID EP660518
  • DOI -
  • Views 191
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How To Cite

Dmytro Ostrenko, Oleksandr Kollarov (2018). Selection and development of neural network architecture for finding the maximum mechanical power of the propeller.. Наукові праці Донецького Національного Технічного Університету серія: Електротехніка і Енергетика, 1(1), 63-67. https://europub.co.uk/articles/-A-660518