DocumentCode :
653617
Title :
Validation of artificial neural network based model of microturbine power plant
Author :
Sisworahardjo, N. ; El-Sharkh, M.Y.
Author_Institution :
Electr. Eng. Dept., Univ. of Tennessee Chattanooga, Chattanooga, TN, USA
fYear :
2013
fDate :
6-11 Oct. 2013
Firstpage :
1
Lastpage :
5
Abstract :
This paper introduces an artificial neural network (ANN) based model for microturbine (MT) power plant. Microturbines (MTs) as efficient combined power and heat sources demonstrate a high potential to meet users´ needs for distributed generation and microgrid applications. To understand and investigate the MT operation characteristics, a simple yet accurate model of the microturbine is essential. A detailed performance comparison between the GAST MT model and an ANN based model is presented. The ANN based model has three inputs and one output. The inputs are the control signal of power, speed, and temperature, and the outputs are the MT mechanical power. In this paper the MT is connected to a synchronous generator (SG) which is not included in the ANN model. The validation of the ANN based MT model indicates a close agreement between the outputs of the GAST and the proposed ANN based MT models.
Keywords :
cogeneration; distributed power generation; machine control; neural nets; synchronous generators; turbines; artificial neural network; combined power and heat sources; distributed generation; microgrid applications; microturbine power plant; power control signal; speed control signal; synchronous generator; temperature control signal; Artificial neural networks; Mathematical model; Rotors; Temperature control; Turbines; Voltage control; Artificial Neural Network; Distributed Generation; Dynamic Model; Microturbine; Simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industry Applications Society Annual Meeting, 2013 IEEE
Conference_Location :
Lake Buena Vista, FL
ISSN :
0197-2618
Type :
conf
DOI :
10.1109/IAS.2013.6682526
Filename :
6682526
Link To Document :
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