Validation of Artificial Neural Network Based Model of Microturbine Power Plant

被引：0
|
作者：
Sisworahardjo, N. [1 ]
El-Sharkh, M. Y. [2 ]
机构：
[1] Univ Tennessee, Dept Elect Engn, Chattanooga, TN 37403 USA
[2] Univ S Alabama, Dept Elect & Comp Engn, Mobile, AL USA
来源：
2013 IEEE INDUSTRY APPLICATIONS SOCIETY ANNUAL MEETING | 2013年
关键词：
Artificial Neural Network; Distributed Generation; Dynamic Model; Microturbine; Simulation; PEM FUEL-CELL;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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.
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页数：5
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