Paper Info
Title
Adaptive intelligent hydro turbine speed identification with water and random load disturbances
Abstract
In this paper, the hydro power plant model (with penstock-wall elasticity and compressible water column effect) is simulated at random load disturbance variation with output as turbine speed for random gate position as input. The multilayer perceptron neural network (i.e. NNARX) and fused neural network and fuzzy inference system (i.e. ANFIS) for identification of turbine speed as output variable are reported. Emphasis is put on obtaining a generalized model, using (i) NNARX model and (ii) ANFIS model with membership functions defined by subtractive clustering for plant model representation under different values of water time constant. The comparative performance study between the two approaches is also addressed. In the end of the paper, an application of adaptive noise cancellation based on ANFIS model to identify the turbine speed dynamics is also discussed.
Year
DOI
Venue
2007
10.1016/j.engappai.2006.11.014
Eng. Appl. of AI
Keywords
Field
DocType
fused neural network,anfis model,adaptive intelligent hydro turbine,nnarx model,hydro power plant model,compressible water column effect,turbine speed dynamic,plant model representation,generalized model,random load disturbance,turbine speed,multilayer perceptron neural network,speed identification,membership function,neuro fuzzy,hydro power plant,time constant,noise cancellation,adaptive,modeling,multilayer perceptron,neural network
Compressibility,Neuro-fuzzy,Computer science,Artificial intelligence,Turbine,Active noise control,Adaptive neuro fuzzy inference system,Artificial neural network,Hydroelectricity,Time constant,Machine learning
Journal
Volume
Issue
ISSN
20
6
Engineering Applications of Artificial Intelligence
Citations 
PageRank 
References 
6
0.56
7
Authors
3
Name
Order
Citations
PageRank
Nand Kishor17814.41
S. P. Singh25314.55
A. S. Raghuvanshi392.12