Adaptive neuro-fuzzy estimation of diffuser effects on wind turbine performance

Vlastimir Nikolić, Dalibor Petković, Shahaboddin Shamshirband () and Žarko Ćojbašić

Energy, 2015, vol. 89, issue C, 324-333

Abstract: Wind power is generating interest amongst many countries to produce sustainable electrical power. It is well known that the main drawback of wind power is the inherent variable behavior of wind speed. Significant research has been carried out to improve the performance of the wind turbines and establish the power system stability. As power output is proportional to the cubic power of the incident airspeed, any small increase in the incident wind yields a large increase in the energy output. One of the more promising advanced concepts for overcoming the inherent variable behavior of wind speed is the DAWT (diffuser-augmented wind turbine). The diffuser or flanged diffuser generates separation regions behind it, where low-pressure regions appear to draw more wind through the rotors compared to a bare wind turbine. Thus, the output power of the DAWT is much larger than for a unshrouded turbine. To estimate rotor performance of the diffuser-augmented wind turbine, this paper constructed a process which simulates the power output, torque output and rotational speed of the rotor in regard to diffuser effect and wind input speed with ANFIS (adaptive neuro-fuzzy) method. This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated.

Keywords: Ducted wind turbine; Shrouded wind turbine; Diffuser augmented wind turbine; Neuro-fuzzy; ANFIS (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544215007483
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:89:y:2015:i:c:p:324-333

DOI: 10.1016/j.energy.2015.05.126

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().