Compensating PQ problem using ANFIS-based unified power quality conditioner
by Mangapuram Vishnu Vardhan; P. Sangameswararaju
International Journal of Power and Energy Conversion (IJPEC), Vol. 6, No. 3, 2015

Abstract: In this paper, an ANFIS-based UPQC controller is proposed for compensating the PQ problem. ANFIS is the combination of fuzzy inference system (FIS) and neural network which improves the performance of UPQC. In order to generate the discharging dc link voltage via bias voltage generator, ANFIS is used which allows the amalgamation of numerical and linguistic data. Subsequently, the neural network is trained by using the generated fuzzy rules and thus a desired output from the interference system is obtained. The output of ANFIS is injected to the line by the proposed UPQC system. Then, assessment is carried out to analyse the power quality problem by the compensating performance of proposed ANFIS-based UPQC. The assessment results are judged against those of neuro fuzzy controller (NFC), artificial neural network (ANN), and fuzzy logic controller (FLC)-based UPQC system.

Online publication date: Tue, 07-Jul-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Power and Energy Conversion (IJPEC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com