A novel ANN-based harmonic extraction method tested with ESN, RNN and MLP in shunt active power filters
by Jinbang Xu; Jun Yang; Anwen Shen; Junfeng Chen
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 7, No. 2, 2014

Abstract: With the wide use of power conversion devices - 'nonlinear loads' - many harmonic currents are being injected into the power grid. Shunt Active Power Filters (SAPF) are the power electronic equipment to compensate the harmonic currents caused by nonlinear loads. As the foundation of the harmonics recognition and compensation, harmonic extraction is the key technology in SAPF. Artificial Neural Networks (ANN) method has the features of parallel computation and satisfactory results for distorted source voltages over traditional extraction methods. This paper proposes a new harmonic extraction method based on ANN. To test the feasibility of different types of neural networks in this application, this paper compares the performances of three types of ANN: Echo State Networks (ESN), Recurrent Neural Networks (RNN) and Multilayer Perceptron Networks (MLP).

Online publication date: Fri, 31-Oct-2014

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 Wireless and Mobile Computing (IJWMC):
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