A comprehensive micro-grid fault protection scheme based on S-transform and machine learning techniques
by Manohar Mishra; Pravat Kumar Rout
International Journal of Advanced Mechatronic Systems (IJAMECHS), Vol. 7, No. 5, 2017

Abstract: This manuscript presents a novel micro-grid protection scheme based on S-transform (ST) and machine learning techniques. Initialisation of the proposed approach is done by extracting the current signals from the targeted buses of different feeders and pre-processing through ST to derive different needful differential features. The extracted features are further used as an input vector to the machine learning model to classify the fault events. The proposed micro-grid protection scheme is tested for different protection scenario, such as the type of fault (symmetrical, asymmetrical and high impedance fault), micro-grid structure (radial and mesh) and mode of operation (islanded and grid connected), etc. Three different machine learning models are tested and compared in this framework: naïve Bayes classifier (NBC), support vector machine (SVM) and extreme learning machine (ELM). The extensive simulated results from a standard IEC micro-grid model prove the effectiveness and reliability of proposed micro-grid protection scheme.

Online publication date: Fri, 19-Oct-2018

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 Advanced Mechatronic Systems (IJAMECHS):
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