Hybrid neural network with bat approach for smart grid fault location
by Mangal Hemant Dhend; Rajan Hari Chile
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 11, No. 3, 2019

Abstract: This paper proposes identification of fault location in smart distribution grid based on artificial intelligence using currents and voltages measured; with the help of sensor nodes in distribution system. The approach presented here is the hybrid bat algorithm with neural network, implemented on latest smart distribution system which comprises distributed generation. The fault lengths for various types of faults on distribution feeders are recognised using system parameters measured, before and after the occurrence of a fault. For verifying the performance of proposed algorithm, the MATLAB-based coding is developed and executed on sample modified IEEE test feeders. The performance of a proposed technique is compared with the simple neural network method. The proposed method founds more accurate and fast in speed.

Online publication date: Mon, 30-Sep-2019

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 Reasoning-based Intelligent Systems (IJRIS):
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