Distribution Feeder Energy Conservation By Using Hybrid NEURO-Fuzzy Approach

S.Thiruvenkadam*, A. Nirmal Kumar**, A. Sakthivel***
* Lecturer, Department of Electrical and Electronics Engineering, Dr. Mahalingam College of Engineering & Tech., TamilNadu, India.
** Professor and HOD, Department of Electrical and Electronics Engineering, Bannari Amman Institute of Tech., TamilNadu, India.
*** Senior Lecturer, Department of Electrical and Electronics Engineering, Dr. Mahalingam College of Engineering & Tech TamilNadu, India.
Periodicity:January - March'2008
DOI : https://doi.org/10.26634/jee.1.3.421

Abstract

This paper presents a feeder reconfiguration algorithm for the line loss reduction and feeder load balancing with minimum consumption of time. The proposed algorithm efficiently utilizes a heuristic based fuzzy strategy and constrained fuzzy operation along with back propagation neural network. This approach reduces the computation cost making it suitable for online application. A new network configuration is obtained through the proposed algorithm, which line achieves loss reduction and feeder load balance at the same time. The effectiveness of the proposed approach is demonstrated by employing the feeder switching operation scheme to a distribution system. The desired switching operations can be fulfilled in a very efficient manner as indicated from the results. The complete algorithm has been framed with strict top-down dependency is proposed to decrease software couplings using C++ object oriented programming language and provides the support for software reusability.

Keywords

Feeder reconfiguration, fuzzy , neural network, switching operation, load balance, power loss, radial network ,etc.

How to Cite this Article?

S.Thiruvenkadam, A. Nirmal Kumar and A. Sakthivel (2008). Distribution Feeder Energy Conservation By Using Hybrid NEURO-Fuzzy Approach. i-manager’s Journal on Electrical Engineering, 1(3), Jan-Mar 2008, Print ISSN 0973-8835, E-ISSN 2230-7176, pp. 45-52. https://doi.org/10.26634/jee.1.3.421

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