Sabarinath.G

Work place: Dept. of EEE, S.V.University, Tirupati, Pin code: 517502, Andhra Pradesh, India

E-mail: sabarinath204@gmail.com

Website:

Research Interests: Artificial Intelligence, Autonomic Computing, Neural Networks, Computer Networks, Data Structures and Algorithms

Biography

Sabarinath.G received his B.Tech and M.Tech degrees in Electrical and Electronics Engineering from JNT University Anantapuramu, India, in 2009 and 2013, respectively. Currently, he is pursuing his Ph.D. in the Department of Electrical and Electronics Engineering at the S.V. University, Tirupati. His research interests are in the areas of Soft computing techniques, Artificial neural networks, FACTS, Nature-inspired algorithms, Economic load dispatch, Renewable energy sources, and Power electronics. 

Author Articles
Optimal Sitting and Sizing of Distributed Generation Units in an Indian Practical Distribution System using Bird Swarm Algorithm

By Sabarinath.G T.Gowri Manohar

DOI: https://doi.org/10.5815/ijisa.2019.10.06, Pub. Date: 8 Oct. 2019

Indian practical rural distribution systems are very long and spread over a wide range of area. The nodes far away from the distribution substation are suffering from low voltage. In India, total distribution system losses are around 20% to 25%. From the past few years, penetration of distributed generation (DG) in to the distribution network/system is increasing expeditiously. DG allocation with appropriate location and size can provide numerous benefits to the distribution companies as well as to the society. In this regard, a new technique called combined sensitivity index (CSI), to find the optimal DG unit location, based on voltage sensitivity and network load magnitude is proposed. To assess the effectiveness of the proposed technique, it is tested on Indian practical 52-bus rural distribution system. The results obtained with the proposed CSI technique is compared with the results obtained with the combined power loss sensitivity (CPLS) technique. Here, the optimal DG unit size is calculated using Bird Swarm Algorithm (BSA). The results show that the proposed CSI technique performs better in minimizing power losses and voltage profile augmentation when compared to existing CPLS technique.

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Application of Bird Swarm Algorithm for Allocation of Distributed Generation in an Indian Practical Distribution Network

By Sabarinath.G T.Gowri Manohar

DOI: https://doi.org/10.5815/ijisa.2019.07.06, Pub. Date: 8 Jul. 2019

This article addresses an optimal allocation of multi Distributed Generation (DG) units in an Indian practical radial distribution network (RDN) for minimization of network loss and voltage deviation. For this work, combined sensitivity index (CSI) is utilized to identify the appropriate positions/locations of DG units. However, the appropriate size of DG is determined through a nature-inspired; population-based Bird Swarm Algorithm (BSA). Secondly, the influence of DG penetration level on network loss and voltage profile is investigated and presented. In this regard, two types of DG technologies (solar and biomass) are considered for loss reduction and voltage deviation reduction. The performance of CSI and BSA methodology is successfully evaluated on an Indian practical 52-bus RDN.

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