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

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Sabarinath.G 1,* T.Gowri Manohar 2

1. Dept. of EEE, Sri Venkateswara University, Tirupathi, Pin: 517502, India

2. Dept. EEE, Sri Venkateswara University, Tirupathi, Pin: 517502, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2019.10.06

Received: 6 Apr. 2019 / Revised: 7 May 2019 / Accepted: 19 May 2019 / Published: 8 Oct. 2019

Index Terms

Bird swarm algorithm, Combined power loss sensitivity, Combined sensitivity index, Distributed generation, Distribution system, power loss, voltage deviation


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.

Cite This Paper

Sabarinath.G, T.Gowri Manohar, "Optimal Sitting and Sizing of Distributed Generation Units in an Indian Practical Distribution System using Bird Swarm Algorithm", International Journal of Intelligent Systems and Applications(IJISA), Vol.11, No.10, pp.54-64, 2019. DOI:10.5815/ijisa.2019.10.06


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