An Efficient Method for Optimal Placement and Sizing of Multiple Distributed Generators in a Radial Distribution Systems

Kumar, Injeti Satish; Navuri, Prema Kumar

doi:10.1080/21563306.2012.10531123

Cited by 18 publications

(1 citation statement)

References 23 publications

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“…The methods available for DG allocation problem can be broadly categorized as analytical approaches and heuristic method‐based approaches. Heuristic methods include genetic algorithms (GA), ant colony optimization, simulated annealing, tabu search (TS), particle swarm optimization, artificial bee colony algorithm, shuffled bat algorithm, GA with point estimate method, modified simulated annealing, and harmony search with differential operator . Population‐based heuristic methods are widely adapted in both operational and planning studies because of their efficient handling of multiple constraint criteria.…”

Section: Introductionmentioning

confidence: 99%

An analytical approach for allocation and sizing of distributed generations in radial distribution network

Kayal¹,

Chanda

2017

Int. Trans. Electr. Energ. Syst.

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This article presents a simple model to identify the proper location and size of distributed generations (DGs) in radial distribution networks. The proposed model is a combination of a 2-stage framework that determines a suitable location for DG and appropriate size at obtained location. An index is formulated that combines aspects of the real power losses in the network and the voltage stability condition of the network. The index is defined as the DG selection index, and it is used to determine the proper bus location for the DG. On the basis of a DG sizing formula presented in the article, the optimal generation capacity of a DG unit is determined. The proposed methodology is tested on 12-bus, 33-bus, and 69-bus radial distribution network models that consider different operational power factor operation modes of DGs. The simulation results are compared with existing analytical approaches to demonstrate the effectiveness of the proposed methodology in radial network systems.

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