Optimal Site and Size of Distributed Generation Allocation in Radial Distribution Network Using Multi-objective Optimization

Distributed generation (DG) allocation in the distribution network is generally a multi-objective optimization problem. The maximum benefits of DG injection in the distribution system highly depend on the selection of an appropriate number of DGs and their capacity along with the best location. In t...

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Veröffentlicht in:Journal of modern power systems and clean energy Jg. 9; H. 2; S. 404 - 415
Hauptverfasser: Aamir Ali, M. U. Keerio, J. A. Laghari
Format: Journal Article
Sprache:Englisch
Veröffentlicht: IEEE 01.03.2021
Schlagworte:
active power loss
distributed generation
Distribution system
improved decomposition based evolutionary algorithm (I-DBEA)
multi-objective optimization
ISSN:2196-5420
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Zusammenfassung:Distributed generation (DG) allocation in the distribution network is generally a multi-objective optimization problem. The maximum benefits of DG injection in the distribution system highly depend on the selection of an appropriate number of DGs and their capacity along with the best location. In this paper, the improved decomposition based evolutionary algorithm (I-DBEA) is used for the selection of optimal number, capacity and site of DG in order to minimize real power losses and voltage deviation, and to maximize the voltage stability index. The proposed I-DBEA technique has the ability to incorporate non-linear, nonconvex and mixed-integer variable problems and it is independent of local extrema trappings. In order to validate the effectiveness of the proposed technique, IEEE 33-bus, 69-bus, and 119-bus standard radial distribution networks are considered. Furthermore, the choice of optimal number of DGs in the distribution system is also investigated. The simulation results of the proposed method are compared with the existing methods. The comparison shows that the proposed method has the ability to get the multi-objective optimization of different conflicting objective functions with global optimal values along with the smallest size of DG.
ISSN:2196-5420
DOI:10.35833/MPCE.2019.000055