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Distributed generation capacity planning for distribution networks to minimize energy loss: an unbalanced multi-phase optimal power flow based approach

Anwar, Adnan, Mahmud, Md. Apel, Hossain, Md. Jahangir and Pota, Himanshu Roy 2016, Distributed generation capacity planning for distribution networks to minimize energy loss: an unbalanced multi-phase optimal power flow based approach. In Shandilya, Smita, Shandilya, Shishir, Thakur, Tripta and Nagar, Atulya K. (ed), Handbook of research on emerging technologies for electrical power planning, analysis and optimization, Engineering Science Reference, [London, Eng.], pp.76-95, doi: 10.4018/978-1-4666-9911-3.ch005.

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Title Distributed generation capacity planning for distribution networks to minimize energy loss: an unbalanced multi-phase optimal power flow based approach
Author(s) Anwar, Adnan
Mahmud, Md. ApelORCID iD for Mahmud, Md. Apel orcid.org/0000-0002-5302-5338
Hossain, Md. Jahangir
Pota, Himanshu Roy
Title of book Handbook of research on emerging technologies for electrical power planning, analysis and optimization
Editor(s) Shandilya, Smita
Shandilya, Shishir
Thakur, Tripta
Nagar, Atulya K.
Publication date 2016
Chapter number 5
Total chapters 19
Start page 76
End page 95
Total pages 20
Publisher Engineering Science Reference
Place of Publication [London, Eng.]
Keyword(s) Technology & Engineering
Summary This chapter presents an unbalanced multi-phase optimal power flow (UMOPF) based planning approach to determine the optimum capacities of multiple distributed generation units in a distribution network. An adaptive weight particle swarm optimization algorithm is used to find the global optimum solution. To increase the efficiency of the proposed scheme, a co-simulation platform is developed. Since the proposed method is mainly based on the cost optimization, variations in loads and uncertainties within DG units are also taken into account to perform the analysis. An IEEE 123 node distribution system is used as a test distribution network which is unbalanced and multi-phase in nature, for the validation of the proposed scheme. The superiority of the proposed method is investigated through the comparisons of the results obtained that of a Genetic Algorithm based OPF method. This analysis also shows that the DG capacity planning considering annual load and generation uncertainties outperform the traditional well practised peak-load planning.
ISBN 9781466699120
1466699116
Language eng
DOI 10.4018/978-1-4666-9911-3.ch005
Field of Research 090607 Power and Energy Systems Engineering (excl Renewable Power)
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category B1 Book chapter
ERA Research output type B Book chapter
Copyright notice ©2016, Engineering Science Reference
Persistent URL http://hdl.handle.net/10536/DRO/DU:30084002

Document type: Book Chapter
Collection: School of Engineering
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