DocumentCode :
2022311
Title :
Active distribution network integrated planning incorporating distributed generation and load response uncertainties
Author :
Borges, C. ; Martins, V.
fYear :
2012
fDate :
22-26 July 2012
Firstpage :
1
Lastpage :
1
Abstract :
Summary form only given: This paper presents a model for active distribution systems expansion planning based on Genetic Algorithms, where Distributed Generation (DG) integration is considered together with conventional alternatives for expansion, such as, rewiring, network reconfiguration, installation of new protection devices, etc. The novel approach of planning DG integration together with network expansion is a requirement for the modern active distribution network. However, the uncertainties related to DG power generation and load response growth must be taken into account in order to plan a safe system at a minimum cost. Thus, two different methodologies for uncertainties incorporation through the use of multiple scenarios analysis are proposed and compared. The multiple objectives optimization algorithm applied in the model takes into account the costs of reliability, losses, power imported from transmission, and network investments.
Keywords :
distributed power generation; genetic algorithms; power distribution planning; DG integration; active distribution network integrated planning; distributed generation; distribution systems expansion planning; genetic algorithms; load response growth; load response uncertainties; multiple objectives optimization algorithm; network investments; network reconfiguration; protection devices; rewiring; safe system; Companies; Distributed power generation; Educational institutions; Genetic algorithms; Load modeling; Planning; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
ISSN :
1944-9925
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
Type :
conf
DOI :
10.1109/PESGM.2012.6343936
Filename :
6343936
Link To Document :
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