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Expansion Planning of Distribution Substations with Dynamic Programming and Immune Algorithm

The thesis investigates the optimal expansion planning of substations for the distribution system of Taipei City District of Taiwan Power Company. The small area load forecasting is executed with the support of Outage Management System(OMS) database. The capacity expansion of distribution substations is obtained by considering the annual load growth of each service area to achieve the cost effectiveness of substation investment.
The geographic information of each service zone has been retrieved form the OMS data. With the land use planning of Taipei City Government, the load density of each small area for the target year is derived according to the final floor area and development strength of the land base. The load forecasting of each small area is then solved by considering the load growth of each customer class, which is then used for the expansion planning of substations.
After determining the small area load forecasting for the final target year, the center of gravity method is applied to find the geographic blocks of all substations and the corresponding service areas at the target year. The power loading of each small area is used to calculate the power loading loss of which service area to solve the optimal location within the block for each substation. Based on the annual load forecasting of all small areas, the expansion planning of distribution substations for Taipei City District is derived by Dynamic Programming(DP) and Immune Algorithm(IA) to achieve minimization of power loading loss with subject to the operation constraint. By the proposed methodology, the unit commitment of distribution substations is determined to meet the load growth of service area and achieve power loading loss minimization of distribution systems.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0624105-115118
Date24 June 2005
CreatorsLin, Chia-Chung
Contributorsnone, none, Chao-Shun Chen
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0624105-115118
Rightscampus_withheld, Copyright information available at source archive

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