DocumentCode
650237
Title
Macro Demand Spatial Approach (MDSA) with principal component analysis (PCA) on spatial demand forecasting for industrial area in transmission planning
Author
Sasmono, Sudarmono ; Sinisuka, N.I. ; Atmopawiro, Mukmin W. ; Darwanto, Djoko
Author_Institution
Sch. of Electr. Eng. & Inf., Bandung Inst. of Technol., Bandung, Indonesia
fYear
2013
fDate
7-8 Oct. 2013
Firstpage
380
Lastpage
384
Abstract
Macro Demand Spatial Approach (MDSA) is an approach introduced in long time electricity demand forecasting considering location. It will be used at transmission planning and policy decision on electricity infrastructure development in a region. In the model, MDSA combined with principal component analysis (PCA) method to determine the variables that affecting electricity demand in industrial area. The variables are different for each load sector. Hypothesis on unique variables affecting electricity demand on every load sector in the industrial area were analyzed with qualitative methods and references. The variables have no significant effect can be reduced by using PCA. The generated models tested to assess whether it still at the range of confidence level of electricity demand forecasting. At the case study, generated model for South Sumatra Subsystem as a part of Sumatra System is still in the range of confidence level.
Keywords
industrial plants; load forecasting; power transmission planning; principal component analysis; MDSA; PCA; electricity demand; electricity infrastructure development; industrial area; load sector; macro demand spatial approach; policy decision; principal component analysis method; spatial demand forecasting; transmission planning; electricity demand forecasting; industrial area; macro demand spatial approach; principal component analysis; transmission planning;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology and Electrical Engineering (ICITEE), 2013 International Conference on
Conference_Location
Yogyakarta
Print_ISBN
978-1-4799-0423-5
Type
conf
DOI
10.1109/ICITEED.2013.6676272
Filename
6676272
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