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Macro demand spatial approach (MDSA) at spatial demand forecasting for transmission system planning
Sasmono S.a, Sinisuka N.I.a, Atmopawiro M.W.a, Darwanto D.a
a School of Electrical Engineering and Informatics, InstitutTeknologi, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2015, School of Electrical Engineering and Informatics. All rights reserved.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 qualitative approach and quantitative approach as mixed method. QA used to determine main development area and supporting area in region.This method is used to prove the hypothesis that the observed transmission service area are not homogeneous.Main development area is an area with industrial domination as a driver of economic growth. Whilst, supporting area is an area with residential domination that supporting economic growth at main development area.Hence, the electricity demand driver variables are different for type of electricity consumer at different spatial characteristics. The variables have no significant effect can be reduced by using PCA. The results of PCA should be validated with the results of QA. Generated models formed from the variables generated by PCA. The generated models tested to assess whether it fit with the actual data. Range of interval confidence level used as fit criteria. At the case study, generated model for main development areas and supporting area in Southern Sumatra Regionas a part of Sumatra System is still in the range of confidence level. Thus, MDSA can be proposed as alternative approach on demand forecastingat transmission planning that considering location.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Macro demand spatial approach,Main development area,Principal component analysis,Spatial electricity demand forecasting,Transmission planning[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.15676/ijeei.2015.7.2.3[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]