Development of a spatial load-forecasting module for optimizing planning of electricity supply

被引：0
|
作者：
Morales, D. X. [1 ]
Besanger, Y. [1 ]
Moscoso, S. A. [2 ]
Pesantez, P. A. [3 ]
机构：
[1] Univ Grenoble Alpes, CNRS, Grenoble INP, G2Elab, F-38000 Grenoble, France
[2] UCACUE, Cuenca, Ecuador
[3] UPV, IIE, Quito, Ecuador
来源：
2017 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE - LATIN AMERICA (ISGT LATIN AMERICA) | 2017年
关键词：
Smart planning; GIS; Spatial Load Forecasting; !text type='Python']Python[!/text;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
In today's economy, there is a strong need to forecast and predict future load demands in order to estimate the amount of load required and to properly prepare the planning purposes. This paper presents the development of a module with the ability to calculate the spatial load forecasting in any area of study. First, the electrical distribution system must be defined with all its components. After a model of geographical and temporal prediction of this demand for electricity, which uses a Hybrid method is developed. The software Python and ARCMAP are used in order to program the module. Furthermore, the developed module considers the main requirements for a good spatial load forecasting. Land use is a key factor in this work, excluding specific areas where is not possible to have growth.
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页数：6
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