Modelling Energy Data in a Generalized Additive Model-A Case Study of Colombia

被引:2
|
作者
Berbesi, Lina [1 ]
Pritchard, Geoffrey [1 ]
机构
[1] Univ Auckland, Fac Sci, Dept Stat, Auckland 1010, New Zealand
关键词
generalized additive models; cubic splines; Markov random fields; tensor product splines; energy modelling; REGRESSION;
D O I
10.3390/en16041929
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
Energy demand modelling is essential for reliable informing and framing energy policy decisions. More accurate modelling betters ensuring availability of energy and energy quality. Energy availability is related to energy access across the country and defines important economic measures such as energy poverty, which plays a critical role in developing countries. Energy quality is related to the reliability of the supply for correctly estimating energy needs. To incorporate spatial and temporal components of energy in a way that availability and quality are accurately assessed, this article discussed a number of suitable task methods for this (Second-generation GAMs with one-dimensional smoothers: Cyclic/Non-Cyclic Cubic Splines and two-dimensional smoothers: Markov Random Fields/Tensor Splines Interactions). The results showed that the complete consideration of both temporal and spatial aspects leads to a better fitted model which explains more of the data variation.
引用
收藏
页数:20
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