Statistical Models for Disaggregation and Reaggregation of Natural Gas Consumption Data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F15%3A00436216" target="_blank" >RIV/67985807:_____/15:00436216 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11320/15:10285455

Výsledek na webu

<a href="http://dx.doi.org/10.1080/02664763.2014.993365" target="_blank" >http://dx.doi.org/10.1080/02664763.2014.993365</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/02664763.2014.993365" target="_blank" >10.1080/02664763.2014.993365</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Statistical Models for Disaggregation and Reaggregation of Natural Gas Consumption Data

Popis výsledku v původním jazyce

In this paper, we present a unified framework for natural gas consumption modeling and forecasting. This consists of models of GAM class and their nonlinear extension, tailored for easy estimation, aggregation and treatment of the delayed relationship between temperature and consumption. Since the consumption data for households and small commercial customers are routinely available in many countries only as long-term sum meter readings, their disaggregation and possibly reaggregation to different timeintervals is necessary for a variety of purposes. We show some examples of specific models based on the presented framework and then we demonstrate their use in practice, especially for the disaggregation and reaggregation tasks.

Název v anglickém jazyce

Statistical Models for Disaggregation and Reaggregation of Natural Gas Consumption Data

Popis výsledku anglicky

In this paper, we present a unified framework for natural gas consumption modeling and forecasting. This consists of models of GAM class and their nonlinear extension, tailored for easy estimation, aggregation and treatment of the delayed relationship between temperature and consumption. Since the consumption data for households and small commercial customers are routinely available in many countries only as long-term sum meter readings, their disaggregation and possibly reaggregation to different timeintervals is necessary for a variety of purposes. We show some examples of specific models based on the presented framework and then we demonstrate their use in practice, especially for the disaggregation and reaggregation tasks.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Applied Statistics

ISSN

0266-4763

e-ISSN

—

Svazek periodika

42

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

17

Strana od-do

921-937

Kód UT WoS článku

000349904500001

EID výsledku v databázi Scopus

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