Prediction of Natural Gas Consumption using Empirical Models

被引：0

作者：

Hribar, Rok ^{[1
]}

Papa, Gregor ^{[1
]}

Silc, Jurij ^{[1
]}

机构：

[1] Jozef Stefan Inst, Ljubljana, Slovenia

来源：

PROCEEDINGS OF 2017 INTERNATIONAL CONFERENCE ON SMART SYSTEMS AND TECHNOLOGIES (SST) | 2017年

关键词：

natural gas consumption; demand forecasting; buildings; nonlinear forecasting models; RESIDENTIAL HEATING DEMAND; COMBINATION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Prediction of natural gas consumption of a town is very important for its logistics and district heating workflow. In this paper different empirical models are introduced for gas consumption prediction. The models are based on the characteristics of gas consumption data that was gathered in Ljubljana, Slovenia. Important observables were recognized from the data and the models were structured according to the correlation found in the data. The models are tested on forecasted weather data up to 60 hours into the future so that they can be used in realistic setting. The models presented in this paper are also able to model rare events such as public and school holidays.

引用

页码：31 / 36

页数：6

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