A Functional Regression Approach for Prediction in a District-Heating System

Aldo GOIA

A Functional Regression Approach for Prediction in a District-Heating System

Aldo GOIA

Department of Economics and Business Studies

Research output: Contribution to conference › Paper

Abstract

We consider the problem of short-term peak demand forecasting in a district heating system. Our dataset consists of four separated periods, with 198 days each period and 24 hourly observations within each day relative to heat consumption and climate. We take advantage of the functional nature of the data and we propose a forecasting methodology based on functional regression. The influence of exogenous explanatory variables is modelled in a suitable way. The out-of-sample performances of the proposed approach are evaluated.

Original language	French
Publication status	Published - 1 Jan 2010
Event	42èmes Journées de Statistique - Marseille, France Duration: 1 Jan 2010 → …

Conference

Conference	42èmes Journées de Statistique
City	Marseille, France
Period	1/01/10 → …

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 13 Climate Action

Cite this

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abstract = "We consider the problem of short-term peak demand forecasting in a district heating system. Our dataset consists of four separated periods, with 198 days each period and 24 hourly observations within each day relative to heat consumption and climate. We take advantage of the functional nature of the data and we propose a forecasting methodology based on functional regression. The influence of exogenous explanatory variables is modelled in a suitable way. The out-of-sample performances of the proposed approach are evaluated.",

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PY - 2010/1/1

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N2 - We consider the problem of short-term peak demand forecasting in a district heating system. Our dataset consists of four separated periods, with 198 days each period and 24 hourly observations within each day relative to heat consumption and climate. We take advantage of the functional nature of the data and we propose a forecasting methodology based on functional regression. The influence of exogenous explanatory variables is modelled in a suitable way. The out-of-sample performances of the proposed approach are evaluated.

AB - We consider the problem of short-term peak demand forecasting in a district heating system. Our dataset consists of four separated periods, with 198 days each period and 24 hourly observations within each day relative to heat consumption and climate. We take advantage of the functional nature of the data and we propose a forecasting methodology based on functional regression. The influence of exogenous explanatory variables is modelled in a suitable way. The out-of-sample performances of the proposed approach are evaluated.

UR - https://iris.uniupo.it/handle/11579/23116

M3 - Contributo in Atti di Convegno

T2 - 42èmes Journées de Statistique

Y2 - 1 January 2010

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A Functional Regression Approach for Prediction in a District-Heating System

Abstract

Conference

UN SDGs

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