Projecting impacts of uncertain climate change on future energy demand

Sandhya Patidar; David P. Jenkins; Andrew Peacock

Projecting impacts of uncertain climate change on future energy demand

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Abstract

This paper presents a novel approach for developing a Demand Profile Synthesis Tool (DPSTool) involving the decomposition of electricity demand into subcomponents and selectively applying cutting-edge statistical modelling techniques for predicting (short/long-term) domestic energy demand patterns. The DPSTool will be underpinned by a new ‘climate module’ integrated within a previously developed high-tech HMM_GP model. The ‘climate module’ can simulate the impacts of key climatic variables on the electricity demand scenarios. The paper will demonstrate the key stages of statistical methodology development and validation procedure of ‘climate module’ using a residential case-study building selected from a community ‘Auroville’, located in India.

Original language	English
Number of pages	8
Publication status	Published - 1 Sept 2021
Event	17th IBPSA Conference 2021 - Bruges/Virtual, Bruges, Belgium Duration: 1 Sept 2021 → 3 Sept 2021 https://bs2021.org/

Conference

Conference	17th IBPSA Conference 2021
Country/Territory	Belgium
City	Bruges
Period	1/09/21 → 3/09/21
Internet address	https://bs2021.org/

UN SDGs

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

SDG 7 Affordable and Clean Energy
SDG 13 Climate Action

Keywords

climate change
Energy Demand
Forecasting
Hidden Markov model
STL_HMM_GP

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Cite this

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title = "Projecting impacts of uncertain climate change on future energy demand",

abstract = "This paper presents a novel approach for developing a Demand Profile Synthesis Tool (DPSTool) involving the decomposition of electricity demand into subcomponents and selectively applying cutting-edge statistical modelling techniques for predicting (short/long-term) domestic energy demand patterns. The DPSTool will be underpinned by a new {\textquoteleft}climate module{\textquoteright} integrated within a previously developed high-tech HMM\_GP model. The {\textquoteleft}climate module{\textquoteright} can simulate the impacts of key climatic variables on the electricity demand scenarios. The paper will demonstrate the key stages of statistical methodology development and validation procedure of {\textquoteleft}climate module{\textquoteright} using a residential case-study building selected from a community {\textquoteleft}Auroville{\textquoteright}, located in India.",

keywords = "climate change, Energy Demand, Forecasting, Hidden Markov model, STL\_HMM\_GP",

author = "Sandhya Patidar and Jenkins, \{David P.\} and Andrew Peacock",

year = "2021",

month = sep,

day = "1",

language = "English",

note = "17th IBPSA Conference 2021 ; Conference date: 01-09-2021 Through 03-09-2021",

url = "https://bs2021.org/",

}

TY - CONF

T1 - Projecting impacts of uncertain climate change on future energy demand

AU - Patidar, Sandhya

AU - Jenkins, David P.

AU - Peacock, Andrew

PY - 2021/9/1

Y1 - 2021/9/1

N2 - This paper presents a novel approach for developing a Demand Profile Synthesis Tool (DPSTool) involving the decomposition of electricity demand into subcomponents and selectively applying cutting-edge statistical modelling techniques for predicting (short/long-term) domestic energy demand patterns. The DPSTool will be underpinned by a new ‘climate module’ integrated within a previously developed high-tech HMM_GP model. The ‘climate module’ can simulate the impacts of key climatic variables on the electricity demand scenarios. The paper will demonstrate the key stages of statistical methodology development and validation procedure of ‘climate module’ using a residential case-study building selected from a community ‘Auroville’, located in India.

AB - This paper presents a novel approach for developing a Demand Profile Synthesis Tool (DPSTool) involving the decomposition of electricity demand into subcomponents and selectively applying cutting-edge statistical modelling techniques for predicting (short/long-term) domestic energy demand patterns. The DPSTool will be underpinned by a new ‘climate module’ integrated within a previously developed high-tech HMM_GP model. The ‘climate module’ can simulate the impacts of key climatic variables on the electricity demand scenarios. The paper will demonstrate the key stages of statistical methodology development and validation procedure of ‘climate module’ using a residential case-study building selected from a community ‘Auroville’, located in India.

KW - climate change

KW - Energy Demand

KW - Forecasting

KW - Hidden Markov model

KW - STL_HMM_GP

M3 - Paper

T2 - 17th IBPSA Conference 2021

Y2 - 1 September 2021 through 3 September 2021

ER -

Projecting impacts of uncertain climate change on future energy demand

Abstract

Conference

UN SDGs

Keywords

Access to Document

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Cite this