Managing household electricity consumption: a correlational, regression analysis

Papageorgiou, George; Efstathiades, Andreas; Poullou, Maria; Ness, Alexander N.

doi:10.1080/14786451.2020.1718675

Cited by 8 publications

(8 citation statements)

References 15 publications

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“…Building size, footprint, and size of rooms contributed in relation to the number of people staying in the home. Papageorgiou et al 2020;Zhang, Bai, and Mills 2020;Namazkhan, Albers, and Steg 2020;Strengers et al 2020 Despite abundant research papers on residential buildings' energy characteristics, exploratory studies in situational-based research remain limited. The situation that developed in India from the COVID-19 outbreak, February 2020 to May 2020, provides an excellent case study to examine usage when a highly infectious epidemic is present and the entire country is placed in lockdown.…”

Section: Behavioral Factors (Bf)mentioning

confidence: 99%

Analyzing energy consumption factors during coronavirus (COVID-19) pandemic outbreak: a case study of residential society

Qarnain

2020

Energy Sources, Part A: Recovery, Utilization, and Environmenta

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The global pandemic of COVID-19 has affected most countries and has impacted every household's operations. Mandatory stay-at-home lockdowns have forced building residents to use more energy for their daily routine activities, giving rise to higher energy usage. The increased energy use by building residents results in high energy bills and leads to a scarcity in the energy supply. Identifying factors that can control the high energy consumption in buildings can be used to optimize energy consumption and act as energy conservation factors. This proposed research is conducted to identify and explore the most influential energy consumption factors amid COVID-19 pandemic in residential buildings using a case study in India. To analyze the energy consumption factors, a Multiple Criteria Decision Making (MCDM) methodology based Best Worst Method (BWM) and a Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology have been integrated. The results show that among 34 comprehensive energy consumption factors, the high priority topmost 50% of the factors were analyzed. The main research outcome indicates that 53% of the factors were in the cause group and the remaining 47% were in the effect group factors. Research results conclude that in response to COVID-19, social distancing, home quarantine, and home transformation were the primary factors for energy consumption in homes. Among the sub-factors, the lockdown of streets, shutdown of public markets, and psychological factors were the top three factors adding to increased energy consumption. Further, Industrial and economic importance of the research is also discussed.

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Section: Behavioral Factors (Bf)mentioning

confidence: 99%

Analyzing energy consumption factors during coronavirus (COVID-19) pandemic outbreak: a case study of residential society

Qarnain

2020

Energy Sources, Part A: Recovery, Utilization, and Environmenta

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“…Knowledge of the different routines and practices performed by the occupants will allow systems to predict the magnitude of energy required to allow energy supply to be manipulated and dynamic. An important aspect of residential living is the effective use of energy [45], and thus the ability to predict energy consumption will help to achieve this. Managing electricity generation and consumption provides avenues for more efficient methods to be used to achieve energy savings, resulting in an environmental benefit through reduced emissions [45].…”

Section: Energy Managementmentioning

confidence: 99%

“…An important aspect of residential living is the effective use of energy [45], and thus the ability to predict energy consumption will help to achieve this. Managing electricity generation and consumption provides avenues for more efficient methods to be used to achieve energy savings, resulting in an environmental benefit through reduced emissions [45]. Previous studies revealed how effective energy management methods can be in commercial and residential settings [46].…”

Section: Energy Managementmentioning

confidence: 99%

Identifying Home System of Practices for Energy Use with K-Means Clustering Techniques

Malatesta

Breadsell

2022

Sustainability

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Human behaviour is a major driver and determinant of household energy consumption, with routines and practices shaping daily energy profiles. These routines and practices are made up of individual lifestyles and other contextual factors that vary from home to home. Social and psychological theories aim to explain and describe how people consume resources in the home, which has resulted in the development of the home system of practice. This evaluates how occupants live and follow multiple routines which result in varying energy consumption practices. This paper develops a methodology to identify and support the concept of the home system of practice using a data analytical approach and link it to residential energy and distribution network management. This paper utilises k-means cluster analysis to identify these different home systems of practices and routines in energy use by using real-time energy consumption data from July 2019 to March 2021 from a living laboratory in Australia. The results of the analysis show the different daily energy profiles for each of the 39 households, with some homes observing large fluctuations and changes in the way they consume energy during the day. Specific homes were discussed as case studies in this paper focusing on linking the occupants’ contextual factors to their energy profiles. This variation is discussed in terms of the routines of the occupants and associated lifestyles that explain why some energy peaks occurred at different parts of the day and differed during the COVID-19 lockdown period in Australia. The paper conducts a comparison between these case studies to show how people’s lifestyles impact household energy consumption (and variation). These case studies investigated the heating and cooling practices of the occupants to demonstrate how they impact overall consumption. This variation is discussed in relation to energy management and prediction of when homes will consume energy to assist in net-zero energy developments and grid stabilisation operations.

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“…There are two ways to improve energy efficiency (de Gracia and Cabeza, 2015). The first one is to optimize HVAC systems (Pérez-Lombard et al, 2011). This could be achieved by monitoring humidity and temperature conditions to improve thermal comfort (Földváry Ličina et al, 2018;Hazyuk et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…A different approach is to improve the thermal performance of walls in buildings. Insulation materials are used in buildings to drop heat losses, allowing for reducing heating/cooling duties (Papageorgiou et al, 2020) with improved indoor thermal comfort (Meng et al, 2018). Rigid polyurethane foam (RPU) has been widely used in the field of thermal insulation of buildings due to its low thermal conductivity, low density, and superior mechanical properties (Yang et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Monitor and control test room for investigating thermal performance of panels incorporating phase-change material

Othmen

Bahri

Najar

et al. 2021

J. Sens. Sens. Syst.

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Abstract. This article aims to present equipment designed and developed to study the effective thermal conductivity of composite panels. The composite panel used is a rigid polyurethane foam covered with a layer of aluminum on both sides. The panel is mounted in the test chamber equipped with several sensors and actuators connected via an Arduino platform. Tests have been carried out by applying heat to impose various interior temperatures. Sensors at different locations are used to monitor and record temperatures in and around the composite panel during heating and natural cooling. A model, based on the Fourier equations of thermal conduction and natural convection heat transfer for the steady state, was developed to assess the effective thermal conductivity. The performance of the system was confirmed using temperature signals through the panels for thermal characterization of composite materials. The determined effective thermal conductivity obtained was in agreement with the experimental values reported in the technical data sheets with relative deviations of less than 10 %.

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Managing household electricity consumption: a correlational, regression analysis

Cited by 8 publications

References 15 publications

Analyzing energy consumption factors during coronavirus (COVID-19) pandemic outbreak: a case study of residential society

Analyzing energy consumption factors during coronavirus (COVID-19) pandemic outbreak: a case study of residential society

Identifying Home System of Practices for Energy Use with K-Means Clustering Techniques

Monitor and control test room for investigating thermal performance of panels incorporating phase-change material

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