Towards Efficient Energy Management in a Smart Home Using Updated Population

Faisal, Hafiz Muhammad; Javaid, Nadeem; Khan, Zahoor Ali; Mussadaq, Fahad; Akhtar, Muhammad; Abbasi, Raza Abid

doi:10.1007/978-3-030-15032-7_4

Cited by 3 publications

(4 citation statements)

References 31 publications

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“…The findings demonstrate a wider views and perceptual difference in scale of priority between the two groups. This partially supports Faisal et al (2020) and Faure and Schleich (2018) claims regarding energy consumptiona reduction in peak loads results in less waiting time for the user which implies a reduction in energy consumption towards a decrease in carbon emissions.…”

Section: Perception About Technology Used In Reducing the Average Uk ...supporting

confidence: 81%

“…Given its more advanced technological solutions, the smart power grid must be put into greater practice in order to attain the energy demands of the public, as opposed to the current traditional grid which is unable to sustain public demands (Khan et al, 2019). Faisal et al, (2020) focused on DSM and a smart grids domain rather than household. The emphasis was largely on reducing the total cost for the end user based on PAR.…”

Section: Smart Homes and Smart Gridsmentioning

confidence: 99%

“…Faisal et al (2020) focused on DSM and a smart grids domain rather than household. The emphasis was largely on reducing the total cost for the end user based on PAR.…”

Section: Smart Homes and Environmentally Beneficial Technologiesmentioning

confidence: 99%

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A qualitative assessment of the impact of smart homes and environmentally beneficial technologies on the UK 2050 net-zero carbon emission target

Shabha

Barber

Laycock

2021

SASBE

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PurposeThere are 29 million homes in the UK, accounting for 14% of the UK's energy consumption. This is given that UK has one of the highest water and energy demands in Europe which needs to be addressed according to the Committee on Climate Change (CCC). Smart homes technology holds a current perception that it is principally used by “tech-savvy” users with larger budgets. However, smart home technology can be used to control water, heat and energy in the entire house. This paper investigates how smart home technology could be effectively utilised to aid the UK government in meeting climate change targets and to mitigate the environmental impact of a home in use towards reducing carbon emissions.Design/methodology/approachBoth primary and secondary data were sought to gain insight into the research problem. An epistemological approach to this research is to use interpretivism to analyse data gathered via a semi-structured survey. Two groups of participants were approached: (1) professionals who are deemed knowledgeable about smart home development and implementation and (2) users of smart home technology. A variety of open-ended questions were formulated, allowing participants to elaborate by exploring issues and providing detailed qualitative responses based on their experience in this area which were interpreted quantitatively for clearer analysis.FindingsWith fossil fuel reserves depleting, there is an urgency for renewable, low carbon energy sources to reduce the 5 tonnes annual carbon emissions from a UK household. This requires a multi-faceted and a multimethod approach, relying on the involvement of both the general public and the government in order to be effective. By advancing energy grids to make them more efficient and reliable, concomitant necessitates a drastic change in the way of life and philosophy of homeowners when contemplating a reduction of carbon emissions. If both parties are able to do so, the UK is more likely to reach its 2050 net-zero carbon goal. The presence of a smart meter within the household is equally pivotal. It has a positive effect of reducing the amount of carbon emissions and hence more need to be installed.Research limitations/implicationsFurther research is needed using a larger study sample to achieve more accurate and acceptable generalisations about any future course of action. Further investigation on the specifics of smart technology within the UK household is also needed to reduce the energy consumption in order to meet net-zero carbon 2050 targets due to failures of legislation.Practical implicationsFor smart homes manufacturers and suppliers, more emphasis should be placed to enhance compatibility and interoperability of appliances and devices using different platform and creating more user's friendly manuals supported by step-by-step visual to support homeowners in the light of the wealth of knowledge base generated over the past few years. For homeowners, more emphasis should be placed on creating online knowledge management platform easily accessible which provide virtual support and technical advice to home owners to deal with any operational and technical issues or IT glitches. Developing technical design online platform for built environment professionals on incorporating smart sensors and environmentally beneficial technology during early design and construction stages towards achieving low to zero carbon homes.Originality/valueThis paper bridges a significant gap in the body of knowledge in term of its scope, theoretical validity and practical applicability, highlighting the impact of using smart home technology on the environment. It provides an insight into how the UK government could utilise smart home technology in order to reduce its carbon emission by identifying the potential link between using smart home technology and environmental sustainability in tackling and mitigating climate change. The findings can be applied to other building types and has the potential to employ aspects of smart home technology in order to manage energy and water usage including but not limited to healthcare, commercial and industrial buildings.

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Section: Perception About Technology Used In Reducing the Average Uk ...supporting

confidence: 81%

Section: Smart Homes and Smart Gridsmentioning

confidence: 99%

See 1 more Smart Citation

A qualitative assessment of the impact of smart homes and environmentally beneficial technologies on the UK 2050 net-zero carbon emission target

Shabha

Barber

Laycock

2021

SASBE

View full text Add to dashboard Cite

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“…A well proposed new algorithm namely Genetic Algorithm Super-clustering (GASC) for scheduling appliances is done by using super clustering appliances and their working timing hours [3]. By scheduling the appliances of the smart home, the operation of these appliances can be shifted to off-peak hours and spread over a longer period of time that would in turn reduce the excessive energy consumed [4], [5]. Thus, optimizing the scheduling of appliances should greatly minimize the peak demand and electricity bills [6].…”

Section: Introductionmentioning

confidence: 99%

Load Scheduling for Smart Home Using Day-Ahead Prediction From Artificial Neural Network (Ann)

Joharry¹,

Hussin²,

Rosmin³

et al. 2020

IJATCSE

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This paper presents load scheduling for smart home application using day-ahead prediction from an artificial neural network (ANN). In this study, load forecasting using ANN approach is embedded in the load scheduling scheme that is modeled using mixed integer linear programming (MILP). The main objective of the scheduling is to reduce the electricity bill by shifting peak load to off-peak period. A dayahead energy consumption is predicted based on a previous yearly data set of hourly resolution. The dataset is normalized and injected as input in ANN and the result is then fed to the load scheduling optimization process. The results show that the integration process affects the allocation of load consumption in the load profile as well as the electricity cost. From the comparative study between before and after ANN integration, the total cost saving achieved is $1.53/day with the cost reduction of 38.44%.

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Scheduling of Demand-Side Resources for a Residential Air Conditioning Load

Muley¹,

Bhongade²

2022

Lecture Notes in Electrical Engineering

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Towards Efficient Energy Management in a Smart Home Using Updated Population

Cited by 3 publications

References 31 publications

A qualitative assessment of the impact of smart homes and environmentally beneficial technologies on the UK 2050 net-zero carbon emission target

A qualitative assessment of the impact of smart homes and environmentally beneficial technologies on the UK 2050 net-zero carbon emission target

Load Scheduling for Smart Home Using Day-Ahead Prediction From Artificial Neural Network (Ann)

Scheduling of Demand-Side Resources for a Residential Air Conditioning Load

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