Smart Home Energy Management Supported by Cloud Computing

Joaquim Leitão; Paulo Gil; Bernardete Ribeiro; Alberto Cardoso

doi:10.1109/EXPAT.2019.8876531

Smart Home Energy Management Supported by Cloud Computing

Joaquim Leitão, Paulo Gil, Bernardete Ribeiro, Alberto Cardoso

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The current work studies optimal management of electrical appliances in smart homes. An appliance scheduling problem is addressed via optimisation approaches with the goal of minimising the overall energy bill over a week. Scheduling of electrical appliances must take into account non-controllable domestic demand, grid prices and local energy production by photovoltaic panels. Here, a preliminary cloud architecture is proposed to support smart home sensor data collection, storage, processing and scheduling computation. Optimal schedules achieve a balance between local energy production and grid prices, exploring periods of higher generation to attenuate non-controllable demands and favouring night periods (during which energy is cheaper) for controllable appliances operations.

Original language	English
Title of host publication	Proceedings of the 2019 5th Experiment at International Conference, exp.at 2019
Editors	Alberto Cardoso, Maria Teresa Restivo
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	96-101
Number of pages	6
ISBN (Electronic)	9781728136370
DOIs	https://doi.org/10.1109/EXPAT.2019.8876531
Publication status	Published - Jun 2019
Event	5th Experiment at International Conference, exp.at 2019 - Funchal, Madeira, Portugal Duration: 12 Jun 2019 → 14 Jun 2019

Conference

Conference	5th Experiment at International Conference, exp.at 2019
Country/Territory	Portugal
City	Funchal, Madeira
Period	12/06/19 → 14/06/19

Keywords

Cloud Computing
Cyber-Physical Systems
Home Energy Management Systems
Mixed-Integer Programming
Smart Homes

UN SDGs

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

Access to Document

10.1109/EXPAT.2019.8876531

Cite this

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title = "Smart Home Energy Management Supported by Cloud Computing",

abstract = "The current work studies optimal management of electrical appliances in smart homes. An appliance scheduling problem is addressed via optimisation approaches with the goal of minimising the overall energy bill over a week. Scheduling of electrical appliances must take into account non-controllable domestic demand, grid prices and local energy production by photovoltaic panels. Here, a preliminary cloud architecture is proposed to support smart home sensor data collection, storage, processing and scheduling computation. Optimal schedules achieve a balance between local energy production and grid prices, exploring periods of higher generation to attenuate non-controllable demands and favouring night periods (during which energy is cheaper) for controllable appliances operations.",

keywords = "Cloud Computing, Cyber-Physical Systems, Home Energy Management Systems, Mixed-Integer Programming, Smart Homes",

author = "Joaquim Leit{\~a}o and Paulo Gil and Bernardete Ribeiro and Alberto Cardoso",

note = "UID/CEC/00326/2019 SFRH/BD/122103/2016 Sem PDF conforme despacho.; 5th Experiment at International Conference, exp.at 2019 ; Conference date: 12-06-2019 Through 14-06-2019",

year = "2019",

month = jun,

doi = "10.1109/EXPAT.2019.8876531",

language = "English",

pages = "96--101",

editor = "Alberto Cardoso and Restivo, {Maria Teresa}",

booktitle = "Proceedings of the 2019 5th Experiment at International Conference, exp.at 2019",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

}

Leitão, J, Gil, P, Ribeiro, B & Cardoso, A 2019, Smart Home Energy Management Supported by Cloud Computing. in A Cardoso & MT Restivo (eds), Proceedings of the 2019 5th Experiment at International Conference, exp.at 2019., 8876531, Institute of Electrical and Electronics Engineers (IEEE), pp. 96-101, 5th Experiment at International Conference, exp.at 2019, Funchal, Madeira, Portugal, 12/06/19. https://doi.org/10.1109/EXPAT.2019.8876531

Smart Home Energy Management Supported by Cloud Computing. / Leitão, Joaquim; Gil, Paulo; Ribeiro, Bernardete et al.
Proceedings of the 2019 5th Experiment at International Conference, exp.at 2019. ed. / Alberto Cardoso; Maria Teresa Restivo. Institute of Electrical and Electronics Engineers (IEEE), 2019. p. 96-101 8876531.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Smart Home Energy Management Supported by Cloud Computing

AU - Leitão, Joaquim

AU - Gil, Paulo

AU - Ribeiro, Bernardete

AU - Cardoso, Alberto

N1 - UID/CEC/00326/2019 SFRH/BD/122103/2016 Sem PDF conforme despacho.

PY - 2019/6

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N2 - The current work studies optimal management of electrical appliances in smart homes. An appliance scheduling problem is addressed via optimisation approaches with the goal of minimising the overall energy bill over a week. Scheduling of electrical appliances must take into account non-controllable domestic demand, grid prices and local energy production by photovoltaic panels. Here, a preliminary cloud architecture is proposed to support smart home sensor data collection, storage, processing and scheduling computation. Optimal schedules achieve a balance between local energy production and grid prices, exploring periods of higher generation to attenuate non-controllable demands and favouring night periods (during which energy is cheaper) for controllable appliances operations.

AB - The current work studies optimal management of electrical appliances in smart homes. An appliance scheduling problem is addressed via optimisation approaches with the goal of minimising the overall energy bill over a week. Scheduling of electrical appliances must take into account non-controllable domestic demand, grid prices and local energy production by photovoltaic panels. Here, a preliminary cloud architecture is proposed to support smart home sensor data collection, storage, processing and scheduling computation. Optimal schedules achieve a balance between local energy production and grid prices, exploring periods of higher generation to attenuate non-controllable demands and favouring night periods (during which energy is cheaper) for controllable appliances operations.

KW - Cloud Computing

KW - Cyber-Physical Systems

KW - Home Energy Management Systems

KW - Mixed-Integer Programming

KW - Smart Homes

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U2 - 10.1109/EXPAT.2019.8876531

DO - 10.1109/EXPAT.2019.8876531

M3 - Conference contribution

SP - 96

EP - 101

BT - Proceedings of the 2019 5th Experiment at International Conference, exp.at 2019

A2 - Cardoso, Alberto

A2 - Restivo, Maria Teresa

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 5th Experiment at International Conference, exp.at 2019

Y2 - 12 June 2019 through 14 June 2019

ER -

Smart Home Energy Management Supported by Cloud Computing

Abstract

Conference

Keywords

UN SDGs

Access to Document

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