A-SEM: An adaptive smart energy management testbed for shiftable loads optimisation in the smart home

Maizal Isnen*, Sigit Kurniawan, Emiliano Garcia-Palacios

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

Managing the increment in energy demand can be solved by involving the demand side in order to increase energy consumption efficiency. However, increasing energy consumption efficiency tends to influence the user level of comfort. A research gap exists in the study of the energy efficiency and user comfort trade-off and in particular in providing low cost testbeds to study this phenomenon. This research discusses a low-cost testbed hardware design and the potential of the proposed Adaptive-Smart Energy Management Tool (A-SEM tool) to balance the level of comfort and energy consumption efficiency. We implement an adaptive energy limitation algorithm which uses up to 30 days historical data. The energy consumption is influenced by user behaviour which is monitored by the system sensors and energy limits are adapted for the provision of comfort. A smart home user is able to set the monthly energy consumption budget which determines the initial level of daily energy limitation. A-SEM performs real time monitoring and controlling, mainly considering shiftable loads evaluated at the testing stage. We test 3 possible conditions (possible modes of operation) and prove that our “adaptive limit” energy limitation algorithm is the most successful in balancing the level of comfort and energy efficiency. For a fixed budget and energy price, the proposed adaptive approach meets user level of comfort (our main priority) as well as achieving some energy savings. In our test the A-SEM tool provides user comfort, meets the monthly budget constraint and yet shows an energy saving of 2.62% which can increase or decrease depending on user behaviour. We present results showing energy saving levels, comfort levels and efficiency levels. The proposed A-SEM tool is low cost, implements an uncomplicated adaptive algorithm and therefore has the potential to be an affordable smart energy management system in future smart homes.

Original languageEnglish
Article number107285
Number of pages8
JournalMeasurement: Journal of the International Measurement Confederation
Volume152
Early online date20 Nov 2019
DOIs
Publication statusPublished - Feb 2020

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Energy management
Testbeds
Energy utilization
comfort
Scanning electron microscopy
scanning electron microscopy
optimization
Energy conservation
energy consumption
Energy efficiency
energy
Costs
Energy management systems
Adaptive algorithms
budgets
Computer hardware
Monitoring
Sensors
Testing
management systems

Keywords

  • Adaptive-A-SEM tool
  • Demand side management
  • HEMS
  • Home energy management system
  • Smart home
  • User comfort

Cite this

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abstract = "Managing the increment in energy demand can be solved by involving the demand side in order to increase energy consumption efficiency. However, increasing energy consumption efficiency tends to influence the user level of comfort. A research gap exists in the study of the energy efficiency and user comfort trade-off and in particular in providing low cost testbeds to study this phenomenon. This research discusses a low-cost testbed hardware design and the potential of the proposed Adaptive-Smart Energy Management Tool (A-SEM tool) to balance the level of comfort and energy consumption efficiency. We implement an adaptive energy limitation algorithm which uses up to 30 days historical data. The energy consumption is influenced by user behaviour which is monitored by the system sensors and energy limits are adapted for the provision of comfort. A smart home user is able to set the monthly energy consumption budget which determines the initial level of daily energy limitation. A-SEM performs real time monitoring and controlling, mainly considering shiftable loads evaluated at the testing stage. We test 3 possible conditions (possible modes of operation) and prove that our “adaptive limit” energy limitation algorithm is the most successful in balancing the level of comfort and energy efficiency. For a fixed budget and energy price, the proposed adaptive approach meets user level of comfort (our main priority) as well as achieving some energy savings. In our test the A-SEM tool provides user comfort, meets the monthly budget constraint and yet shows an energy saving of 2.62{\%} which can increase or decrease depending on user behaviour. We present results showing energy saving levels, comfort levels and efficiency levels. The proposed A-SEM tool is low cost, implements an uncomplicated adaptive algorithm and therefore has the potential to be an affordable smart energy management system in future smart homes.",
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