Optimum Energy Management for Air Conditioners in IoT-Enabled Smart Home
This paper addresses the optimal pre-cooling problem for air conditioners (AC) used in Internet of Things (IoT)-enabled smart homes while ensuring that user-defined thermal comfort can be achieved. The proposed strategy utilises renewable energy generation periods and moves some of the air condition...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/19/7102 |
| _version_ | 1797477018212761600 |
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| author | Ashleigh Philip Shama Naz Islam Nicholas Phillips Adnan Anwar |
| author_facet | Ashleigh Philip Shama Naz Islam Nicholas Phillips Adnan Anwar |
| author_sort | Ashleigh Philip |
| collection | DOAJ |
| description | This paper addresses the optimal pre-cooling problem for air conditioners (AC) used in Internet of Things (IoT)-enabled smart homes while ensuring that user-defined thermal comfort can be achieved. The proposed strategy utilises renewable energy generation periods and moves some of the air conditioning loads to these periods to reduce the electricity demand. In particular, we propose a multi-stage approach which maximises the utilisation of renewable energy at the first stage to satisfy air conditioning loads, and then schedules residual energy consumption of these loads to low price periods at the second stage. The proposed approach is investigated for the temperature and renewable generation data of NSW, Australia, over the period 2012–2013. It is shown that the approach developed can significantly reduce the energy consumption and cost associated with AC operation for nearly all days in summer when cooling is required. Specifically, the proposed approach was found to achieve a 24% cost saving in comparison to the no pre-cooling case for the highest average temperature day in January, 2013. The analysis also demonstrated that the proposed scheme performed better when the thermal insulation levels in the smart home are higher. However, the optimal pre-cooling scheme can still achieve reduced energy costs under lower thermal insulation conditions compared to the no pre-cooling case. |
| first_indexed | 2024-03-09T21:12:00Z |
| format | Article |
| id | doaj.art-57474b1392684a90a7d17fe0598c30d4 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T21:12:00Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-57474b1392684a90a7d17fe0598c30d42023-11-23T21:43:23ZengMDPI AGSensors1424-82202022-09-012219710210.3390/s22197102Optimum Energy Management for Air Conditioners in IoT-Enabled Smart HomeAshleigh Philip0Shama Naz Islam1Nicholas Phillips2Adnan Anwar3Deakin University, Waurn Ponds, VIC 3216, AustraliaDeakin University, Waurn Ponds, VIC 3216, AustraliaItron Australasia, Melbourne, VIC 3000, AustraliaStrategic Centre for Cyber Security Research and Innovation (CSRI), School of Information Technology, Deakin University, Waurn Ponds, Geelong, VIC 3216, AustraliaThis paper addresses the optimal pre-cooling problem for air conditioners (AC) used in Internet of Things (IoT)-enabled smart homes while ensuring that user-defined thermal comfort can be achieved. The proposed strategy utilises renewable energy generation periods and moves some of the air conditioning loads to these periods to reduce the electricity demand. In particular, we propose a multi-stage approach which maximises the utilisation of renewable energy at the first stage to satisfy air conditioning loads, and then schedules residual energy consumption of these loads to low price periods at the second stage. The proposed approach is investigated for the temperature and renewable generation data of NSW, Australia, over the period 2012–2013. It is shown that the approach developed can significantly reduce the energy consumption and cost associated with AC operation for nearly all days in summer when cooling is required. Specifically, the proposed approach was found to achieve a 24% cost saving in comparison to the no pre-cooling case for the highest average temperature day in January, 2013. The analysis also demonstrated that the proposed scheme performed better when the thermal insulation levels in the smart home are higher. However, the optimal pre-cooling scheme can still achieve reduced energy costs under lower thermal insulation conditions compared to the no pre-cooling case.https://www.mdpi.com/1424-8220/22/19/7102energy managementpre-coolingair conditionersIoT-enabled smart hometime of use |
| spellingShingle | Ashleigh Philip Shama Naz Islam Nicholas Phillips Adnan Anwar Optimum Energy Management for Air Conditioners in IoT-Enabled Smart Home Sensors energy management pre-cooling air conditioners IoT-enabled smart home time of use |
| title | Optimum Energy Management for Air Conditioners in IoT-Enabled Smart Home |
| title_full | Optimum Energy Management for Air Conditioners in IoT-Enabled Smart Home |
| title_fullStr | Optimum Energy Management for Air Conditioners in IoT-Enabled Smart Home |
| title_full_unstemmed | Optimum Energy Management for Air Conditioners in IoT-Enabled Smart Home |
| title_short | Optimum Energy Management for Air Conditioners in IoT-Enabled Smart Home |
| title_sort | optimum energy management for air conditioners in iot enabled smart home |
| topic | energy management pre-cooling air conditioners IoT-enabled smart home time of use |
| url | https://www.mdpi.com/1424-8220/22/19/7102 |
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