{"title":"开关式空调显式模型预测温度控制的评价","authors":"Abdulhafiz Chesof, S. Panaudomsup, T. Cheypoca","doi":"10.23919/ICCAS.2017.8204304","DOIUrl":null,"url":null,"abstract":"The objective is to evaluate the performance of an explicit model predictive control for controlling the room temperature actuated by the on-off air conditioner to minimize the energy usage by reducing the working time of a compressor. There are a lot of on-off air conditioners already installed in the educational building in Thailand. To replace all of those by the inverter air conditioner or HVAC system, the high investment cost is required. Therefore, the on-off air conditioners continue to work in such building. The effective solution may be the low cost control unit which is simple like a remote control. The method is to design the remote control embedded by the temperature sensor and the explicit model predictive control that is based on the off-line optimization. The experiment is performed in the laboratory room with dimension 4×7×3.5 m (WxLxH) actuated by Saijo Denki 18,320 Btu on-off air conditioner. The experimental results reveal that the temperature reaches the desired value 25 degree Celsius within 10 minute and keeps fluctuating between 23 and 26 degree Celsius. The working time of compressor is reduced 33.33 %. The result shows that the explicit model predictive control is effective for the remote control application in terms of the implementation and energy saving.","PeriodicalId":140598,"journal":{"name":"2017 17th International Conference on Control, Automation and Systems (ICCAS)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Evaluation of explicit model predictive temperature control for on-off air conditioner\",\"authors\":\"Abdulhafiz Chesof, S. Panaudomsup, T. Cheypoca\",\"doi\":\"10.23919/ICCAS.2017.8204304\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective is to evaluate the performance of an explicit model predictive control for controlling the room temperature actuated by the on-off air conditioner to minimize the energy usage by reducing the working time of a compressor. There are a lot of on-off air conditioners already installed in the educational building in Thailand. To replace all of those by the inverter air conditioner or HVAC system, the high investment cost is required. Therefore, the on-off air conditioners continue to work in such building. The effective solution may be the low cost control unit which is simple like a remote control. The method is to design the remote control embedded by the temperature sensor and the explicit model predictive control that is based on the off-line optimization. The experiment is performed in the laboratory room with dimension 4×7×3.5 m (WxLxH) actuated by Saijo Denki 18,320 Btu on-off air conditioner. The experimental results reveal that the temperature reaches the desired value 25 degree Celsius within 10 minute and keeps fluctuating between 23 and 26 degree Celsius. The working time of compressor is reduced 33.33 %. The result shows that the explicit model predictive control is effective for the remote control application in terms of the implementation and energy saving.\",\"PeriodicalId\":140598,\"journal\":{\"name\":\"2017 17th International Conference on Control, Automation and Systems (ICCAS)\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 17th International Conference on Control, Automation and Systems (ICCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ICCAS.2017.8204304\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 17th International Conference on Control, Automation and Systems (ICCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ICCAS.2017.8204304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
目的是评估一种显式模型预测控制的性能,用于控制由开关空调驱动的室温,通过减少压缩机的工作时间来最大限度地减少能源使用。泰国的教育大楼里已经安装了很多开关式空调。如果全部用变频空调或暖通空调系统替代,投资成本高。因此,在这样的建筑中,开关式空调继续工作。有效的解决方案可能是像遥控器一样简单的低成本控制单元。该方法是设计嵌入温度传感器的远程控制和基于离线优化的显式模型预测控制。实验在尺寸为4×7×3.5 m (WxLxH)的试验室中进行,由Saijo Denki 18320 Btu开关空调驱动。实验结果表明,温度在10分钟内达到所需值25℃,并在23 ~ 26℃之间波动。压缩机工作时间缩短33.33%。结果表明,显式模型预测控制在实现和节能方面对远程控制应用是有效的。
Evaluation of explicit model predictive temperature control for on-off air conditioner
The objective is to evaluate the performance of an explicit model predictive control for controlling the room temperature actuated by the on-off air conditioner to minimize the energy usage by reducing the working time of a compressor. There are a lot of on-off air conditioners already installed in the educational building in Thailand. To replace all of those by the inverter air conditioner or HVAC system, the high investment cost is required. Therefore, the on-off air conditioners continue to work in such building. The effective solution may be the low cost control unit which is simple like a remote control. The method is to design the remote control embedded by the temperature sensor and the explicit model predictive control that is based on the off-line optimization. The experiment is performed in the laboratory room with dimension 4×7×3.5 m (WxLxH) actuated by Saijo Denki 18,320 Btu on-off air conditioner. The experimental results reveal that the temperature reaches the desired value 25 degree Celsius within 10 minute and keeps fluctuating between 23 and 26 degree Celsius. The working time of compressor is reduced 33.33 %. The result shows that the explicit model predictive control is effective for the remote control application in terms of the implementation and energy saving.