基于随机模型预测控制的独立空调节能潜力评价——以印度为例

Tiyasa Ray, S. Majumdar, S. Mukherjee
{"title":"基于随机模型预测控制的独立空调节能潜力评价——以印度为例","authors":"Tiyasa Ray, S. Majumdar, S. Mukherjee","doi":"10.1109/ICONCE.2014.6808742","DOIUrl":null,"url":null,"abstract":"Reduction in energy consumption has become imperative in the modern day. The building segment is responsible for almost 40% consumption. These installations are typically located at the distribution level. There are losses associated with the transmission system, such as T&D Losses and pilferage losses. Hence a single unit of energy saved at distribution level would amount to greater savings at the generation level. Developing nations rely largely on standalone Air Conditioning units for office and domestic use since these facilities rarely designed to accommodate centralized Heating ventilation and Air Conditioning (HVAC) systems. In this paper a novel approach to control all these air conditioning units using a centralized controller based on Stochastic Model Predictive Control (SMPC) has been presented. The SMPC takes into account the predicted weather to reduce energy consumption while maintaining the comfort level of the occupants. A sample office space has been modeled and performance of the algorithm has been studied for weather conditions of large cities of India. With centralized SMPC the system has significantly outperformed the existing SAC with localized controller.","PeriodicalId":109404,"journal":{"name":"2014 1st International Conference on Non Conventional Energy (ICONCE 2014)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Evaluation of energy saving potential using Stochastic Model Predictive Control for stand alone Air Conditioning units a study in Indian scenario\",\"authors\":\"Tiyasa Ray, S. Majumdar, S. Mukherjee\",\"doi\":\"10.1109/ICONCE.2014.6808742\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reduction in energy consumption has become imperative in the modern day. The building segment is responsible for almost 40% consumption. These installations are typically located at the distribution level. There are losses associated with the transmission system, such as T&D Losses and pilferage losses. Hence a single unit of energy saved at distribution level would amount to greater savings at the generation level. Developing nations rely largely on standalone Air Conditioning units for office and domestic use since these facilities rarely designed to accommodate centralized Heating ventilation and Air Conditioning (HVAC) systems. In this paper a novel approach to control all these air conditioning units using a centralized controller based on Stochastic Model Predictive Control (SMPC) has been presented. The SMPC takes into account the predicted weather to reduce energy consumption while maintaining the comfort level of the occupants. A sample office space has been modeled and performance of the algorithm has been studied for weather conditions of large cities of India. With centralized SMPC the system has significantly outperformed the existing SAC with localized controller.\",\"PeriodicalId\":109404,\"journal\":{\"name\":\"2014 1st International Conference on Non Conventional Energy (ICONCE 2014)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 1st International Conference on Non Conventional Energy (ICONCE 2014)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICONCE.2014.6808742\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 1st International Conference on Non Conventional Energy (ICONCE 2014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICONCE.2014.6808742","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

在现代社会,减少能源消耗已成为当务之急。建筑部分占了近40%的消耗。这些安装通常位于分发级。还有与输电系统有关的损失,如输配电损失和窃电损失。因此,在配电层面节省一个单位的能源将相当于在发电层面节省更多的能源。发展中国家在很大程度上依赖于办公室和家庭使用的独立空调机组,因为这些设施很少设计用于容纳集中供暖通风和空调(HVAC)系统。本文提出了一种基于随机模型预测控制(SMPC)的集中控制器控制所有空调机组的新方法。SMPC考虑到预测的天气,以减少能源消耗,同时保持居住者的舒适度。以一个办公空间为样本进行了建模,并研究了该算法在印度大城市天气条件下的性能。采用集中式SMPC的系统明显优于现有的采用局部控制器的SAC。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of energy saving potential using Stochastic Model Predictive Control for stand alone Air Conditioning units a study in Indian scenario
Reduction in energy consumption has become imperative in the modern day. The building segment is responsible for almost 40% consumption. These installations are typically located at the distribution level. There are losses associated with the transmission system, such as T&D Losses and pilferage losses. Hence a single unit of energy saved at distribution level would amount to greater savings at the generation level. Developing nations rely largely on standalone Air Conditioning units for office and domestic use since these facilities rarely designed to accommodate centralized Heating ventilation and Air Conditioning (HVAC) systems. In this paper a novel approach to control all these air conditioning units using a centralized controller based on Stochastic Model Predictive Control (SMPC) has been presented. The SMPC takes into account the predicted weather to reduce energy consumption while maintaining the comfort level of the occupants. A sample office space has been modeled and performance of the algorithm has been studied for weather conditions of large cities of India. With centralized SMPC the system has significantly outperformed the existing SAC with localized controller.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信