智能电网中多分区商业建筑的分布式灵活性表征与资源分配

H. Hao, Jianming Lian, K. Kalsi, J. Stoustrup
{"title":"智能电网中多分区商业建筑的分布式灵活性表征与资源分配","authors":"H. Hao, Jianming Lian, K. Kalsi, J. Stoustrup","doi":"10.1109/CDC.2015.7402693","DOIUrl":null,"url":null,"abstract":"The HVAC (Heating, Ventilation, and Air-Conditioning) system of commercial buildings is a complex system with a large number of dynamically interacting components. In particular, the thermal dynamics of each zone are coupled with those of its neighboring zones. In this paper, we study an agent-based approach to model and control commercial building HVAC system for providing ancillary services to the power grid. In the multi-agent-building-system (MABS), individual zones are modeled as agents that can communicate, interact, and negotiate with one another to achieve a common objective. We first propose a distributed characterization method on the aggregate airflow (and thus fan power) flexibility that the HVAC system can provide to the ancillary service market. A Nash-bargaining-based airflow allocation strategy is then proposed to track a dispatch signal while respecting the preference and flexibility of individual zones. Moreover, we devise a distributed algorithm to obtain the Nash bargaining solution via dual decomposition. Numerical simulations illustrate that the proposed distributed protocols are much more scalable than centralized approaches especially when the system becomes larger and more complex.","PeriodicalId":308101,"journal":{"name":"2015 54th IEEE Conference on Decision and Control (CDC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Distributed flexibility characterization and resource allocation for multi-zone commercial buildings in the smart grid\",\"authors\":\"H. Hao, Jianming Lian, K. Kalsi, J. Stoustrup\",\"doi\":\"10.1109/CDC.2015.7402693\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The HVAC (Heating, Ventilation, and Air-Conditioning) system of commercial buildings is a complex system with a large number of dynamically interacting components. In particular, the thermal dynamics of each zone are coupled with those of its neighboring zones. In this paper, we study an agent-based approach to model and control commercial building HVAC system for providing ancillary services to the power grid. In the multi-agent-building-system (MABS), individual zones are modeled as agents that can communicate, interact, and negotiate with one another to achieve a common objective. We first propose a distributed characterization method on the aggregate airflow (and thus fan power) flexibility that the HVAC system can provide to the ancillary service market. A Nash-bargaining-based airflow allocation strategy is then proposed to track a dispatch signal while respecting the preference and flexibility of individual zones. Moreover, we devise a distributed algorithm to obtain the Nash bargaining solution via dual decomposition. Numerical simulations illustrate that the proposed distributed protocols are much more scalable than centralized approaches especially when the system becomes larger and more complex.\",\"PeriodicalId\":308101,\"journal\":{\"name\":\"2015 54th IEEE Conference on Decision and Control (CDC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 54th IEEE Conference on Decision and Control (CDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.2015.7402693\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 54th IEEE Conference on Decision and Control (CDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.2015.7402693","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18

摘要

商业建筑的暖通空调系统是一个由大量动态相互作用的部件组成的复杂系统。特别是,每个区域的热动力学与其相邻区域的热动力学是耦合的。本文研究了一种基于智能体的商用建筑暖通空调系统的建模与控制方法。在多智能体构建系统(MABS)中,单个区域被建模为能够相互通信、交互和协商以实现共同目标的智能体。我们首先提出了一种分布式表征方法,用于分析暖通空调系统可以为辅助服务市场提供的总气流(以及风扇功率)灵活性。然后提出了一种基于纳什交易的气流分配策略,以跟踪调度信号,同时尊重各个区域的偏好和灵活性。此外,我们设计了一种分布式算法,通过对偶分解获得纳什议价解。数值模拟结果表明,分布式协议比集中式协议具有更大的可扩展性,特别是当系统变得更大、更复杂时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed flexibility characterization and resource allocation for multi-zone commercial buildings in the smart grid
The HVAC (Heating, Ventilation, and Air-Conditioning) system of commercial buildings is a complex system with a large number of dynamically interacting components. In particular, the thermal dynamics of each zone are coupled with those of its neighboring zones. In this paper, we study an agent-based approach to model and control commercial building HVAC system for providing ancillary services to the power grid. In the multi-agent-building-system (MABS), individual zones are modeled as agents that can communicate, interact, and negotiate with one another to achieve a common objective. We first propose a distributed characterization method on the aggregate airflow (and thus fan power) flexibility that the HVAC system can provide to the ancillary service market. A Nash-bargaining-based airflow allocation strategy is then proposed to track a dispatch signal while respecting the preference and flexibility of individual zones. Moreover, we devise a distributed algorithm to obtain the Nash bargaining solution via dual decomposition. Numerical simulations illustrate that the proposed distributed protocols are much more scalable than centralized approaches especially when the system becomes larger and more complex.
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:604180095
Book学术官方微信