Review of modern demand control solutions and technologies for HVAC operation

Author:

Borodinecs Anatolijs,Zemitis Jurgis,Palcikovskis Arturs,Ardavs Arturs,Lavendelis Egons

Abstract

HVAC systems, which use traditional control strategies with fixed ventilation rates or with ventilation rate schedules, do not adjust according to the required IAQ and thermal comfort. As a result, building spaces are being over or under-ventilated. In this paper, the latest modern solutions for demand-controlled HVAC system operation are analyzed, based on the review of existing studies. Such modern technologies as human detection systems, computer vision, and neural network applications are looked at. Different types of human presence detection are presented based on the applied technology. The most common ones are indirect detection based on the usage data of existing IT equipment, and direct detection through the use of passive infrared sensors, wearable tags, and vision sensors. Also, the potential solutions of human activity monitoring, skin temperature, and clothing level detection systems are examined. The studies discussed in this paper show real application examples and prove the benefits of using the technologies for the control of ventilation systems in various building types. Research has shown that such technologies have a favorable effect on both indoor air quality and system energy consumption. In the future, the ventilation system should be equipped with cameras for a more accurate analysis of the room and occupancy. Also, the systems must consider occupant behavior, activity, and other information, which can be used for indoor environment quality improvement. Based on the gained knowledge a sensor capable of human detection, accounting, and location marking is developed.

Publisher

EDP Sciences

Subject

General Medicine

Reference30 articles.

1. Heat recovery ventilation operation traded off against natural and simple exhaust ventilation in Europe by primary energy factor, carbon dioxide emission, household consumer price and exergy

2. Borodinecs A., Zemitis J., and Palcikovskis A., Energies 15, (2022)

3. Duan Z., Ozan Tezcan M., Nakamura H., Ishwar P., and Konrad J., in IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. Work. (2020)

4. Melfi R., Rosenblum B., Nordman B., and Christensen K., in 2011 Int. Green Comput. Conf. Work. IGCC 2011 (n.d.)

5. Brown N., Bull R., Faruk F., and Ekwevugbe T., Energy Build 2012, 47 (n.d.)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3