Determination of thermal preferences based on event analysis

Determination of thermal preferences based on event analysis Real thermal preferences of occupants are rarely considered by the automatic control of HVAC systems. It is due to difficulties in describing satisfactory thermal conditions, especially when opinion of many people has to be taken into account. This work presents a method which allows to determine the preferred temperature and the associated relative humidity for a group of occupants in the room equipped with a manually controlled local cooling/heating system. It was assumed that thermal preferences of the group are reflected in the way they operate such system. The method is based on the continuous monitoring of air temperature and relative humidity and the detection of events. An event is defined by the time period between succeeding adjustments of the heating/cooling device. During events, temperature and relative humidity behave in a characteristic manner. Patterns of their periodic variation were determined using Discrete Fourier Transform and used for the detection of events. The preferred temperature can be derived from the descriptive statistics of temperature during detected events. The method was developed and calibrated for an air conditioned office. The relevant data was collected during summer period. The analysis showed that the method is successful in retrieving the preferred temperature and it is less effective in reproducing the preferred temperature range. Events were more accurately detected when using patterns of temperature variation (false negative detection rate was 14.00% and false positive detection rate was 4.44%) compared with patterns of variation of relative humidity. The approach is computationally efficient and after calibration, it may be directly applied to evaluate local thermal preferences. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Energy and Buildings Elsevier

Determination of thermal preferences based on event analysis

Loading next page...
 
/lp/elsevier/determination-of-thermal-preferences-based-on-event-analysis-oHKTL3Wd03
Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier B.V.
ISSN
0378-7788
eISSN
1872-6178
D.O.I.
10.1016/j.enbuild.2018.02.014
Publisher site
See Article on Publisher Site

Abstract

Real thermal preferences of occupants are rarely considered by the automatic control of HVAC systems. It is due to difficulties in describing satisfactory thermal conditions, especially when opinion of many people has to be taken into account. This work presents a method which allows to determine the preferred temperature and the associated relative humidity for a group of occupants in the room equipped with a manually controlled local cooling/heating system. It was assumed that thermal preferences of the group are reflected in the way they operate such system. The method is based on the continuous monitoring of air temperature and relative humidity and the detection of events. An event is defined by the time period between succeeding adjustments of the heating/cooling device. During events, temperature and relative humidity behave in a characteristic manner. Patterns of their periodic variation were determined using Discrete Fourier Transform and used for the detection of events. The preferred temperature can be derived from the descriptive statistics of temperature during detected events. The method was developed and calibrated for an air conditioned office. The relevant data was collected during summer period. The analysis showed that the method is successful in retrieving the preferred temperature and it is less effective in reproducing the preferred temperature range. Events were more accurately detected when using patterns of temperature variation (false negative detection rate was 14.00% and false positive detection rate was 4.44%) compared with patterns of variation of relative humidity. The approach is computationally efficient and after calibration, it may be directly applied to evaluate local thermal preferences.

Journal

Energy and BuildingsElsevier

Published: May 1, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • No expiration
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches

$49/month

Start Free Trial

14-day Free Trial

Best Deal — 39% off

Annual Plan

  • All the features of the Professional Plan, but for 39% off!
  • Billed annually
  • No expiration
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.

$588

$360/year

billed annually
Start Free Trial

14-day Free Trial