Finding the Sweet Spot: Balancing Thermal Comfort and Building Energy Consumption for a Sustainable Future

Are you interested in understanding the relationship between thermal comfort and building energy performance? Then, you might want to check out a fascinating publication by Liu Yang, Haiyan Yan, and Joseph C. Lam. This paper explores various adaptive methods and empirical models for evaluating thermal comfort and their implications for building energy savings.

In this article, we’ll dive into the topic of “thermal comfort evaluation methods and building energy savings” and discuss the different approaches to thermal comfort evaluation found in this publication. Whether you’re a researcher or an enthusiast, this article will give you a glimpse of the exciting world of thermal comfort evaluation.

In this study, social-economical and cultural studies, as well as general and past occupancy studies, have been utilized to obtain the research findings. Predicting methods targeting future climatic changes and fuel/energy availability was also an objective of this study. Future predictions and sustainable approaches are, of course, very important for future work.

📢 Some important findings

• • The PMV method is accurate for air conditioned spaces, but not for naturally ventilated building environments.

• • An increased indoor temperature set-point (considered comfortable), lowers energy usage during the summer. Similarly, indoor temperature setpoints go up during the winter, causing high energy demand for space cooling. However, it depends on the HVAC system and the number of occupants in the building.

As a result of conducting numerous research and experiments on approaches focusing on global warming, the following relationship was exposed to the world. Interestingly, these parameters are similar to the 3 Ps of sustainability.

Economy <> EnergyUse <> Carbon Emission

PER is another term used by the researchers to compare the per capita energy usage of the citizens. It was found that around 40% of PER accounts for HVAC, which has increased lately with the demand for high standards of living. In other words, in recent decades, energy consumption per person has increased rapidly due to their high standards. The same person who was comfortable sleeping with no mechanical ventilation now needs an air conditioner or a fan.

As a result, in today’s world, thermal comfort has ranked top compared to visual and acoustic comfort and indoor air quality. People are willing to bear any cost to stay thermally comfortable, regardless of the increasing cost of energy. As I discuss this part, I would like to share some information about the types of buildings that are defined by industry experts and researchers when working on HVAC requirements. They are as follows:

1. 1. Residential

1. 1. Commercial

1. 1. Industrial

Out of these three categories, commercial building designers rarely care about energy savings and sustainability because they could easily cover the cost directly from the customers by including that in the product or service prices. However, when it comes to residential and industrial applications, energy savings are a huge concern, and designers almost always prefer natural ventilation.

 

📚 Thermal Comfort Models

As discussed, thermal comfort has been a trending topic since the mid-20th century, and thousands of research studies have been conducted to find methods that could be used to evaluate and predict thermal comfort levels in a selected building environment. There are two main methods used by industrial experts and researchers when studying thermal comfort:

1. 1. Heat balance model
      1. 1. from experiments conducted in climate chambers
      1. 1. steady and consistent results

1. 1. Adaptive model
      1. 1. measured data from surveys and field visits

 

🏃🏼‍♂️ Heat Balance Model

This model assumes that the human thermoregulatory system keeps the human body at a constant temperature by exchanging heat and mass with the immediate environment. Thermal sensations (hot/cold) are found to be proportional to the magnitude of these incidents and parameters. Latent heat loss, mean skin temperature, and wittedness due to sweating are some of the examples. I will discuss more on human heat balance using the ASHRAE Handbook and other sources, in upcoming articles.

 

📈 Fanger Model

Fanger (1970) developed a model to predict the thermal comfort level in a controlled environment using his findings about relationship between,

1. 1. Mean temperature and activity level.

1. 1. Sweat secretion and activity level.

Later, this model was compared with the famous 7-point comfort scale, and the ASHARE 55 thermal comfort scale was created. Fanger’s model was and is being referred to by so many researchers globally, as it is a highly accurate and reliable method of predicting satisfactory thermal levels when designing buildings.

 

🗳️ Predicted Mean Vote (PMV)

PMV is a quantitative thermal comfort assessing model created to predict the satisfactory levels of average occupants inside a built environment (i.e., an indoor space created with controlled air conditioning and temperature). PMV method is a function of the following,

1. 1. Dry bulb (air) temperature.

1. 1. Mean radiant temperature.

1. 1. Air humidity.

1. 1. Relative air velocity.

1. 1. Occupant activity level.

1. 1. Clothing factor.

When conducting thermal comfort questionnaires, researchers get feedback from occupants on a 7-point scale. These values are thereafter compared with predicted (theoretical) PMV values. It was found that the PMV model is more accurate for indoor built environments than uncontrolled outdoor spaces, as I discussed previously. However, for well designed and controlled indoor spaces, this model is said to be accurate most of the time.

 

🙅🏽‍♀️ Predicted Percentage Dissatisfaction (PPD)

This model was created because dissatisfied people are the most likely community to complain. There’s an empirical relationship between PPD and PMV. However, these models are most of the time accurate only for controlled environments.

Even at PMV = 0, there can be people who are dissatisfied. Therefore, this model is very important in predicting occupant thermal comfort levels when designing building environments, as an extended comfortable temperature range can save a lot of energy. In other words, small changes in indoor set temperatures could save millions of dollars annually when it comes to huge commercial buildings. The accuracy of PPD calculations is found below in various studies conducted worldwide.

• • 80% overall accuracy for occupants in built environments.

• • Plus or minus 10% deviations in actual PMV. (i.e., -0.5 < PMV < 0.5).

• • Additional 10% error for PPD calculations when local discomfort is available.

Even though the PMV model has activity levels and clothing factors in it, these experiments were conducted inside climate chambers, giving no information on the changes people make when adapting to outside thermal environments.

In general, people do not resist any thermal environment, but tend to restore their thermal comfort when the environment changes. There are three main adaptation methods: psychological, physiological, and physical. These modes of adaptation are discussed in depth in my previous blog article on psychological adaptation to thermal comfort.

 

✅ Comfortable Temperature Range

The below figure, extracted from ASHRAE Trans 1998, shows different indoor temperature values and the respective temperatures that occupants found comfortable. Each point represents an average value taken from the feedback of a sample population. For example, at an indoor temperature close to 15 ºC, occupants preferred a slightly higher temperature (close to 20 ºC); while indoor temperature values between 17 ºC and 30 ºC were identified as comfortable temperatures. From the results, it can be assumed that the outliers (values outside this range) are caused by social, psychological, and economic aspects of the occupants.

 

✍🏼 Conclusion

In conclusion, this article has explored the topic of thermal comfort evaluation methods and building energy savings, and highlighted the various approaches found in the publication by Liu Yang, Haiyan Yan, and Joseph C. Lam.

It was discussed that while there are numerous empirical and theoretical methods for assessing thermal comfort, the results obtained are subjective and depend on various parameters. Nonetheless, the findings of this research are crucial in benefiting the industry and individual researchers alike. As we continue to strive for energy-efficient buildings and sustainable practices, understanding thermal comfort and its implications for building energy performance is crucial. I hope that this article has provided you with valuable insights into this fascinating research area.

 

👨🏽‍🎓 Reference

• • Thermal comfort and building energy consumption implications – A reviewby – Liu Yang, Haiyan Yan, and Joseph C. Lam.