Developing a Thermal Comfort Report Card for Building

Energy savings and occupant thermal comfort are the two most important factors in controlling heating ventilation and air conditioning (HVAC) operation in buildings. Typically, it is found that thermal comfort is not always met in buildings. Hence, there is still an opportunity to improve indoor thermal comfort, and at the same time save energy by controlling HVAC set points. The objective of this paper is to propose a method to obtain energy savings by adjusting HVAC set points based on occupant comfort measured using Predicted Mean Vote (PMV) and occupancy information. The idea is to calculate hourly PMV values based on real-time occupancy information, indoor temperature set points and humidity in a building. Then, a new set of temperature set points that can maintain occupant comfort, i.e., PMV = 0, is derived. To evaluate the effectiveness of the proposed method, a building model is developed in eQUEST using the information from a real-world building located in Alexandria, VA. Research findings indicate that HVAC electrical consumption savings of 14.58% is achieved when the proposed set point adjustment method is implemented as compared to that of the base case. To study the impact of adding occupancy information on HVAC energy savings, another scenario is simulated where HVAC set point is increased when the building is unoccupied, e.g., during lunchtime or holidays. Research findings indicate that additional HVAC electrical consumption savings of 8.79% is achieved when taking into account occupancy information in HVAC control.

Managing thermal comfort in contemporary high-rise residential buildings: Using smart thermostats and surveys to identify energy efficiency and comfort opportunities

In the paper there are presented the problems of optimal control for indoor thermal comfort in buildings equipped with HVAC (Heating, Ventilation and Air Conditioning) systems. It is very important that the design of such control systems allows to minimize the energy consumption. There are discussed the results of air-conditioning system simulation and there is given an example of simulation model of a room and mathematical model of thermal comfort. Fuzzy control algorithms and model predictive control algorithms are used in the hierarchical structure of climate comfort control system. The tuning of predictive controllers is discussed in the paper, too.

Studies indicate that the energy performance gap between real and calculated energy use can be explained for 80% by occupant behaviour. This human factor may be composed of routine and thermoregulatory behaviour. When occupants do not feel comfortable due to high or low operative temperatures and resulting high or low skin temperatures, they are likely to exhibit thermoregulatory behaviour. The aim of this study is to monitor and understand this thermoregulatory behaviour of the occupant. This is a detailed study of two females living in a rowhouse in the city of Heerlen (Netherlands). During a monitoring period of three weeks over a time span of three months the following parameters were monitored: activity level, clothing, micro climate, skin temperatures and thermal comfort and sensation. Their micro climate was measured at five positions on the body to assess exposed near body conditions and skin temperature. Every two hours they filled in a questionnaire regarding their thermal comfort and sensation level (7-point scale), clothing, activities and thermoregulatory behaviour. The most comfortable (optimal) temperature was calculated for each person by adopting a biophysical model, a thermoneutral zone model. This study shows unique indivual comfort patterns in relation to ambient conditions. An example is given how this information can be used to calculate the buildings energy comsumption.

The healthcare sector is a significant contributor to global energy consumption, particularly within the heating, ventilation, and air conditioning (HVAC) market, due to stringent requirements for maintaining indoor thermal comfort for patients, staff, and visitors in hospital wards, rooms, and intensive care units. This study presents a novel approach employing a Machine Learning-based Linear Regression Algorithm to predict indoor adaptive thermal comfort within the inpatient medical wards. The methodology establishes a robust correlation between key indoor environmental parameters including air temperature, relative humidity, and air velocity, and thermal comfort indices, including Predicted Mean Vote (PMV) and Predicted Percentage Dissatisfied (PPD). Real-time measurements of indoor environmental conditions were conducted in selected hospitals in Islamabad, Pakistan, utilizing calibrated sensors to capture ambient temperature, wet bulb globe temperature, relative humidity, air velocity, light intensity, and CO₂ levels. This empirical data was integrated with responses from thermal comfort questionnaires, assessing the perceptions of patients, medical staff, and visitors regarding thermal sensation, acceptability, preference, and overall comfort. The adaptive ML-based, predictive analysis identified optimal thermal comfort ranges for hospital wards, recommending indoor air temperatures between 22.0°C and 23.0°C, relative humidity levels between 50% and 55%, and air velocities between 0.1 and 0.2 m/s. The findings revealed a significant impact of overcooling and undercooling on PMV and PPD levels, emphasizing the need for precise HVAC system control to enhance both energy efficiency and occupant comfort. This research contributes to advancing adaptive thermal comfort modeling in healthcare facilities, offering insights for sustainable HVAC management and improved patient outcomes.

ВПЛИВ ОБРОБІТКУ ҐРУНТУ

Climate change, its causes and effects have become a topical issue in the world today. Universal increases in temperature and sea levels, are evidences of this global phenomenon. In the field of architecture, climate-resilient and climate-responsive domestic buildings are being developed to adapt to changing climates, while being socio-economically suited to their geographical contexts. Much research in this area has been carried out in developing tropical countries such as Nigeria. Most studies concentrate on passive optimisation of building envelopes to promote thermal comfort and reduce reliance on active mechanical controls which worsen climate change. Thus, it may be said that thermal comfort has been established as a link between climate change and housing. In south-west Nigeria, where an abundance of tropical rainforests engenders a hot-humid climate, achieving thermal comfort in buildings is a major need. Studies show that of all house envelopes in south-west Nigeria through time, two housing styles namely the pre-colonial traditional and colonial modernist styles best demonstrate effective use of climatic design principles in achieving thermally comfortable interiors. However, due to cultural changes over time, a third style of housing which is referred to as contemporary south-west Nigerian housing, is currently the most preferred form of housing. South-west Nigerian contemporary house shows considerable influence from the International Style. This housing style features envelopes with minimum use of climatic design principles and maximum reliance on mechanical cooling devices such as air conditioners, in providing indoor thermal comfort. These mechanical devices, however, are known for aggravating south-west Nigerian climate change. To reduce the aggravation of climate change caused by south-west Nigerian contemporary housing envelopes, this study proposes a free-running contemporary house envelope which promotes thermal comfort in present and future south-west Nigerian climates. As such, the study extensively reviewed climatic design principles and thermal standards applicable in tropical climates as well as material on chronological south-west Nigerian housing developments. The study modelled and evaluated the thermal performance of a free-running, base-case contemporary house envelope in present and future climates, using DesignBuilder’s dynamic thermal simulations. South-west Nigerian present and future climatic data used in the simulations, were generated by the climatic data source and calculation software Meteonorm. South-west Nigerian present climatic data was validated by readings from data loggers placed in a real-live contemporary base-case house in the region. The results of this study’s simulations confirmed that the free-running, base-case contemporary house envelope does not promote thermal comfort in present climates, hence the current supplementary mechanical thermal controls. Additionally, the results showed that the contemporary envelope would not promote thermal comfort in future south-west Nigerian climates. As such, this study then proceeded to optimise the contemporary house envelope to improve its thermal performance in south-west Nigerian present and future climates. This optimisation involved adjusting the envelope specifications under the following parameters: headroom height, external wall (thermal mass, insulation and thickness), internal ground floor (thermal mass, insulation and thickness), roof (thermal mass, pitch, structure, overhang length, covering), external window (size, type, glazing thickness and type), azimuth angle (building orientation) and ground floor elevation distance. These parameters were based on Szokolay’s (2014) climatic design principles. The results showed that optimising the south-west Nigerian contemporary envelope under those parameters improved its thermal performance, enabling it to provide indoor thermal comfort in present and future south-west Nigerian climates. Accordingly, this study’s main contribution is the proposal of a free-running climate-responsive south-west Nigerian contemporary house envelope which promotes indoor thermal comfort in present and future climates. It recommends that: 1. without any need for mechanical cooling devices, the specifications of this optimised contemporary house envelope can be used to reform housing design policies in south-west Nigeria, and 2. using the optimised envelope would reduce reliance on mechanical thermal controls and therefore mitigate climate change in the region.

Thermal comfort in educational buildings: The Classroom-Comfort-Data method applied to schools in Bogotá, Colombia

Efficient management of heating, ventilation, and air conditioning (HVAC) systems is paramount for mitigating energy consumption and enhancing climate resilience in modern infrastructure. This review explores the significance of leveraging project management tools to optimize energy efficiency within HVAC operations, thus fostering a pathway towards climate resilience. The integration of project management methodologies offers a systematic approach to address challenges associated with energy consumption in HVAC systems, thereby facilitating informed decision-making processes. Firstly, the review delves into the pressing need for energy conservation in HVAC operations amidst escalating concerns over climate change and its adverse impacts. The imperative to minimize energy consumption in buildings, particularly through HVAC systems, is highlighted as a pivotal step towards achieving climate resilience and sustainability goals. Subsequently, the review outlines the role of project management tools in orchestrating effective strategies to enhance energy efficiency within HVAC operations. By employing techniques such as project scheduling, risk management, and resource allocation, project managers can streamline the implementation of energy-efficient measures, thereby optimizing HVAC system performance and reducing carbon emissions. Moreover, the review underscores the importance of data analytics and technological advancements in augmenting the efficacy of project management tools for energy efficiency in HVAC operations. Leveraging real-time data monitoring, predictive analytics, and IoT-enabled devices enables proactive maintenance and continuous optimization of HVAC systems, thereby maximizing energy savings and bolstering climate resilience. Furthermore, the review elucidates the potential benefits and challenges associated with the adoption of project management tools for energy efficiency in HVAC operations. While improved cost-effectiveness, environmental sustainability, and operational performance emerge as primary benefits, challenges such as initial investment costs, technological complexities, and organizational inertia necessitate careful consideration. This review advocates for the integration of project management tools as a viable approach to foster energy efficiency in HVAC operations, thereby paving the way towards enhanced climate resilience and sustainability in built environments. By embracing innovative methodologies and technological solutions, stakeholders can mitigate energy consumption, reduce greenhouse gas emissions, and fortify infrastructure against the impacts of climate change. Keywords: HVAC, Climate Resilience, Project Management, Energy, Review.

Diffusion of bio-climatic building design techniques in Kenya: Impediments and opportunities

Kashgar, located in China’s far west, has a typical hot-arid climate. There are a large number of low-rise high-density Islamic housing in Kashgar old City. The thermal comfort in these buildings has not yet been adequately researched. In order to obtain a comprehensive understanding about the real indoor thermal environment and the residents’ summer thermal comfort in Kashgar old City, a field investigation of 138 residential buildings was conducted in the summer time, including onsite environmental parameter measurements and simultaneous surveys using subjective thermal comfort questionnaires. Based on a statistical regression analysis of 182 valid questionnaires, a summer thermal comfort model was established. The results show that the measured summer neutral temperature of the local people is 23.4°C, and the upper limit of acceptable summer temperature for 80% of the residents is 26.9°C. The summer thermal tolerance of the residents in the Kashgar old City is lower than expected and also lower than that of the residents in rural Turpan with the same climate features. The survey also shows that the residents in the Kashgar old City have a habit of transfering living spaces over time, and the frequency of passive behaviours is higher than those of active behaviours. The above results are believed to be potentially valuable for the revision of energy conservation policies and the design practice of residential buildings in the hot-arid climate region of China, and also for areas under similar climate conditions in the world.

Maintaining both indoor air quality (IAQ) and thermal comfort in buildings along with optimized energy consumption is a challenging problem. This investigation presents a novel design for hybrid ventilation system enabled by predictive control and soft-sensors to achieve both IAQ and thermal comfort by combining predictive control with demand controlled ventilation (DCV). First, we show that the problem of maintaining IAQ, thermal comfort and optimal energy is a multi-objective optimization problem with competing objectives, and a predictive control approach is required to smartly control the system. This leads to many implementation challenges which are addressed by designing a hybrid ventilation scheme supported by predictive control and soft-sensors. The main idea of the hybrid ventilation system is to achieve thermal comfort by varying the ON/OFF times of the air conditioners to maintain the temperature within user-defined bands using a predictive control and IAQ is maintained using Healthbox 3.0, a DCV device. Furthermore, this study also designs soft-sensors by combining the Internet of Things (IoT)-based sensors with deep-learning tools. The hardware realization of the control and IoT prototype is also discussed. The proposed novel hybrid ventilation system and the soft-sensors are demonstrated in a real research laboratory, i.e., Center for Research in Automatic Control Engineering (C-RACE) located at Kalasalingam University, India. Our results show the perceived benefits of hybrid ventilation, predictive control, and soft-sensors.

The relevance is introducing fourth generation district heating (4GDH), which decreases operation and maintenance costs by utilizing the efficiency of low temperature district heating (LTDH). The aim is to develop a methodology allowing for a more flexible heat demand model and accurate function describing the relationship between outdoor temperature and heat demand. It is represented by a black-box model based on historical data collected from heating, ventilation, and air conditioning (HVAC) systems. Energy delivery/consumption is analyzed with the help of a set of statistical and regression formulas. The analysis of operational data is then transformed to methodology to regulate heat supply with combined heat-and-power (CHP) generation. The key features are that the model takes into account thermal capacity and type of substation; the district heating (DH) plant is not assumed to have a fixed return temperature and generation profile. The novelty is an emphasis on DH operation and introduction of statistics into a dynamic simulation model. With no abnormal buildings, higher accuracy of modeling is achieved. Most of the consumers are pretty similar in thermal response, even though specific energy demand and heated volume may differ. Heat demand of an old building is better simulated with discrete regression, while those with pump-equipped substations are modeled with linear regression.

Thermal comfort markedly impacts our health, well-being and work productivity. This article is a review of practices generally adopted to quantify human thermal comfort in buildings. The review indicates that there is significant variation in comfort requirements due to diversified socio-cultural set-up and local adaptive behaviour. Thus, the localised thermal comfort models need to be developed to identify the actual comfort requirements helpful in drafting new local comfort standards. The study justifying the relationship between thermal comfort and indoor air quality are scant and need to be explored as such relationships are greatly dependent on occupant’s adaptive behaviour. Further, the interdisciplinary research on thermal comfort which not only helps in real-time assessment but also covers other critical aspects like building architecture and energy consumption is lacking in the literature. Moreover, this review paves way for research on thermal comfort in countries where high building stock is expected in future.

Heating, Ventilation, and Air Conditioning (HVAC) systems are among the largest energy consumers in buildings, and their control strategies play a crucial role in achieving energy efficiency, indoor comfort, and sustainability. This review examines the main HVAC control strategies, ranging from traditional methods to Internet of Things (IoT) based and Artificial Intelligence (AI) driven approaches. In addition, occupancy-based control strategies and energy-efficient designs are critically examined for their potential to enhance system responsiveness and reduce operational costs. More than 100 recent research studies were systematically analyzed and compared across key parameters such as the objective of the study, the used control technique, strength, weakness, opportunity, threat, software/tool used, building type (residential, commercial, or industrial), control scale (single zone/multi-zone), and specific HVAC part controlled (e.g., AHU, VAV). To enable consistent comparison, a Multi-Objective Robustness Criterion (MORC) is used to assess how different control strategies balance energy consumption, thermal comfort, and Indoor Air Quality (IAQ) under changing conditions and how each control technique overcomes the limitations of the previous ones. In addition, the review also introduces a case analysis based on three U.S. cities, Charlotte, Greensboro, and Raleigh, to demonstrate the impact of outdoor climate variations and occupancy pattern on HVAC energy consumption. The results show that even a one-degree change in outdoor temperature can cause a considerable increase in annual energy consumption. Moreover, occupancy-based HVAC control can save more than $7,000 annually in the studied educational building. These findings highlight the strong impact of location-specific temperature differences on HVAC performance and emphasize the need for adaptive, climate-aware control strategies, while also pointing to future directions for smarter and more energy-efficient HVAC systems.