Assessment of thermal comfort and energy savings in a field study on adaptive comfort with application for mixed mode offices

Barbadilla-Martín, Elena; Martín, José Guadix; Lissén, José Manuel Salmerón; Ramos, José Sánchez; Domínguez, Servando Álvarez

doi:10.1016/j.enbuild.2018.02.033

Cited by 43 publications

(26 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…depending on their self-contained sensors. In literature, data loggers and temperature/humidity meters are commonly used to monitor indoor temperature and relative humidity [6,15,[43][44][45][46][47][48][35][36][37][38][39][40][41][42].…”

Section: Data Acquisition Technologies For Thermal Comfortmentioning

confidence: 99%

“…diameter black globe thermometer [15,31,33,[38][39][40][44][45][46][47]. It can be also measured by sensors [11,32,49], heat stress meter [30,43,48,50] and data loggers [36,37,41,42]. Moreover, external sensors can be used for measuring globe temperature [35].…”

Section: Data Acquisition Technologies For Thermal Comfortmentioning

confidence: 99%

“…Air speed is usually measured by 3 different types of instruments: (i) air speed probes that are connected to anemometers [6,11,[46][47][48][49][53][54][55]15,[30][31][32][33]38,44,45]; (ii) ventilation meters [35,37,50] and (iii) data loggers [36,40,42].…”

Section: Data Acquisition Technologies For Thermal Comfortmentioning

confidence: 99%

See 2 more Smart Citations

Data Acquisition Technologies for Assessing Thermal Comfort in the Built Environment

Kuru¹,

Çalış²

2021

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

Nowadays, many buildings are equipped with sensors that acquire large amounts of data, which can be useful to monitor, to understand and to identify thermal comfort conditions in buildings. The studies on thermal comfort of building interior spaces are not only numerical analysis based on program outcomes, but also experimental studies to confirm the results of the analysis. However, the most important factor in achieving the correct result in experimental analysis is to plan the data, to select the technology and to determine the test procedure. This study aims at providing an important source for experimental researchers working on thermal comfort by identifying data acquisition technologies that are utilized for capturing thermal comfort related data. Within this context, the study presents existing instruments utilized for monitoring thermal comfort conditions and provides a guideline with respect to technical properties, deployment strategies and time intervals. The findings of this study will be beneficial to practitioners and researchers for selecting and utilizing the most appropriate data acquisition technology for assessing thermal comfort in indoor environments.

show abstract

Section: Data Acquisition Technologies For Thermal Comfortmentioning

confidence: 99%

Section: Data Acquisition Technologies For Thermal Comfortmentioning

confidence: 99%

See 1 more Smart Citation

Data Acquisition Technologies for Assessing Thermal Comfort in the Built Environment

Kuru¹,

Çalış²

2021

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

show abstract

“…Experienced analysts may use a strategic model to frame the parameters of debate. For instance, they may treat the model as an opportunity to inform project stakeholders on recent research in adaptive comfort [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36], advocating for natural ventilation principles to be incorporated into the schematic design. In such a case, the analyst may try to show the cumulative influence of passive design measures on the floating or free-running temperature; that is, how the interior temperature evolves without active thermostatic control.…”

Section: Strategic Modelsmentioning

confidence: 99%

The Optimal Tuning, within Carbon Limits, of Thermal Mass in Naturally Ventilated Buildings

Craig¹

2019

Preprint

View full text Add to dashboard Cite

What proportions should a thermally massive building have? How should the thermal mass be distributed? Should the "massing" change with the choice of material? This paper shows how to optimize the physical proportions of a building so that it synchronizes ambient heat exchanges in a natural feedback cycle. An internal mass is thermally coupled with buoyancy ventilation; the cycle is driven by the daily swing of outdoor temperature. Tripling up functions in this way—so that structural materials can reliably cool and power the ventilation for buildings—could help decarbonize the construction industry and provide an effective strategy for adapting to life-threatening heatwaves. Based on harmonic analysis, the method allows designers to thermally tune the form and mass of a building to meet chosen targets for temperature and ventilation in free-running mode. Once the optimal balance of exchange rates is known, design teams can proportionally vary the building height and ventilation openings against the surface area and thickness of an internal thermal mass. The possible permutations are infinite but parametrically constrained, allowing teams to fairly compare the functional and environmental credentials of different construction materials while they produce and evaluate preliminary options for organizing the exterior form and interior spaces of a building. An example study suggests that thin-shell structures of minimum weight, and even timber buildings, may be optimally tuned to produce ample ventilation and temperature attenuation.

show abstract

“…The results showed energy savings of 11.4% in heating and 27.5% in cooling. The average heating and cooling adaptive setpoint temperatures were 21.5 • C and 24 • C, whereas the conventional temperatures were 22.3 • C and 23.5 • C, respectively [39]; (iv) unlike this study where neutral temperatures were used as setpoint temperatures, the energy consumption in mixed-model buildings were quantified in another study by using the adaptive comfort limits from the EN15251 standard [40] as setpoint temperatures in the current scenario and under the influence of climate change [41]. The results showed a decrease of the energy consumption between 59.5% and 36.7% by comparing the use of conventional setpoints (23 • C in heating and 25 • C in cooling) with the use of adaptive setpoints, respectively, between the current and 2080 scenarios.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Comfort Control Implemented Model (ACCIM) for Energy Consumption Predictions in Dwellings under Current and Future Climate Conditions: A Case Study Located in Spain

et al. 2019

View full text Add to dashboard Cite

Currently, the knowledge of energy consumption in buildings of new and existing dwellings is essential to control and propose energy conservation measures. Most of the predictions of energy consumption in buildings are based on fixed values related to the internal thermal ambient and pre-established operation hypotheses, which do not reflect the dynamic use of buildings and users’ requirements. Spain is a clear example of such a situation. This study suggests the use of an adaptive thermal comfort model as a predictive method of energy consumption in the internal thermal ambient, as well as several operation hypotheses, and both conditions are combined in a simulation model: the Adaptive Comfort Control Implemented Model (ACCIM). The behavior of ACCIM is studied in a representative case of the residential building stock, which is located in three climate zones with different characteristics (warm, cold, and mild climates). The analyses were conducted both in current and future scenarios with the aim of knowing the advantages and limitations in each climate zone. The results show that the average consumption of the current, 2050, and 2080 scenarios decreased between 23% and 46% in warm climates, between 19% and 25% in mild climates, and between 10% and 29% in cold climates by using such a predictive method. It is also shown that this method is more resilient to climate change than the current standard. This research can be a starting point to understand users’ climate adaptation to predict energy consumption.

show abstract

Assessment of thermal comfort and energy savings in a field study on adaptive comfort with application for mixed mode offices

Cited by 43 publications

References 29 publications

Data Acquisition Technologies for Assessing Thermal Comfort in the Built Environment

Data Acquisition Technologies for Assessing Thermal Comfort in the Built Environment

The Optimal Tuning, within Carbon Limits, of Thermal Mass in Naturally Ventilated Buildings

Adaptive Comfort Control Implemented Model (ACCIM) for Energy Consumption Predictions in Dwellings under Current and Future Climate Conditions: A Case Study Located in Spain

Contact Info

Product

Resources

About