• Energy Research

Abstract Since occupant behaviour impacts the energy performance of buildings, its study is relevant in order to bridge the performance gap. While the factors influencing occupant behaviour have been established, most studies have focused on those factors that motivate the action, such as environmental and temporal conditions. Contextual factors including spatial and occupant characteristics, which act as action moderators, remain a subject to explore. In this way, this article aims to identify patterns in the occupants’ actions in office environments, based on spatial and human factors. A field study, including 514 occupants in 85 office spaces, was carried out in 11 buildings in Concepcion, Chile. The results indicate that spatial layout is significantly related to the operation of windows, blinds, and thermostats, but not personal devices. Gender did not influence whether an occupant was active or not and age range was only significant regarding blinds. In shared spaces, there were fewer active occupants and whose acts depend on the perception of opportunity that they have, which is associated with element control distance and occupant age. The findings suggest that the probability that actions occur varies based on spatial and human factors, particularly because these factors affect occupant perception of opportunity.

Abstract Since occupant behaviour impacts the energy performance of buildings, its study is relevant in order to bridge the performance gap. While the factors influencing occupant behaviour have been established, most studies have focused on those factors that motivate the action, such as environmental and temporal conditions. Contextual factors including spatial and occupant characteristics, which act as action moderators, remain a subject to explore. In this way, this article aims to identify patterns in the occupants’ actions in office environments, based on spatial and human factors. A field study, including 514 occupants in 85 office spaces, was carried out in 11 buildings in Concepcion, Chile. The results indicate that spatial layout is significantly related to the operation of windows, blinds, and thermostats, but not personal devices. Gender did not influence whether an occupant was active or not and age range was only significant regarding blinds. In shared spaces, there were fewer active occupants and whose acts depend on the perception of opportunity that they have, which is associated with element control distance and occupant age. The findings suggest that the probability that actions occur varies based on spatial and human factors, particularly because these factors affect occupant perception of opportunity.

Chile is a resilient country which has been struck by a series of natural disasters, affecting heritage areas whose inhabitants live under a great economic and energy vulnerability. Although there are some advances that have been made in the country to recover its heritage, these do not include energy efficiency parameters. In this context, intervention in heritage properties requires a specific, complementary treatment above and beyond what is currently applied. Consequently, this research aims to develop a methodology that balances heritage and energy in energy vulnerability contexts. The proposed methodology analyzes heritage and energy aspects separately through attribute matrices, as well as the building pathologies, to later integrate the results in a final matrix which allows defining an energy-heritage intervention plan. In this way, it includes the systematic identification of elements that require intervention because of pathological issues, as well as the type of intervention that would be acceptable given its heritage significance and whether they mean a possibility to optimize the energy performance. The methodology, for its validation, was applied in a heritage residential building inhabited by low-income occupants. The case study presents physical damages and is located in the city of Lota, an area with an outstanding cultural heritage from the mining era.

Chile is a resilient country which has been struck by a series of natural disasters, affecting heritage areas whose inhabitants live under a great economic and energy vulnerability. Although there are some advances that have been made in the country to recover its heritage, these do not include energy efficiency parameters. In this context, intervention in heritage properties requires a specific, complementary treatment above and beyond what is currently applied. Consequently, this research aims to develop a methodology that balances heritage and energy in energy vulnerability contexts. The proposed methodology analyzes heritage and energy aspects separately through attribute matrices, as well as the building pathologies, to later integrate the results in a final matrix which allows defining an energy-heritage intervention plan. In this way, it includes the systematic identification of elements that require intervention because of pathological issues, as well as the type of intervention that would be acceptable given its heritage significance and whether they mean a possibility to optimize the energy performance. The methodology, for its validation, was applied in a heritage residential building inhabited by low-income occupants. The case study presents physical damages and is located in the city of Lota, an area with an outstanding cultural heritage from the mining era.

Adaptive façades, also known as climate-adaptive building shells (CABSs), could make a significant contribution towards reducing the energy consumption of buildings and their environmental impacts. There is extensive research on glazed adaptive façades, mainly due to the available technology for glass materials. The technological development of opaque adaptive façades has focused on variable-thermal-resistance envelopes, and the simulation of this type of façade is a challenging task that has not been thoroughly studied. The aim of this study was to configure and validate a simplified office model that could be used for simulating an adaptive façade with variable thermal resistance via adaptive insulation thickness in its opaque part. Software-to-software model comparison based on the results of an EnergyPlus Building Energy Simulation Test 900 (BesTest 900)-validated model was used. Cooling and heating annual energy demand (kWh), peak cooling and heating (kW), and maximum, minimum, and average annual hourly zone temperature variables were compared for both the Adaptive and non-adaptive validated model. An Adaptive EnergyPlus model based on the BesTest 900 model, which uses the EnergyPlus SurfaceControl:MovableInsulation class list, was successfully validated and could be used for studying office buildings with a variable-thermal-resistance adaptive façade wall configuration, equivalent to a heavyweight mass wall construction with an External Insulation Finishing System (EIFS). An example of the Adaptive model in the Denver location is included in this paper. Annual savings of up to 26% in total energy demand (heating + cooling) was achieved and could reach up to 54% when electro-chromic (EC) glass commanded by a rule-based algorithm was added to the glazed part of the variable-thermal-resistance adaptive façade.

Adaptive façades, also known as climate-adaptive building shells (CABSs), could make a significant contribution towards reducing the energy consumption of buildings and their environmental impacts. There is extensive research on glazed adaptive façades, mainly due to the available technology for glass materials. The technological development of opaque adaptive façades has focused on variable-thermal-resistance envelopes, and the simulation of this type of façade is a challenging task that has not been thoroughly studied. The aim of this study was to configure and validate a simplified office model that could be used for simulating an adaptive façade with variable thermal resistance via adaptive insulation thickness in its opaque part. Software-to-software model comparison based on the results of an EnergyPlus Building Energy Simulation Test 900 (BesTest 900)-validated model was used. Cooling and heating annual energy demand (kWh), peak cooling and heating (kW), and maximum, minimum, and average annual hourly zone temperature variables were compared for both the Adaptive and non-adaptive validated model. An Adaptive EnergyPlus model based on the BesTest 900 model, which uses the EnergyPlus SurfaceControl:MovableInsulation class list, was successfully validated and could be used for studying office buildings with a variable-thermal-resistance adaptive façade wall configuration, equivalent to a heavyweight mass wall construction with an External Insulation Finishing System (EIFS). An example of the Adaptive model in the Denver location is included in this paper. Annual savings of up to 26% in total energy demand (heating + cooling) was achieved and could reach up to 54% when electro-chromic (EC) glass commanded by a rule-based algorithm was added to the glazed part of the variable-thermal-resistance adaptive façade.

Domestic hot water (DHW) consumption in dwellings can play a key role in the development of policies that are focused on energy poverty, and in improving energy efficiency, among other aspects. There is an important variability observed with DHW among different countries due to technical, sociological, climatic, and economic factors. Most studies that deal with DHW predictions are based on stochastic models, and only a few apply time series or statistical methods. In the case of Chile, the country is undergoing a policy development process, and there is little information about DHW consumption. As a result, it is fundamental to have DHW consumption prediction models that are focused on dwelling. For this reason, the study analysed the possibility of using time series models to make future estimations about monthly domestic hot water (DHW) consumption. To this end, consumption data obtained from 98 apartments between 2015 and 2021 were used, and 3 approaches were applied namely, exponential smoothing, basic structural model (BSM), and state-space model (SSM). The results showed that exponential smoothing and state-space methods allowed to obtain satisfactory results with regard to percentage error and confidence levels. Therefore, these models could be used to make future estimations of domestic hot water (DHW) consumption.