• Energy Research

Reducing energy consumption in the construction sector is urgently needed. In Chile, where income distribution is unequal and the cost of energy is high, energy demand is seriously affected, especially in vulnerable households. Hence, it is essential to establish public policies with more realistic energy-saving goals to address this situation. However, reliably predicting the energy performance of buildings remains a challenge. For this reason, this study aims to identify and evaluate the impact of the variables associated with energy performance in vulnerable households in Central-Southern Chile and propose values that would reduce the gap. A sensitivity analysis was conducted to achieve this, adjusting the energy performance parameters in a base model with data analyzed using local standards. In addition, field information was collected in 93 households to obtain the actual energy consumption. The main results show that the variables that most impacted performance were infiltration, COP, heating setpoints, and schedules, which generated a 60% difference between the theoretical and actual consumption.

Reducing energy consumption in the construction sector is urgently needed. In Chile, where income distribution is unequal and the cost of energy is high, energy demand is seriously affected, especially in vulnerable households. Hence, it is essential to establish public policies with more realistic energy-saving goals to address this situation. However, reliably predicting the energy performance of buildings remains a challenge. For this reason, this study aims to identify and evaluate the impact of the variables associated with energy performance in vulnerable households in Central-Southern Chile and propose values that would reduce the gap. A sensitivity analysis was conducted to achieve this, adjusting the energy performance parameters in a base model with data analyzed using local standards. In addition, field information was collected in 93 households to obtain the actual energy consumption. The main results show that the variables that most impacted performance were infiltration, COP, heating setpoints, and schedules, which generated a 60% difference between the theoretical and actual consumption.

Data simulated for occupancy profiles, usually based on standard occupancy schedules, must be validated against real measurements, and many studies have pointed out the gap between them. This problem is more pronounced in homes that are not heated by grid-connected energy sources, such as wood-burning stoves, because the meter cannot provide a real-time estimate. In Central-South Chile, 74% of homes are heated by wood stoves, causing an acute problem of air pollution in several urban areas. The government is trying to solve this problem, but at the moment there is no data on occupancy profiles, hence it is not possible to estimate the energy intensity for heating. This exploratory study aims to clarify to what extent occupancy profiles can be estimated from PM 2.5 pollution levels. To this end, publicly available data on PM 2.5 concentrations in 17 cities in central-south Chile was used as a proxy to build occupancy schedules for homes heated by wood stoves. The results show that there is a clear relationship between pollution levels and occupancy intensity, and that the latter does not follow the schedules outlined in international standards or building codes. The results and methodology can be replicated in cities where air pollution is driven by wood stoves, allowing public authorities to have access to accurate occupancy schedules and providing them with reliable data to address local air pollution problems The research group “Confort ambiental y pobreza energ´etica (+CO-PE)” of the University of the Bío-Bío, the Thematic Network 722RT0135 “Red Iberoamericana de Pobreza Energ´etica y Bienestar Ambiental” (RIPEBA) financed by the call for Thematic Networks of the CYTED Program for 2021, and the Thematic Network 723RT0151 Red Iberoamericana de Eficiencia y Salubridad en Edificios” (IBERESE) financed by the call for Thematic Networks of the CYTED Program for 2022 for supporting this research Project “ANID Fondecyt Regular 1200551-Energy poverty prediction based on social housing architectural design in the central and centralsouthern zones of Chile Index to analyze and reduce the risk of energy poverty”, funded by the National Agency for Research and Development (ANID, in Spanish) Universidad de Granada / CBUA

Data simulated for occupancy profiles, usually based on standard occupancy schedules, must be validated against real measurements, and many studies have pointed out the gap between them. This problem is more pronounced in homes that are not heated by grid-connected energy sources, such as wood-burning stoves, because the meter cannot provide a real-time estimate. In Central-South Chile, 74% of homes are heated by wood stoves, causing an acute problem of air pollution in several urban areas. The government is trying to solve this problem, but at the moment there is no data on occupancy profiles, hence it is not possible to estimate the energy intensity for heating. This exploratory study aims to clarify to what extent occupancy profiles can be estimated from PM 2.5 pollution levels. To this end, publicly available data on PM 2.5 concentrations in 17 cities in central-south Chile was used as a proxy to build occupancy schedules for homes heated by wood stoves. The results show that there is a clear relationship between pollution levels and occupancy intensity, and that the latter does not follow the schedules outlined in international standards or building codes. The results and methodology can be replicated in cities where air pollution is driven by wood stoves, allowing public authorities to have access to accurate occupancy schedules and providing them with reliable data to address local air pollution problems The research group “Confort ambiental y pobreza energ´etica (+CO-PE)” of the University of the Bío-Bío, the Thematic Network 722RT0135 “Red Iberoamericana de Pobreza Energ´etica y Bienestar Ambiental” (RIPEBA) financed by the call for Thematic Networks of the CYTED Program for 2021, and the Thematic Network 723RT0151 Red Iberoamericana de Eficiencia y Salubridad en Edificios” (IBERESE) financed by the call for Thematic Networks of the CYTED Program for 2022 for supporting this research Project “ANID Fondecyt Regular 1200551-Energy poverty prediction based on social housing architectural design in the central and centralsouthern zones of Chile Index to analyze and reduce the risk of energy poverty”, funded by the National Agency for Research and Development (ANID, in Spanish) Universidad de Granada / CBUA

Adaptive comfort models have emerged as a sustainable way of providing comfort in connection with local climate. Additionally, climate change has posed an additional challenge. In previous studies, the authors clarified how climate change would affect the feasibility of the adaptive comfort model at a worldwide scale, but local considerations for some countries remained unsolved. This study presents the first comprehensive research on the applicability of the adaptive comfort model in Japan not only for current, but also for future scenarios considering the climate change. Remarkable differences across Japanese regions were found, especially between the Northern underpopulated regions of Hokkaidō and Tōhoku and the cities that belong to the Taiheiyō Belt. In general, the adaptive comfort model will find application both in current and future scenarios, but natural ventilation will not play an important role. Special attention should be drawn to the potentials saving of cooling degrees that can be achieved if adaptive setpoint temperatures become commonplace in the future in the Kantō region. These results pave the way for the consideration of the adaptive comfort model as a resilient strategy to adapt to the future changes in climate scenarios for the building industry. © 2020 Elsevier Ltd

Adaptive comfort models have emerged as a sustainable way of providing comfort in connection with local climate. Additionally, climate change has posed an additional challenge. In previous studies, the authors clarified how climate change would affect the feasibility of the adaptive comfort model at a worldwide scale, but local considerations for some countries remained unsolved. This study presents the first comprehensive research on the applicability of the adaptive comfort model in Japan not only for current, but also for future scenarios considering the climate change. Remarkable differences across Japanese regions were found, especially between the Northern underpopulated regions of Hokkaidō and Tōhoku and the cities that belong to the Taiheiyō Belt. In general, the adaptive comfort model will find application both in current and future scenarios, but natural ventilation will not play an important role. Special attention should be drawn to the potentials saving of cooling degrees that can be achieved if adaptive setpoint temperatures become commonplace in the future in the Kantō region. These results pave the way for the consideration of the adaptive comfort model as a resilient strategy to adapt to the future changes in climate scenarios for the building industry. © 2020 Elsevier Ltd

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.

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.