Cooling Energy Use Research Articles

Assessing the effect of night ventilation on PCM performance in high-rise residential buildings

This article investigates the possibility to enhance the use of latent heat thermal energy storage (LHTES) as an energy retrofit measure by night ventilation strategies. For this scope, phase change materials (PCMs) are integrated into wall and ceiling surfaces of high-rise residential buildings with highly glazed facades that experience high indoor diurnal temperatures. In particular, this article investigates the effect of night ventilation on the performance of the PCMs, namely, the daily discharge of the thermal energy stored by PCMs. Following previous experimental tests that have shown the efficacy of LHTES in temperate climates, a system comprising two PCM layers with melting temperatures selected for a year-around LHTES was considered. To quantify the effectiveness of different night ventilation strategies to enhance the potential of this composite PCM system, simulations in EnergyPlusTM were performed. The ventilation flow rate, set point temperature, and operation period were the main tested parameters. The performance of the PCMs in relation to the variables was evaluated based on indoor operative temperature and cooling energy use variations in Toronto and New York in the summer. The solidification of the PCMs was analyzed based on the amount of night ventilation needed in each climate condition. The results quantify the positive impact of combining PCMs with night ventilation on cooling energy reductions and operative temperature regulation of the following days. In particular, the results indicate higher benefits obtainable with PCMs coupled with night ventilation in the context of Toronto, since this city experiences higher daily temperature fluctuations. The impact of night ventilation design variables on the solidification rate of the PCMs varied based on each parameter leading to different compromises based on the PCM and climate characteristics.

An archetype-in-neighbourhood framework for modelling cooling energy demand of a city's housing stock

As hot days are getting hotter and more frequent, urban dwelling is expected to increase cooling energy use in current and future climate. The applicability of dynamic building simulation in estimating cooling loads of a city's housing stock can be limited due to lack of fine-grained on-site current and future weather inputs. For predicative modelling of residential cooling energy demand to aid a city's energy supply planning resilient to excessive heat conditions, it requires cooling energy demand projection based on a relational account of (1) the thermal-environmental interaction between housing stocks and urban microclimate conditions, (2) the city dwellers' cooling energy use behaviour, and (3) the city's climate projections. In this paper, we introduce an ‘archetype-in-neighbourhood’ framework to meet these requirements. Combining empirical urban data modelling and EngeryPlus model calibration, this framework was developed to obtain statistically a maximal cooling energy demand model of a city's housing stock during yearly hottest periods. We applied the framework to multiple datasets selected from Seoul's open urban data sources for the period of 2014–2017 (2014 being the earliest year of data availability, 2017 being the end of the study period), including metered electricity use data of 659 apartment buildings (51,351 households) sampled from 18 city districts. The results show that maximal month cooling energy demand (MMCD, kWh/m2) of Seoul's housing stock can be expressed as a regression function of two determinants: (1) the city's average outdoor temperature during the hottest month period (Tex, °C), and (2) estimated indoor cooling temperature set-point (Tin, °C) of the city’ housing stock during the same period. Through a k-fold (k = 4) validation, the current regression model (2014–17) was evaluated to have an overall coefficient of determination R2=0.969. Assuming no housing stock renovation, we applied the model to generate scenarios of maximal month cooling demand in future years according to some of the highest summer temperatures projected for Seoul (RCP8.5 2045, RCP4.5 2047, MM5 2071–2100). We conclude this paper with a brief discussion of the implication for cooling energy supply planning and further work to extend the applicability of this new framework to housing stock adaptation planning and design.

Broadening human thermal comfort range based on short-term heat acclimation

Elevating indoor temperature set-points can reduce cooling energy use. Short-term heat acclimation (HA), the artificially induced adaptation developed in three consecutive days, is an effective method to increase the occupants' acceptance to hot environments. However, the quantitative study on the effects of short-term HA on thermal comfort is lacking. To this end, simulated experiments were conducted in a climate chamber to test the difference of subjects' thermal comfort before and after short-term HA. The subjects were instructed to do intermittent treadmill exercise under hot conditions to reach a HA state. During the trials, core temperature, ratings of perceived exertion (RPE), and ratings of thermal sensation (RTS) were measured. Perceptual strain index (PeSI) was used to assess the effect of short-term HA. The results showed that short-term HA could improve subjects’ adaptability to warmer environments without sacrificing thermal comfort. Furthermore, a HA zone was defined based on the predicted percentage of dissatisfied (PPD) of 10%. The upper limit of the HA zone was 2.1 °C higher than that of the summer thermal comfort zone in ASHRAE Standard 55–2017. This finding suggests that a higher temperature set-point could be considered into the control of air-conditioning systems, contributing to building energy conservation.

Impact of climate change on the existing residential building stock in Turkey: An analysis on energy use, greenhouse gas emissions and occupant comfort

With the growing need for residential buildings as a result of population growth, the building sector is a high-priority area in climate change due to its large share of CO2 emissions, the significant energy saving opportunities it represents, and the increasing expectations for occupant comfort. This paper presents the results of climate change impact assessment on a typical mid-rise residential building in four representative cities with different climatic characteristics in Turkey. Three different scenarios that characterize different solutions towards space cooling are developed, from naturally ventilated to fully air-conditioned. The energy requirements and corresponding CO2 emissions due to space conditioning as well as occupant thermal comfort are the investigated building performance metrics. The preliminary results based on energy simulations indicate that pronounced overheating will be experienced in the future, which will have a strong effect on cooling energy use and/or occupant comfort. The projected energy demand also points to the future need to explore measures for climate change adaptation of buildings and the importance of the decarbonization of the electricity industry for climate change mitigation. The analysis results presented in this paper provide a basis for future studies on building retrofit for climate change.

A Comparison of Cooling Energy Use of Residential Buildings According to Air Conditioner On/Off Behavior Using Co-Simulation

This study quantitatively analyzed the impact of resident AC (Air Conditioner) use behaviors on the cooling energy use of residential buildings. Behavior models extracted from different households were applied to a building of identical performance to compare cooling energy use according to behaviors. The behavior model used in this study is an AC on/off state prediction model using random forest algorithm; three models extracted from respective households were used. To apply the AC on/off state predicted through random forest, BCVTB was utilized for a co-simulation of a data analysis tool(R) and an energy analysis tool (EnergyPlus). The results showed that despite the identical physical and system performance of the building, the cooling energy use differed by as much as 2.5 times at set temperature 24°C. This study confirmed the possibility of integrating various prediction algorithms with energy analysis tools in future studies and quantitatively reaffirmed the need for behavior studies in the cooling energy use analysis for residential buildings.

Identifying suitable general circulation model for future building cooling energy analysis

These future building energy studies mainly stem from hourly based dynamic building simulation results with the future weather data. The reliability of the future building energy forecast heavily relies on the accuracy of these future weather data. The global circulation models (GCMs) provided by IPCC are the major sources for constructing future weather data. However, there are uncertainties existed among them even with the same climate change scenarios. There is a need to develop a method on how to select the suitable GCM for local application. This research firstly adopted principal component analysis (PCA) method in choosing the suitable GCM for application in Taiwan, and secondly the Taiwanese hourly future meteorological data sets were constructed based on the selected GCM by morphing method. Thirdly, the future cooling energy consumption of an actual office building in the near (2011-2040), the mid (2041-2070), and the far future (2071-2100), were analysed. The results show that NorESM1-M GCM has the lowest root mean square error (RMSE) as opposed to the other GCMs, and was identified as the suitable GCM for further future climate generation processing. The building simulation against the future weather datasets revealed that the average cooling energy use intensity (EUIc) in Taipei will be increased by 12%, 17%, and 34% in the 2020s, 2050s, and 2080s, respectively, as compared to the current climate.

Comparative Analysis of Energy Performance for Residential Wall Systems with Conventional and Innovative Insulation Materials: A Case Study

This study was focused on the simulation of energy performance for residential buildings incorporating different types of insulation materials. The energy consumption of residential buildings in the U.S. plays a significant role in the total annual energy consumption, and using insulation materials of higher performances is one of the most effective ways to reduce the building energy consumption. In this study, the building energy simulation was performed in BEopt for a typical residential house in the U.S. with several different types of insulation materials. The results show that adding insulation materials can significantly improve the building energy performance. The polyisocyanurate performed the best among the conventional insulation materials and had an annualized source energy saving of 37% in Pittsburgh. Vacuum-Insulated Panels had the best performance among all types of materials discussed in this study and showed annualized source energy of 41% in Pittsburgh. Phase Change Material was found to be the most effective way to particularly reduce the cooling energy use.

Statistical Analysis of Window Impacts on Cooling and Heating Energy Use in Single Family Residence Based on Climate Regions in U.S.A.

Purpose : Window area, location, and selection of glazing are a very important factor in reducing cooling and heating energy use of a building. The primary goal of this research is to investigate the effects of window design variables on annual cooling and heating energy use in a single residence based on climate regions in the United States using statistical analysis. Method : The methodologies used in this paper are building energy simulations, descriptive statistics, t-test, Latin Hypercube Sampling, and sensitivity analysis. Two groups of window variables are defined and simulated to explore the difference of the simulation results using Latin Hypercube Sampling and t-test. Then, the enter method as a regression model is used to investigate which group of data better predicted annual cooling and heating energy use. Lastly, Standard Regression Coefficients (SRCs) sensitivity indicator is used to determine if the influence of window parameters on cooling and heating energy use varies by different climate zone. Results : T-test results show that the differences in simulation results between the two groups are not statistically significant. That means that simulations using less number of variables (Group B) can have similar accuracy than simulation with higher number of window variables (Group A). As a result of the regression models, average adjusted R2 is 0.886 for Group A and 0.933 for Group B. Therefore, the regression model using Group B is selected to determine the effect of each variable on energy use. According to SRCs from regression, the most sensitive design parameters for cooling energy use are SHGC, west and south facing windows, while U-value, north and west facing windows are the most sensitive window parameters for heating energy use.

An energy and life-cycle cost comparison of residential PSC and ECM blower systems operating at excess pressures due to restrictive ducts

This study is to comprehensively evaluate energy impacts and life cycle costs of duct designs for residential central HVAC systems. Building energy simulations were performed under two different climates (Chicago, IL and Austin, TX) to predict the heating and cooling energy use in systems with blowers of different types of motors, namely electronically commutated motors (ECMs) and permanent split capacitor (PSC) motors, paired with ductworks of varying flow resistance and duct materials. In addition to the energy use, the life cycle cost of each duct design was determined over a 15-year lifetime. Depending on the specific duct design, the annual energy cost in the Chicago home decreased by 11–17% for systems with ECM blowers and 3–8% for systems with PSC blowers as the flow resistance decreased from 0.8 to 0.3 in. w.g. (200–75 Pa). In the Austin home for the same flow resistance decreases, the annual energy costs decreased by 16–18% for systems with ECM blowers and 7–8% for systems with PSC blowers. Although the cost-effectiveness of a specific duct design is shown to be heavily dependent on initial duct fabrication and installation costs, the use of lower flow resistance ductworks generally leads to lifetime savings in the presence of 10% supply and return leakage. Specifically, the lifetime saving is achieved in 6 out of 8 simulated cases for the Chicago home and all simulated cases for the Austin home.

Impact of perforated solar screens on daylight availability and low energy use in offices

ABSTRACT In this paper, daylighting and thermal analysis are carried out in synergy to ensure the best overall performance of perforated solar screens (PSS) used on fully glazed offices facing towards South, East, West and North, placed in Seville. The study has been conceived by applying multiple orthogonal arrays to account oriented transverse comparisons of several PSS design variables, with respect to their impact on the Daylight Availability (DAv) and the annual energy demand (lighting plus cooling and heating). Daylighting and irradiation calculations are carried out with DIVA-for-Grasshopper. The irradiation simulations are needed for simplifying the PSS complex geometries in order to perform thermal calculations with EnergyPlus. The results revealed that the use of PSS on façades is effective for enhancing DAv at the four orientations, in terms of the actual fully daylit area and the useful daylight illuminances. In comparison with fully and partly glazed façades, PSS increased the electrical lighting use but they considerably decreased the cooling energy use. Since lighting resulted lower and less influencing than cooling, PSS effectively reduced the total annual energy consumption. Therefore, optimizing daylighting through PSS can lead to low energy projects.

Representation and evolution of urban weather boundary conditions in downtown Chicago

This study presents a novel computing technique for data exchange and coupling between a high-resolution weather simulation model and a building energy model, with a goal of evaluating the impact of urban weather boundary conditions on energy performance of urban buildings. The Weather Research and Forecasting (WRF) model is initialized with the operational High-Resolution Rapid Refresh (HRRR) dataset to provide hourly weather conditions over the Chicago region. We utilize the building footprint, land use, and building stock datasets to generate building energy models using EnergyPlus. We mapped the building exterior surfaces to local air nodes to import simulated microclimate data and to export buildings' heat emissions to their local environment. Preliminary experiments for a test area in Chicago show that predicted building cooling energy use differs by about 4.7% for the selected date when compared with simulations using TMY weather data and without considering the urban microclimate boundary conditions.

The impact of local variations in a temperate maritime climate on building energy use

ABSTRACTWe investigate the impact of local climatic variations on the energy performance of buildings by conducting simulations using weather files generated from high-resolution measurements covering 33 stations within a 77 km2 area in southern Vancouver Island, British Columbia, Canada. Weather files were created by resampling the data and applying appropriate models to obtain unmeasured values. The difference in microclimate has been analysed statistically and graphically; average annual temperature varies by around 1°C, and at certain times there is a 6°C variation across the (very small) region.Building energy simulations of a small naturally ventilated office building and a larger air-conditioned building were performed using EnergyPlus for all weather files. Significant variation is found spatially and temporally which would have substantial implications for building design and energy use. The variation in annual heating energy use is ±5% of the mean, equivalent to 18 kWh/m2/a, with even greater relative variation in cooling energy use.

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Clustering and statistical analyses of air-conditioning intensity and use patterns in residential buildings

Energy conservation in residential buildings has gained increased attention due to its large portion of global energy use and potential of energy savings. Occupant behavior has been recognized as a key factor influencing the energy use and load diversity in buildings, therefore more realistic and accurate air-conditioning (AC) operating schedules are imperative for load estimation in equipment design and operation optimization. With the development of sensor technology, it became easier to access an increasing amount of heating/cooling data from thermal energy metering systems in residential buildings, which provides another possible way to understand building energy usage and occupant behaviors. However, except for cooling energy consumption benchmarking, there currently lacks effective and easy approaches to analyze AC usage and provide actionable insights for occupants. To fill this gap, this study proposes clustering analysis to identify AC use patterns of residential buildings, and develops new key performance indicators (KPIs) and data analytics to explore the AC operation characteristics using the long-term metered cooling energy use data, which is of great importance for inhabitants to understand their thermal energy use and save energy cost through adjustment of their AC use behavior. We demonstrate the proposed approaches in a residential district comprising 300 apartments, located in Zhengzhou, China. Main outcomes include: Representative AC use patterns are developed for three room types of residential buildings in the cold climate zone of China, which can be used as more realistic AC schedules to improve accuracy of energy simulation; Distributions of KPIs on household cooling energy usage are established, which can be used for household AC use intensity benchmarking and performance diagnoses.

Climate change and the building sector: Modelling and energy implications to an office building in southern Europe

The building sector is one of the most relevant sectors in terms of generation of wealth and occupation, but it is also one of the main contributor to energy use and greenhouse gas emissions (e.g. at the European level it is currently responsible for 36% of CO2 emissions). For these reason this sector must play a key role in achieving a low-carbon economy consistent with the objective of holding the increase of the average temperature of the globe below 2 °C if compared to pre-industrial levels.In this context, the paper analyses the potential impact of climate change on the energy uses for heating and cooling in southern Europe, based on the assumptions of the latest Intergovernmental Panel on Climate Change (IPCC) future climate projections (assessment report 5). Different General Circulation Models (GCMs) were analysed using different metrics for selecting the most suitable one to be applied to building simulation. GCM data were used as input to a downscaling method known as “morphing”, to generate hourly weather files for 3 future time projections (2035, 2065 and 2090). Finally, in order to assess the building energy use for heating and cooling for the next century, energy simulations for a case study were performed.The results show, in all scenarios, consistent and large increases in future air temperature. The impacts of these driving forces on heating and cooling energy use are very relevant: the results show an overall increase in total energy consumption with a relative decrease in heating demand and increase in cooling demand: the yearly heating and cooling energy requirement in 2090 is expected to increase in a range of +50.8–119.7% if measures are not foreseen to counter and limit the effects of climate change.

Impacts of urbanization and air pollution on building energy demands — Beijing case study

This article addresses the nexus of intense urbanization, building energy and air pollution, a topic minimally explored in the literature. The urban heat island effect on building energy demands for cooling and heating is investigated for Beijing through observations and modeling with a coupled Building Effect Parameterization-Building Energy Model and a single building energy model. The average urban heat island intensity in Beijing during summer is approximately 2.02 K, and in winter, this value reaches 3.41 K. The models used for the investigation are forced with observations from two meteorological towers, one located in downtown and the other in the outskirt. Model validation is conducted for environmental variables and for building energy demands against surface weather observations and actual electricity data, showing good agreement in all cases. Results for a 6-storey office building indicate that cooling energy use in the urban area is 36.53 W m−2 (30%) higher than the suburban area during summer, while heating energy use is 95.29 W m−2 (23%) lower than the suburbs during winter. Residential building shows similar results, with smaller differences in cooling and heating energy use, about 9.14 W m−2 (17%) and 92.71 W m−2 (20%), respectively. Analysis of clear and polluted winter days shows the impact-chain of airpollution–urban heat island–heating energyuse. Heating energy demand is reduced in the urban area during polluted days, corresponding to an enhanced heat island, which may be attributed to a stronger inversion and a lower wind speed.

Parametric analysis of a residential building with phase change material (PCM)-enhanced drywall, precooling, and variable electric rates in a hot and dry climate

Peak electric energy demand inflicts a great stress on the electric grid during the summer in the United States. With most years surpassing its previous year for the warmest year ever recorded, cooling requirements will continue to increase in the coming decades. Energy storage can potentially reduce electric demand. Among different technologies, phase change materials (PCMs) embedded in the building envelope have the potential to shift cooling energy demand away from peak hours. This study performs parametric analysis of PCMs in a relatively new home located in Phoenix, Arizona, USA. The analysis includes PCM location, PCM properties, precooling strategy, and an analysis of natural and forced convection models on the thermal behavior of the house. An extension of a standard forced convection model in EnergyPlus is used to represent the effects of a ceiling fan, which increases heat transfer at wall and ceiling surfaces and shortens the time needed to freeze or melt the phase change materials. Furthermore, the study discusses the use of appropriate setback temperatures to best utilize the PCMs. Overall, the optimal combination of PCMs, convection mode, and precooling schedule can completely shift cooling energy use during a three-hour demand period, producing maximum cost savings up to 29.4%, while increasing the occupant comfort.

The rising energy efficiency of office buildings in Hong Kong

Though area in office buildings has expanded significantly in Hong Kong in the decade to 2013, increase in cooling energy use has been rather moderate. The factors and policy instruments that contributed to the impressive enhancement in energy usage efficiency are not available in published literature. Data of sixty-six office developments were examined to evaluate the role of policy instruments in bringing about the visible improvement. Numerical analyses reveal that use of chiller units with higher efficiency and fresh water cooling tower (FWCT) systems have contributed significantly to reduce cooling energy use of office space in Hong Kong. It is important to note that policies promulgated have played a key role in encouraging designers of office space to opt for energy efficient systems. The BEAM Plus certification for all public buildings has contributed the most (efficacy = 0.09) to the success in moderation of electricity consumption for cooling of office space. The FWCT scheme and the Building Energy Codes have had efficacies amounting to 0.076 and 0.026, respectively. Interestingly, the new OTTV requirement, used for regulation and monitoring of thermal performance of building envelopes, has had a negative rate of efficacy (0.018), implying that the government needs to review its appropriateness.

Correlating daylight availability metric with lighting, heating and cooling energy consumptions

This paper examines the relationship between the Daylight Availability (DAv) metric and annual energy consumption. DAv was established as a means of describing indoor daylight sufficiency both for research and practical purposes. To balance daylighting with energy concerns, the specific amount of daylight sufficiency within a space should neither be too low; nor should it be excessive. However, there is little if any notion of what the relationship between a DAv area and the energy used on-site to supply the artificial lighting, heating and cooling systems might be. The aim of this research is to determine if one or more of the DAv areas predicted on the workplane could serve as a proxy for the overall building energy consumption (lighting plus heating and cooling). The office setting is designed to offer a wide range of daylight exposures, depending on the orientation of the fully-glazed façade and that of the perforated solar screen configuration. Results indicated a strong linear relationship between the overlit area and the cooling energy use. Moreover, confining the overlit area to less than 40% at South and less than 50% at North, East and West could help limit the overall energy consumption to less than 120 kWh/m2-year.