Buildings In Severe Cold Regions Research Articles

Study on the Influence of the Application of Phase Change Material on Residential Energy Consumption in Cold Regions of China

As the impact of climate change intensifies, meeting the energy demand of buildings in China’s cold regions is becoming increasingly challenging, particularly in terms of cooling energy consumption. The effectiveness of integrating phase change material (PCM) into building envelopes for energy saving in China’s cold regions is unclear. The aim of this study is to assess the effectiveness of PCM integration in building enclosures for energy efficiency in these regions. The research monitored and recorded indoor temperature data from typical residential cases from May to September. This measured data was then used to validate the accuracy of EnergyPlus22-1 software simulation models. Subsequently, the calibrated model was utilized to conduct a comparative analysis on the effects of PCM on indoor temperatures and cooling energy consumption across these regions. The results of these comparative analyses indicated that PCM can alleviate indoor overheating to varying degrees in severe cold regions of China. Focusing on north-facing bedrooms, applying PCMs reduced the duration of overheating in non-air-conditioned buildings in severe cold regions of China by 136 h (Yichun), 340 h (Harbin), 356 h (Shenyang), and 153 h (Dalian). In terms of cooling energy consumption, the energy saved by applying PCMs ranged from 1.48 to 13.83 kWh/m2. These results emphasize that the performance of PCM varies with climate change, with the most significant energy-saving effects observed in severe cold regions. In north-facing bedrooms in Harbin, the energy-saving rate was as high as 60.30%. Based on these results, the study offers guidance and recommendations for feasible passive energy-saving strategies for buildings in severe cold and cold regions of China in the face of climate change. Additionally, it provides practical guidance for applying PCMs in different climatic zones in China.

Data-driven modelling of building retrofitting with incomplete physics: A generative design and machine learning approach

Building performance simulation (BPS) based on physical models is a popular method for estimating the expected energy savings from energy-efficient building retrofitting. However, for many buildings, especially older buildings, built several decades ago, an operator do not have full access to the complete information for the BPS method. Incomplete information comes from the lack of detailed building physics, such as the thermal transmittance of some building components due to the deterioration of components over time. To address this challenge, this paper proposed a data-driven approach to support the decision-making of building retrofitting selections under incomplete information conditions. The data-driven approach integrates the backpropagation neural networks (BRBNN), fuzzy C-means clustering (FCM), and generative design (GD). It generates the required big database of building performance through generative design, which can overcome the problem of incomplete information during building performance simulation and energy-efficient retrofitting. The case study is based on old residential buildings in severe cold regions of China, using the proposed approach to predict energy-efficient retrofitting performance. The results indicated that the proposed approach can model the performance of residential buildings with more than 90% confidence, and show the variation of results. The core contribution of the proposed approach is to provide a way of performance prediction of individual buildings resulting from different retrofitting measures under the incomplete physics condition.

Assessing the Potential of Integrated Shading Devices to Mitigate Overheating Risk in University Buildings in Severe Cold Regions of China: A Case Study in Harbin

Creating a comfortable indoor environment in education buildings is an important design objective. Climate change has resulted in rising summer indoor temperatures in the severe cold regions of China, and evidence of summer overheating risk in these regions has not yet been fully investigated. This study presents evidence of overheating in a university building in a severe cold region of China, discusses the potential of integrated shading devices for mitigating overheating, and proposes design ideas for the application of shading devices. Temperature monitoring and simulation were performed in a university building with natural ventilation located in Harbin, and various configurations of integrated shading devices were simulated using IES Virtual Environment software. The results demonstrate that 69% of classrooms were overheated; furthermore, south-facing classrooms could be overheated for up to 152 h during summer occupancy hours. This study finds that integrated shading devices reduce overheating hours by up to 59.2%. The design of appropriate parameters for shading devices can effectively improve indoor thermal comfort while maintaining daylight levels and controlling the increase in energy consumption. The methodology and results presented in this study offer a reference point and practical guidance for mitigating regional overheating, aiming to promote the improvement of regional standards and optimisation of thermal environments in the severe cold regions of China.

Numerical Simulation Analyses on Envelope Structures of Economic Passive Buildings in Severe Cold Region

The present study provides comprehensive analyses of a newly constructed passive energy-efficient building located in Harbin, China, which is a prime example of how to design a passive building that withstands the severe cold climate in northeast Asia. Conduction transfer functions of heat flux equilibrium are employed to simulate energy consumption characteristics of the paradigm passive building. The climatic conditions in severe cold region are analyzed, and the energy-saving designs in the studied engineering cases are summarized for their practical applications. Building physical models are established to perform numerical simulation analyses on the passive building paradigm in northeast Asian frigid zone. The dominant technical parameters of envelope structure affecting energy consumption in severe cold region, including thermal insulation thickness and heat transfer coefficient of building envelope, as well as window-to-wall ratio for each building facade, are taken into consideration as simulation variables to calculate cooling load, heating load, electricity consumption, and CO2 emission, which account for energy efficiency of passive buildings. The simulation results demonstrate the high energy-saving potential of the proposed passive building design and render the optimal energy-efficient parameters suitable for severe cold regions, which can reduce energy consumption and CO2 emission while ensuring comfort for occupants. The present study provides a theoretical reference for envelope structures of passive buildings in severe cold regions, which is of great significance to the development of green buildings and relevant policies.

Change rates and weight values of energy consumption parameters for light steel buildings in severe cold region

ABSTRACT Light steel buildings are widely used in rescue and disaster relief, but they consume a lot of energy to improve the indoor thermal environment due to their high thermal conductivity and poor thermal comfort. To clarify the relationship between various design parameters and their effect on energy consumption, the energy consumption impact of the design parameters including building orientation, aspect ratio, roof slope angle, window-wall ratio (WWR), and envelope structure of a typical light steel building in cold regions is comprehensively analyzed. The impact degree of parameters is determined by the simulation and analytic hierarchy process (AHP) analysis to calculate the weight value of the design parameters affecting the energy consumption. The results show that the consumption of energy increases with the increase of the aspect ratio, slope angle, WWR and heat transfer coefficient of envelope. The orientation of the minimum energy consumption is 180°, the weight less than 180° is positive, and that greater than 180° is negative. The envelope has the greatest impact on the energy consumption, with a weight of about 0.66, of which the wall and roof is about 0.40 and 0.26 respectively; Then the south WWR, slope angle, north WWR, aspect ratio and orientation are in turn, and the weights are about 0.12, 0.08, 0.07, 0.06 and ±0.02 respectively. The research results can optimize the building scheme and estimate the building energy consumption after optimization, which provides a reference for the energy-saving renovation of light steel buildings in severe cold regions.

Research on Carbon Reduction of Residential Buildings in Severe Cold Regions Based on Renovation of Envelopes

The demand for heating in cold regions drives up carbon emissions every year. In order to achieve China’s carbon neutrality target by 2060, CO2 emissions in the cold regions must be reduced. In this paper, using Design Builder software, a simulation model of residential buildings in severe cold regions was created, and the most appropriate parameter design scheme for carbon emission reduction of residential buildings in severe cold regions was derived by simulating the experimental data of the original parameter design scheme and the changed parameter design scheme, as well as the calculation of carbon dioxide emission reduction rate. In order to make the comparison of the results easier, no change was made in the selection of the changed scheme for the external insulation material, foamed polystyrene panels. The results show that the most suitable parameter scheme for houses in severe cold regions is 85 mm thick foamed polystyrene panels for exterior walls, 200 mm thick foamed polystyrene panels for roofs, and exterior windows should use semi-tempered plastic steel frame and triple glass 6 mm glass + vacuum + 6 mm low-e glass + 12 mm air + 6 mm glass composed of windows. This technique saves 30.32% of energy as compared to the original parameter design approach. The efficiency of energy conservation is 33.03%. The emission reduction effect is significant. The best parametric design plan has a static payback period of 5 years. The best parametric design plan has a discounted payback period of 7 and a net present value of USD 65,413.39. This scheme can provide a great economic return while also increasing the performance of the building.

Effect of sunspace and PCM louver combination on the energy saving of rural residences: Case study in a severe cold region of China

The influence of a sunspace and a sunspace including PCM louvers on the heating energy consumption was investigated considering a typical rural residence in a severe cold region of China. The analyses were carried out for four different indoor design temperatures, (14, 16, 18 and 20 °C) throughout seven months, from October to next year April. The results show that compared with the original rural residence, the monthly and total energy savings can be respectively attained up to 439 kWh (20.40%) and 1992 kWh (22.73%) when the building is attached with a sunspace at the indoor design temperature of 18 °C. Additionally, the sunspace with PCM louver integration can achieve an extra energy saving of 5.27% throughout the heating period for the same indoor design temperature, compared with the sunspace without PCM louvers. However, when latent heat of PCM is not fully utilized at low indoor design temperatures, PCM louvers may increase the heating energy consumption compared to the sunspace without PCM louvers. It is concluded from the outcomes of the study that the sunspace utilization, especially when integrated with PCM louvers with a reasonable melting point, can significantly contribute to the heating energy saving in buildings in severe cold regions.

Impact of Urban Morphology and Climate on Heating Energy Consumption of Buildings in Severe Cold Regions.

This study aims to acquire a better understanding of the quantitative relationship between environmental impact factors and heating energy consumption of buildings in severe cold regions. We analyze the effects of five urban morphological parameters (building density, aspect ratio, building height, floor area ratio, and shape factor) and three climatic parameters (temperature, wind speed, and relative humidity) on the heating energy use intensity (EUI) of commercial and residential buildings in a severe cold region. We develop regression models using empirical data to quantitatively evaluate the impact of each parameter. A stepwise approach is used to ensure that all the independent variables are significant and to eliminate the effects of multicollinearity. Finally, a spatial cluster analysis is performed to identify the distribution characteristics of heating EUI. The results indicate that the building height, shape factor, temperature, and wind speed have a significant impact on heating EUI, and their effects vary with the type of building. The cluster analysis indicated that the areas in the north, east, and along the river exhibited high heating EUI. The findings obtained herein can be used to evaluate building energy efficiency for urban planners and heating companies and departments based on the surrounding environmental conditions.

Application of Green Building Technology in Cold Region Cities

After half a century of development, green buildings have gradually formed a relatively sophisticated system. Based on the development status of green buildings and the climatic characteristics of cold region cities, the paper analyses the key technologies applicable to cold region cities in combination with actual projects, and provides a theoretical and applied basis for promoting the sustainable development of green buildings in severe cold regions.

Artificial Neural Network for Assessment of Energy Consumption and Cost for Cross Laminated Timber Office Building in Severe Cold Regions

This paper aims to develop an artificial neural network (ANN) to predict the energy consumption and cost of cross laminated timber (CLT) office buildings in severe cold regions during the early stage of architectural design. Eleven variables were selected as input variables including building form and construction variables, and the values of input variables were determined by local building standards and surveys. ANNs were trained by the simulation data and Latin hypercube sampling (LHS) method was used to select training datasets for the ANN training. The best ANN was obtained by analyzing the output variables and the number of hidden layer neurons. The results showed that the ANN with multiple outputs presented better prediction performance than the ANN with single output. Moreover, the number of hidden layer neurons in ANN should be greater than five and preferably 10, and the best mean square error (MSE) value was 1.957 × 103. In addition, it was found that the time of predicting building energy consumption and cost by ANN was 80% shorter than that of traditional building energy consumption simulation and cost calculation method.

Simulation-Based Multiobjective Optimization of Timber-Glass Residential Buildings in Severe Cold Regions

In the current context of increasing energy demand, timber-glass buildings will become a necessary trend in sustainable architecture in the future. Especially in severe cold zones of China, energy consumption and the visual comfort of residential buildings have attracted wide attention, and there are always trade-offs between multiple objectives. This paper aims to propose a simulation-based multiobjective optimization method to improve the daylighting, energy efficiency, and economic performance of timber-glass buildings in severe cold regions. Timber-glass building form variables have been selected as the decision variables, including building width, roof height, south and north window-to-wall ratio (WWR), window height, and orientation. A simulation-based multiobjective optimization model has been developed to optimize these performance objectives simultaneously. The results show that Daylighting Autonomy (DA) presents negative correlations with Energy Use Intensity (EUI) and total cost. Additionally, with an increase in DA, Useful Daylighting Illuminance (UDI) demonstrates a tendency of primary increase and then decrease. Using this optimization model, four building performances have been improved from the initial generation to the final generation, which proves that simulation-based multiobjective optimization is a promising approach to improve the daylighting, energy efficiency, and economic performances of timber-glass buildings in severe cold regions.

Study on Office Building Window Design Strategy in Severe Cold Region Based on Daylight Comfort

Effective and reasonable daylight can create a comfortable and healthy lighting environment, and significantly affect the quality of indoor light environment in office buildings. Reasonable architectural form design can improve indoor light environment quality and visual comfort degree, and has great significance. Combining with light climate characteristics in severe cold region, the study based on parametric model, aims to analyze the influence degree of the window-wall ratio, glass transmittance and window shape on lighting comfort of westward office buildings. Taking a westward office building in Harbin as an example, Rhino & Grasshopper is used to establish the parametric simulation model. Using different conditions of Window-Wall Ratio (WWR), Window Height (WH) and Height-Width Ratio (H/W) as variables to calculate the value of Daylight Factors (DF) and Daylight Discomfort Probability (DGP) through the control variable method. Adopting the regression analysis, the correlation between above three exterior window variables and the lighting comfort degree is studied, and the optimal design strategies for lighting environment of western office buildings in severe cold region are summarized. The results show that when the WWR is 0.2-0.3, the daylight comfortable performance is the best, the WH is about 0.9 and W/H is between 0.4-0.8, the office building has better daylight comfortable quality.

Study of Exterior Window’s Energy-Saving Design for the Residential Buildings in Severe Cold Region

Measure the temperature of exterior window and surrounding walls’ inner surface, and measure interior air temperature to analyze the effect, which was brought to building energy consumption and interior thermal conditions by the exterior window of the building; studied several details of exterior window design, and proposes a method, which is separately controlling the heat-transfer coefficient according to different orientation, room’s positions and room’s functions while designing the exterior windows, in order to improve the interior thermal conditions and reduce energy consumption of the residential buildings.

Research on Solar Energy Technology Application for Residential Buildings in Severe Cold Regions

Under the present major circumstances of global energy crisis and earth environmental degradation, as a country with rapid economic development, China has an increasing demand for energy. One way to solve this problem in China is to promote the development of clean renewable energy. This research takes this view as a starting point and discusses the solar energy application methods and the possibility focusing on the solar energy application status and problems for residential buildings in severe cold regions. At first, we carry out the theoretical discussion on the solar energy residence, and discuss the solar energy comprehensive utilization for multi-floor buildings and the methods and possibilities of building integration design, so as to play an instructive role in the solar energy comprehensive utilization research and practical application in our severe cold regions.