Thermal Environment Optimization and Energy Saving of Residential Buildings under the Demand of Low-Carbon Operation

Influenced by the industrial revolution, the CO₂ content in the atmosphere increased sharply from the original stable value of 190 ~ 290ppm. Because carbon emissions account for 37%-39% of the global total emissions, the construction industry has become one of the national key emission reduction fields. As an important part of the construction industry, it is of great significance for residential buildings to carry out production and operation activities with the goal of controlling carbon emissions to achieve short-term emission reduction targets [1-4]. Improving the thermal environment quality of buildings under the demand of low-carbon operation is beneficial to residents' physical and mental health, and also puts forward higher requirements for the design of thermal environment optimization of residential buildings.

The core reason for such problems as high overall energy consumption and poor thermal environment in traditional residential buildings is the lack of heat preservation and insulation measures in its enclosure structure [5, 6]. Morovat and Athienitis [7] investigates the main characteristics and construction forms of traditional residential buildings, and numerically simulates the energy consumption of various typical residential buildings based on DesignBuilder software, thus completing the optimization and renovation of interior design based on the comfort of human thermal environment. Residential buildings before and after the heating period have the problems of indoor cold, and poor thermal comfort with high humidity. At the same time, the simultaneous use of artificial heating equipment and humidification equipment also causes energy waste [8-11]. Wang et al. [12] carries out subsequent characteristic analysis and thermal environment test on the city where a residential building is located and puts forward suggestions for improving the relevant enclosure structure and applying the building energy-saving mode according to the analysis of the characteristics and influencing factors of indoor thermal comfort of the buildings. Hospitals, as public buildings, need to provide healthy, hygienic and efficient indoor thermal environment for patients and it’s necessary to carry out further study on whether it's energy-saving for the ways and means used to maintain the stability of thermal environment by HVAC [13-15]. Reddy et al. [16] combines the discussion of patient rehabilitation, thermal comfort and hygiene standards, gives thermal environment standards and the range of temperature and humidity indexes of the ward buildings, and optimizes the plane selection and detailed layout design in combination with the actual evaluation results so as to realize the rationalization and energy saving of the thermal environment of the ward buildings. The deterioration of thermal environment in urban residential buildings seriously threatens the health of residents in buildings [17-19]. Zhang et al. [20] uses Mann-Kendall trend method to analyze the temporal and spatial evolution characteristics of thermal environment of urban residential buildings in China, analyzes the driving mechanism of indoor thermal comfort evolution of residential buildings, and reveals the comprehensive adjustment mechanism by the use of green building materials on indoor thermal environment and human comfort. In the construction industry, the tall space buildings with the characteristics of huge volume, high population density and complex thermal environment is the highest carbon emission intensity. The research on architectural design from the perspective of low carbon is of great significance to the control of global greenhouse effect [21-25]. Oshio et al. [26] relates to the low carbonization of large space buildings in areas hot in summer and cold in winter, puts forward matters needing attention in the rational utilization of natural lighting and natural ventilation and the rational selection of building materials, and studies the selection of natural ventilation channels and enclosure materials from the above two perspectives. Hu et al. [27] optimizes the comprehensive evaluation indexes of low-carbon buildings, realizes the analysis and calculation of carbon emission index, analyzes the influencing factors hindering the development of low-carbon buildings, and gives the evaluation method of low-carbon building structure.

To sum up, under the background of advocating energy saving and emission reduction, low carbonization of residential buildings is imminent. Most of the existing researches focus on the dynamic simulation of building energy consumption or carbon emissions quantification methods of different buildings. They have not carried out a long-term dynamic simulation of the indoor thermal environment of residential buildings, nor have they linked the low-carbon demand with the thermal environment optimization methods of residential buildings. Therefore, this study relates to the optimization strategies and energy-saving technologies on thermal environment of residential buildings under the demand of low-carbon operation. The paper mainly involves the following aspects: The indoor thermal environment of residential buildings is dynamically simulated in the second part of the paper, and the analysis is made around three aspects including the external disturbance conditions of the thermal process, the internal disturbance conditions of the thermal process and the ventilation of the thermal process; the heat transfer model for the facade of residential buildings is constructed and the calculation of indoor air temperature is completed in the third part of this paper; the indoor heat distribution mechanism of residential buildings under the heating mode of concentrated heat source is studied, the generation process of heat jet above the heat source is analyzed, and the influence of concentrated heat source on temperature distribution is explored in the fourth part; the calculation of carbon emissions from common energy sources in residential buildings is conducted the fifth part; the experimental results in the sixth part verify the effectiveness of the proposed method and the corresponding suggestions on thermal environment optimization and energy saving of residential buildings are provided.

When the wall thickness of building facade is smaller compared to the height and width of the building, the heat transfer process can be treated as one-dimensional transient heat conduction process, and the solution error can be controlled within 0.01. Assuming that the thermal diffusion coefficient and thermal conductivity of the building facade are represented with β_H and μ, the time variable with φ, the convective heat transfer coefficient of the inner and outer surfaces of the facade with β_O and β_I, the long-wave radiation and short-wave radiation of the indoor wall surface with E_KW and E_SW, and the transient heat transfer model of the building facade is expressed with Eq. (8) on the premise that the physical parameters of the building facade are constant:

$\begin{align}  & \frac{\partial \tau }{\partial \phi }={{\beta }_{H}}\frac{{{\partial }^{2}}\tau }{\partial {{a}^{2}}} \\ & -\mu \frac{\partial \tau }{\partial a}{{|}_{a=0}}={{\beta }_{O}}\left( {{\tau }_{T}}-{{\tau }_{a=0}} \right) \\ & -\mu \frac{\partial \tau }{\partial a}{{|}_{a=L}}={{\beta }_{I}}\left( {{\tau }_{a=L}}-{{\tau }_{RA}}\left( \phi  \right) \right)+{{E}_{KW}}-{{E}_{SW}} \\ & \tau \left( a,0 \right)=g\left( a \right) \\\end{align}$     (8)

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Figure 2. Schematic diagram of instantaneous heat gain of indoor air

As the most important factor affecting the indoor thermal environment of residential buildings, dry bulb temperature can be obtained by analyzing the instantaneous heat gain balance equation of air based on the principle of energy conservation. In this paper, the lumped parameter method is used to construct the indoor air temperature and heat balance equation in a time step. Figure 2 shows the instantaneous heat gain of indoor air. Assuming that the indoor air temperature variable and space volume are represented with ∆τ_RA and V_RA, the convective heat transfer between indoor wall and indoor air, indoor heat source and indoor air, and ventilation air flow with W₁, W₂, and W₃ respectively, based on the conservation principle of indoor air heat gain in residential buildings, the indoor temperature heat balance equation shown in Eq. (9) can be constructed:

$\int_{\phi }^{\phi +\Delta \phi }{\left( {{W}_{1}}+{{W}_{2}}+{{W}_{3}} \right)}d\varphi =\Delta {{\tau }_{RA}}{{V}_{RA}}{{\sigma }_{A}}\left( {{\tau }^{\varphi +\Delta \varphi }}-{{\tau }^{\varphi }} \right)$     (9)

where the W₁ value is determined by the indoor wall temperature, while the heat conduction process of the building facade, the solar radiation heat through the door and window openings and the indoor heat radiation jointly affect the indoor wall temperature value. The thermal process of convection heat transfer between indoor wall and indoor air can be analyzed with the steady-state calculation method to analyze the thermal conduction differential equations of the external facades of related buildings. Assuming that the convective heat transfer coefficient and temperature of the indoor i-th surface in the residential buildings are represented with β_i and τ_Si, the area of the i-th surface with S_i, the heat transfer coefficient and area of doors and windows with L_CW and S_W, the dry bulb temperature of outdoor air with τ_D, and the convective heat transfer between the inner surface of each indoor wall and indoor air can be calculated with Eq. (10):

${{W}_{1}}=\sum{{{\beta }_{i}}\left( {{\tau }_{Si}}-{{\tau }_{RA}} \right){{S}_{i}}+{{L}_{CW}}{{S}_{W}}\left( {{\tau }_{D}}-{{\tau }_{RA}} \right)}$     (10)

During the indoor heating of residential buildings, the heat dissipation of indoor heat source is relatively great. The convection heat transfer W₂ between indoor heat source and indoor air is only generated by the radiant heat of indoor heat source acting on indoor walls and transferred to indoor air by convection heat transfer, so the radiant heat of indoor air by indoor heat source can be characterized in W₁. Assuming that the ventilation volume is represented with TA_V, W₃ can be calculated with Eq. (11):

${{W}_{3}}={{\sigma }_{A}}\cdot \rho \cdot {{Q}_{A}}\cdot T{{A}_{V}}\cdot \left( {{\tau }_{OA}}-{{\tau }_{RA}} \right)$     (11)

5.1 Calculation of carbon emissions from commonly used energy in residential buildings

Figure 4 shows the classification of carbon emissions in the life cycle of residential buildings. As can be seen from the figure, the carbon emissions during the operation phase of the buildings involve a three-level emission route: direct carbon emissions caused by fuel combustion, indirect carbon emissions caused by purchased electricity and heat and indirect carbon emissions caused by other industrial chain processes and services. The data basis for carbon emission analysis and calculation during the operation stage of residential buildings is to accurately calculate the carbon emission coefficients of energy and materials during operation.

Energy consumption is the main source of carbon emissions during the operation stage of residential buildings. Assuming that the carbon content, calorific value and oxidation rate of the fuel consumed to maintain the stability of the indoor thermal environment during the operation phase of the residential building are respectively represented with T_C, T_V and η_O, and the default emissions of CH₄ and N₂O released during fuel combustion are respectively represented with DE₁ and DE₂, the carbon emission coefficient CA_C of the fuel consumed can be calculated with the empirical formula shown in Eq. (19):

$C{{A}_{C}}=\left( \text{3}\text{.67}{{T}_{V}}{{\eta }_{O}}+\text{28}D{{E}_{1}}+2\text{65}D{{E}_{2}} \right)\cdot {{T}_{C}}\times 1{{0}^{-6}}$      (19)

4.png

Figure 4. Classification of carbon emissions in the life cycle of residential buildings

Based on the baseline emission factor, this study calculates the carbon emission coefficient of electricity used for electric heating or air conditioning cooling of residential buildings. The specific steps are as follows:

(1) According to the local thermal power generation, the carbon content, carbon oxidation rate, low heating value, effective CO₂ emission coefficient, CH4 emission coefficient, N₂O emission coefficient, carbon emission coefficient and other parameters that characterize the level of carbon emissions are calculated.

(2) Based on the primary energy power production, the total amount of non-thermal power generation is calculated, and the same system boundary condition as thermal power is constructed, which is approximately "zero emission".

(3) The thermal power generation and non-thermal power generation are superimposed to calculate the total power generation of the regional power grid, and further obtain the total carbon emissions caused by the energy consumption of thermal power generation. Assuming that the total amount of carbon emissions from the power supply of the i-th regional power grid is represented with T_RG-i and the total amount of power supply with IA_RG-i, the carbon emission coefficient CA^C_1-i from the power supply of the i-th regional power grid can be calculated with Eq. (20):

$CA_{\text{1}-i}^{C}={{T}_{RG-i}}/I{{A}_{RG-i}}$      (20)

(4) According to the actual power grid layout structure around buildings, the power exchange between regional power grids is analyzed. It is assumed that the electric energy transmitted by the i-th regional power grid to the j-th regional power grid is represented with IA_i-j, and the total amount of electric energy returned by the j-th regional power grid to the i-th regional power grid with IA_j-I, the regional carbon emission coefficient CA^C_2-i without considering line loss including M regional power grids can be calculated with Eq. (21):

$CA_{\text{2-}i}^{C}=\frac{CA_{\text{1-}i}^{C}\cdot \left[ I{{A}_{RG-i}}-\sum\limits_{j=1,j\ne i}^{M}{I{{A}_{i-j}}} \right]+\sum\limits_{j=1,j\ne i}^{M}{CA_{\text{1},j}^{C}\cdot I{{A}_{j-i}}}}{I{{A}_{RG-i}}-\sum\limits_{j=1,j\ne i}^{M}{I{{A}_{i-j}}}+\sum\limits_{j=1,j\ne i}^{M}{I{{A}_{_{j-i}}}}}$     (21)

(5) Assuming that the power transmission loss of the i-th regional power grid is represented with IA_L-i and the corresponding power terminal consumption with IA_PT-i, the line loss ratio μ_L-i of each regional power grid can be calculated with Eq. (22):

${{\mu }_{L\text{-}i}}=I{{A}_{L\text{-}i}}/\left( I{{A}_{PT\text{-}i}}+I{{A}_{L\text{-}i}} \right)$     (22)

(6) According to the calculation results of μ_L-i and CA^C_2-i, the electric carbon emission coefficients CA_C,i of residential buildings considering line loss for electric heating or cooling by air conditioning can be calculated with Eq. (23):

$C{{A}_{C\text{-}i}}=CA_{\text{2-}i}^{C}/\left( 1-{{\mu }_{L\text{-}i}} \right)$     (23)

Based on the energy balance table of thermal production, the carbon emission coefficient of concentrated heating in residential buildings is calculated by using the energy consumption and heat supply of thermal heating. Based on the input and output of processing conversion heating, the total heating carbon emission T_WU-i in the i-th concentrated heating area is calculated, and the corresponding thermal energy output PR_WU-i of thermal heating is further obtained. Ignoring the heat loss ratio of heat supply, the heating carbon emission coefficient CA_WU-i of the i-th concentrated heating area can be calculated with Eq. (24):

$C{{A}_{WU\text{-}i}}={{T}_{WU\text{-}i}}/P{{R}_{WU\text{-}i}}$     (24)

If only the production and use process of energy is considered, it can be considered that the carbon emissions of clean energy sources such as nuclear power, wind power and solar energy are approximately zero. Compared with traditional fossil fuels, clean energy and biomass energy have relatively lower carbon emission levels in the construction, maintenance and production services of energy facilities, which can be ignored. In the time range studied, when analyzing and calculating the energy consumption in the operation stage of residential buildings, it is necessary to summarize the total consumption of all kinds of energy as standard coal converted from low calorific value, and then calculate the total carbon emission based on the consumption and energy utilization efficiency of all kinds of energy to further obtain the corresponding comprehensive carbon emission coefficient.

5.2 Carbon emission calculation of residential buildings in operation stage

In this study, the evaluation indicators on energy-saving effect of thermal environment optimization of residential buildings under the requirements of low-carbon economy operation are constructed:

Level 1 (evaluation objectives):

TEA={TEA₁, TEA₂}={ Technical evaluation and economic evaluation};

Level 2 (primary indicators):

TEA₁={TEA₁₁, TEA₁₂, TEA₁₃, TEA₁₄}={energy use management, green material resource utilization, outdoor thermal environment, indoor thermal environment};

TEA₂={TEA₂₁, TEA₂₂}={operating cost and benefit};

Level 3 (Detailed indicators):

TEA₁₁={TEA₁₁₁, TEA₁₁₂, TEA₁₁₃}={clean energy utilization, energy saving of equipment system, energy saving of use and maintenance};

TEA₁₂={TEA₁₂₁, TEA₁₂₂, TEA₁₂₃, TEA₁₂₄}={use of green building materials, use of energy-saving materials, material recycling and waste reuse, and energy-saving production of green building materials};

TEA₁₃ ={TEA₁₃₁, TEA₁₃₂}={outdoor thermal environment quality, outdoor greening and carbon fixation};

TEA₁₄={TEA₁₄₁, TEA₁₄₂, TEA₁₄₃, TEA₁₄₄}={indoor thermal environment quality, building facade optimization, lighting energy saving, concentrated heating};

TEA₂₁={TEA₂₁₁, TEA₂₁₂, TEA₂₁₃}={operating expenses, maintenance input and energy consumption input};

TEA₂₂={TEA₂₂₁, TEA₂₂₂}={human thermal comfort, public satisfaction}.

Based on the evaluation direction of the above evaluation rules, this study analyzes the two main ways of carbon emissions when residential buildings maintain their stable indoor thermal environment during the operation, namely, building maintenance investment and daily operation energy consumption. Figure 5 shows the carbon emission statistics of residential buildings during the operation. Assuming that the carbon emissions and benchmark values of residential buildings in the operation stage are represented with U_CP and U_CPF respectively, the corresponding emission reduction O_CP can be calculated with Eq. (25):

${{O}_{CP}}={{U}_{CP}}-{{U}_{CPF}}$     (25)

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Figure 5. Carbon emission statistics of residential buildings in operation stage

The maintenance process in the building operation stage involves the optimization of thermal environment with the replacement of only green building materials and energy-saving materials. As the consumption of specific materials for buildings with different structures also varies, it can be estimated according to the estimated proportion of maintenance investment to project construction investment. Assuming that the benchmark value of building maintenance project investment is represented with EB_G, the proportion of input cost for renovation and energy-saving measures with ϕ_CI, and the implied carbon emission intensity with λ_C, then the benchmark value U_G-CPF of carbon emission in the replacement process of green building materials and energy-saving materials can be obtained by the following equation:

$U{}_{G-CPF}=E{{B}_{G}}\cdot {{\varphi }_{CI}}\cdot {{\lambda }_{C}}$      (26)

The daily operation process of residential buildings involves thermal environment optimization and energy saving. The energy consumption mainly includes the power consumption and heat supply energy consumption analyzed in the previous section. Reducing energy carbon emission coefficient and consumption in operation stage can effectively reduce emission reduction, thus realizing energy conservation and emission reduction in daily operation of residential buildings. Assuming that the actual value and benchmark value of the energy carbon emission coefficient base are represented with RV_PBR and RV_PB, and the actual value and benchmark value of energy consumption in daily operation with RV_WBR and RV_WB, the emission reduction ER_NTP realized by reducing the energy carbon emission coefficient can be calculated with Eq. (27):

$E{{R}_{NTP}}=\sum\limits_{l}{R{{V}_{WBR-l}}\cdot \left( R{{V}_{PBR-l}}-R{{V}_{PB-l}} \right)}$     (27)

The emission reduction achieved by reducing energy consumption can be calculated by ER_NTW with Eq. (28):

$E{{R}_{NTW}}=\sum\limits_{l}{\left( R{{V}_{WBR-l}}-R{{V}_{WB-l}} \right)\cdot R{{V}_{PB-l}}}$     (28)

The benchmark value of carbon emissions from electric cooling of residential buildings can be determined based on the calculation results of electric energy consumption of residential buildings, while carbon emissions from thermal heating of residential buildings need to fully consider the local climate zoning. For residential buildings in cold areas where concentrated heating is the main heating mode, the relevant national standard for energy conservation gives the heating design index and thermal consumption index limits of residential buildings in different areas and different floors. Assuming that the calorific value and carbon emission coefficient measured by standard coal are represented with CV_FC and CA_FC, the transmission efficiency of heating pipe network and the yield efficiency of heating boiler with γ₁ and γ₂, the thermal consumption index of residential buildings and the number of days of heating period with H_B and N_day, and the benchmark value of annual heating carbon emission with U_CBD, then the benchmark value of heating carbon emission of residential buildings under concentrated heating mode can be expressed as follows:

${{U}_{CBD}}=24\cdot {{N}_{day}}\cdot {{H}_{B}}/\left( C{{V}_{FC}}\cdot {{\gamma }_{1}}\cdot {{\gamma }_{2}} \right)\cdot C{{A}_{FC}}$      (29)

The benchmark value of lighting carbon emission of residential buildings can be calculated based on the lighting power density values of different types of residential buildings. Assuming that the lighting power density value and the estimated value of the total lighting duration of residential buildings are represented with BL_PDV and ZM_PDV, ignoring the carbon emissions of other electrical equipment that are greatly affected by the subjective consciousness of users, the benchmark value U_PDV of lighting carbon emissions of residential buildings can be calculated with Eq. (30):

${{U}_{PDV}}=B{{L}_{PDV}}\cdot Z{{M}_{PDV}}$     (30)

When considering the biological carbon sequestration amount of indoor greening of residential buildings, assuming that the actual indoor greening rate and the limit value of greening rate are represented with η_AG and η_L, the actual value and benchmark value of CO₂ fixed amount per unit greening area of the year with FV_A and FV_JZ, and the total indoor area of buildings with S_TR, the annual indoor greening emission reduction ER_G can be calculated with Eq. (31):

$E{{R}_{GS}}=\left( {{\eta }_{L}}F{{V}_{JZ}}-{{\eta }_{GS}}F{{V}_{A}} \right)\cdot {{S}_{TR}}$      (31)

If residential buildings adopt energy collection systems of clean energy sources such as solar energy and wind energy for energy conservation, assuming that the net yield and carbon emission coefficient of clean energy are represented with PR_NE and CA_CAP respectively, and the carbon emission of the system during its production, installation and maintenance with U_MF, then the indirect emission reduction ER_HS of the energy-saving system can be estimated by the following equation:

$E{{R}_{HS}}=-P{{R}_{NE}}\cdot C{{A}_{CAP}}+{{U}_{MF}}$     (32)

The study analyzes the thermal environment optimization strategies and energy-saving technologies of residential buildings under the demand of low-carbon operation. Firstly, it analyzes the indoor thermal environment of residential buildings based on the external disturbance conditions, internal disturbance conditions and ventilation, constructs the heat transfer model of the facade of residential building, and calculate the indoor air temperature. It describes the third-order polynomial fitting functions between different heat source area ratios and corresponding area coefficients, different heat source heights and corresponding height coefficients, and different heat source radiant heat ratios and corresponding radiation coefficients in detail. Then, it explores the indoor heat distribution mechanism of residential buildings under the heating mode of concentrated heat source, and analyzes the generation process of hot jet above the heat source and the influence of concentrated heat source on temperature distribution. Finally, the study provides the calculation method of carbon emission from common energy sources in residential buildings. The experimental results show the temperature changes monitored at each point under different dissipation degrees of heating heat sources. This study also analyzes the change curves of electricity and thermal consumption of different residential buildings and the change curves of carbon emissions under different heating modes of residential buildings, and gives some measures to improve energy efficiency and reduce carbon emissions. The study provides the change curve of carbon emission during the operation of residential buildings, obtains the composition of carbon emissions, and summarizes the change trend of carbon emissions during the operation of residential buildings in different regions.