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Urban Mixed Use and its Impact on Energy Performance of Micro Gird System
Available online at www.sciencedirect.com
ScienceDirect Energy Procedia 103 (2016) 339 – 344
Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid, 19-21 April 2016, Maldives
Urban mixed use and its impact on energy performance of micro gird system Yinan Zhoua,*, Ziyue Lia, Xinyu Taoa a
Sino-US Eco Urban Lab, College of Architecture and Urban Planning, Tongji University, Shanghai, 200092, China
Abstract Urban mixed use as one of the key urban morphological factors, has the potential to impact the urban energy supply and demand, including not only transportation energy but also building energy. This paper is focusing on mix-used urban functions and building energy performance, such as residential building, commercial building, office and so on, to explore the correlation between them by computing simulation of simplified models. First of all, the district energy performance with different cover ratios, but the same mix-used ratio is examined. Then aiming for achieving stable energy profile, the energy fluctuation with different mix-used ratio is evaluated and analyzed based on the same physical model. Solar potential is also taken into consideration during the process. Finally, this paper concludes that urban mixed use can impact the energy efficiency in certain degrees, meanwhile its potential to guide urban design is discussed. © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license © 2016 The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and/or peer-reviewof under responsibility of REM2016 Peer-review under responsibility the scientific committee of the Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid. Keywords: Mixed use; Urban form; District energy performance; Energy fluctuation; Simulation; Micro grid system
1. Introduction As the basic urban morphological factor, mixed use is advocated by ecological urbanism and considered to be a pathway leading to a sustainable urban design. Various urban functions such as residential building, commercial building, office and so on, are planned meticulously to close to each other in the walking distance. This kind of community is inclusive and connected, and in some literatures, it is called compact district. It is pedestrian-oriented and contains elements of a live-work-play environment. However, as for the question how the compact city can achieve high energy efficiency, most of the current researches focus on transportation aspect, because the needs of residents' daily life can
* Corresponding author. Tel.: +86-185-1121-8126; fax: +86-021-6598-6707.
E-mail address: [email protected].
1876-6102 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid. doi:10.1016/j.egypro.2016.11.296
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Yinan Zhou et al. / Energy Procedia 103 (2016) 339 – 344
be satisfied without long-distance travel so that the gas of the automobile is reduced dramatically [1]. Different urban functions not only impact the transportation energy but also the fluctuation of energy profile of the district buildings in a certain period. So it can be applied as design criteria for urban planning in preliminary stage. Hachem [2] studies on the design of a solar mixed-use community and the analysis of its performance basing on potential energy generation and energy consumption of different functions. In the existing research mixed use is considered to be a prerequisite not a variable so that the impact of energy performance caused by the variety of mixed use is not clear. This paper lays out a research method for the above topic in the district level. 2. Research Question Two questions are raised corresponding to sequential steps of implementing this research as follows. (1) What density or cover ratio does the urban mixed use has the best energy performance with? It can be interpreted as how dense the designer layouts the buildings in the district with the certain mixed use ratio. Martin [3] proposed the question what kind of land use has the best performance and influenced subsequent researches, which indicates that different kind of functions in specific climate and geographic area has its most appropriate form for energy saving. Even though the floor area ratio of each function is fixed, the corresponding urban forms can be totally different. Building density (cover ratio) as the main urban form contributor can not only impact energy demand because of sunlight availability, wind fluent condition and so on, but also impact the capacity of potential energy generation when considering of solar. (2) Is there an ideal floor area proportion of different functions that has the best energy performance? It addresses the question that whether there is the best combination method of different functions that can reduce the peak energy use to sustain system stability so that the system can acquire the best operational efficiency. For instance, the energy consumption of residential building amounts to the peak in the morning and evening, but conversely for commercial building and office it appears in the daytime. If the total capacity of energy supply is constrained, it is the best way to balance the energy profiles of different functions, in terms of proper adjustment of the mixed use ratio, to avoid the longstanding energy surplus and deficiency. 3. Research method Two experiments are designed to address the questions raised above respectively. A simulation approach based on Martin's ideal model is applied in these experiments. It assumes that the objective district comprises three basic types, including residence, business and office. Each of them has its particular energy consumption profile due to different utility schedule in the same time span. If stacking up the three profile curves according to different weight or its floor area proportion, there is an obvious fluctuation indicating the stability of energy consumption of the whole district. By doing so, energy performance can be analyzed and estimated from architecture scale to district scale, in which the influence of urban context is inclusive. It is widely accepted that when the energy consumption curve turns to be stable, the efficiency of energy system can be improved. Thus intelligently adjusting the floor area proportion of single function to eliminate the energy peak and optimize the integrated curve shows its potential to improve the energy performance. Additional pressure to install and utilize micro grid system has increased in recent years due to the deteriorated environment. On-site renewable energy is a crucial impact factor for energy supply and is also considered in this research. As for the technology popularity in reality, solar energy as the representative is calculated and solar panels are assumed to cover all the roof areas of the buildings. Two experiments are basing on 3D model which are created in Rhinoceros5.0 and Grasshopper. EnergyPlusTM as a powerful tool not only to evaluate energy consumption, such as heating, cooling, ventilation, lighting, and plug and process loads, but also to investigate the complexities and non-linearity
Yinan Zhou et al. / Energy Procedia 103 (2016) 339 – 344
of various physical phenomena is used as a simulation tool. Two experiments are presumed in Shanghai weather conditions and utility schedules corresponding to each function refer to the standard from American Department of Energy and is adjusted to accommodate Chinese habits. ˖energy performance with different density 4. Experiment 1˖ 4.1. Objectives Experiment 1 is aiming to discuss how energy consumption of mix-used district varies with different density. It compares district energy consumption profiles with different cover ratio. All of the models have the same FAR (floor area ratio) and mixed use proportion. District energy consumption profile is to sum up the energy consumption of residential, commercial and office buildings and then subtract the solar energy potential.
Fig. 1. Four models with different cover ratio
Fig. 2. Simulation result
4.2. Constants and Variables Constants in this experiment are block size, FAR, and mixed use proportion. The testing model is an 800m X 800m urban block, whose FAR is 1.9. The mixed use proportion is constituted by 70% residential building, 15% commercial building and 15% office. Then four scenarios with different cover ratio, 0.48, 0.36, 0.24 and 0.12, are proposed (Fig.1). All of them are planned following the centralized development mode, which means that residence and office are located in the center and encompassed by residential area. Building form is from the simplification of local architecture prototype. The different cover ratio represents the typical development mode that is commonly used in China, from which the influence of urban context can be concluded. For example, when the cover ratio is 0.48, it represents a denser district with lower building height and relatively less open space. But when the cover ratio decreases to 0.12, the block is shaped by high rise buildings and the distance between adjacent buildings is wider. 4.3. Workflow The workflow includes sequentially three steps as follows. (1) Modeling. Simplified 3D model is an appropriate way for testing on district scale, in which due to the requirements of simulation accuracy and computing speed some architecture details can be ignored. (2) Energy consumption simulation. Testing models are divided into basic thermal zones for energy consumption simulation. Every one storey for each building should be divided into five thermo zones, including four zones adjacent to different orientations and one central zone. For each function, its corresponding parameters should be set respectively including window to wall ratio, heat transfer
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Yinan Zhou et al. / Energy Procedia 103 (2016) 339 – 344
coefficient, energy load, HVAC system, temperature set point, occupancy schedule, building materials and constructions conforming to local codes. Moreover, roof panels are set up independently for solar potential simulation. 80% of the roof panels are taken as effective area for calculation, while the efficiency index of PV module is set as 0.15. (3) Data analysis. The outputs are more valuable as relative indicators in comparative analysis so that the impact caused by density will be examined directly. After the simulation, energy consumption profiles of each density per typical day, per typical week and per year are graphed by hour. In this step, two aspects should be focused on. One is the total amount of energy consumption and the other is the degree of the fluctuation of energy consumption within a certain time span, which is measured by SD (Standard Deviation) and CV (Coefficient of Variation). The CV is a standardized measure of dispersion of a probability distribution or frequency distribution in probability theory and statistics. It is defined as the ratio of the standard deviation to the mean (or its absolute value). 4.4. Results Comparing the total energy consumption of the four scenarios, the result shows a negative correlation with cover ratio (Fig.2). When the density increases, the energy consumption decreases. The total energy consumption of a year decreases about 36% when cover ratio changes from 0.12 to 0.48. Due to Shanghai climate condition that cooling in summer accounts for the largest proportion of energy use, it can be understood that in the denser district the sunlight absorbed by the buildings is less. Meanwhile not as evident as energy consumption, the CV changes slightly, which means that the cover ratio almost doesn't make any impact on the stability of energy profile but it impacts the amount of total energy consumption. ˖energy performance with different mix-used ratio 5. Experiment 2˖
Fig.3. Four scenarios with different mixed use ratio
Fig. 4. CV comparison of four scenarios
5.1. Objectives Energy efficiency of mix-used district is demonstrated to be much better than those with single function as a result that different operational schedules make the peak hours of energy consumption staggered. For instance, the peak hour of residential building appears in the morning and evening but for office it appears in daytime. Nevertheless, is it more energy-efficient when floor area proportion of commercial and office buildings increases? The result of this experiment can help us to quantify the appropriate mixed use ratio from an energy perspective.
Yinan Zhou et al. / Energy Procedia 103 (2016) 339 – 344
5.2. Constants and variables In this experiment, all of the morphological factors are constants, including block size, cover ratio, FAR and so on. The testing area is an 800m x 800m block, while FAR is 5.87 and cover ratio is 0.59. Four scenarios with different mixed use ratio are proposed, including (residential building: commercial building: office) 1:0:0 (only residential building), 0.84:0.08:0.08, 0.68:0.16:0.16 and 0.36:0.32:0.32 (Fig.3). 5.3. Workflow The workflow includes three sequential steps similar to the previous experiment: (1) Modeling; (2) Energy consumption simulation; (3) Data analysis. As for modeling, high-rise buildings and shopping malls with huge volume are located in the central area, while low-rise courtyards enclose the center. Different colors represent different urban functions. Thermal zone division, parameter setting and solar simulation setting refer to experiment 1. 5.4. Results
Fig.5. Hourly energy consumption profile in a typical winter week
Because the urban form doesn't change under the different mixed use ratio, the solar potential related to roof area of the four scenarios is the same. So the difference of net energy consumption is manifested to be determined by the total energy consumption, which consists of three energy consumption curves: residence, commerce and office. The empirical investigation in Shanghai indicates that commercial building and office have much more energy consumption than residential buildings. Commercial building is about 8 times as much as residential building. Obviously, if the mixed use proportion of commercial building and office increases, no doubt that the total energy consumption should increase. However, the fluctuation degree of the energy profile is more valuable to study for system efficiency optimization. In comparison with the CV values of the annual energy profile of the four models, as the mixed use ratio increase, firstly it decreases and then increases (Fig.4). The second model with the ratio of 0.84:0.08:0.08 reaches the minimum CV value, which is 20% lower than maximum with the ratio of 0.36:0.32:0.32. With respect to a typical winter week (Fig.5), the minimum with a ratio of 0.84:0.08:0.08 is 26% lower than the maximum with a ratio of 1:0:0. In a typical summer week, the minimum with a ratio of 0.84:0.08:0.08 is 59% lower than the maximum with a ratio of 0.36:0.32:0.32. On a typical winter day, the minimum value is 60% lower than the maximum. On a typical summer day, the minimum value is 53% lower than the maximum. In conclusion, the fluctuation degree of energy consumption is impacted by mixed use ratio largely, but it is a non-linear correlation. The mixed use ratio with the most stable energy profile is approaching to 8:1:1.
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Yinan Zhou et al. / Energy Procedia 103 (2016) 339 – 344
6. Further discussion According to Baker and Steemers [4], building design accounts for a 2.5 times variation in energy consumption, while system efficiency accounts for a 2 times variation. However, the impact of urban context is unknown and to be explored. From above experiments, in specific climate condition such as Shanghai, urban mixed can impact the district energy performance dramatically, including the quantity of net energy consumption and fluctuation degree of energy profile. Research methodology is more important than results because in different cities and different climate conditions the result will be totally different or even conversed to each other. Thus a native research based on local weather data is suggested. The trend towards urban district with micro grid system is more distinct than ever before. Conventionally when urban planners design a mix-used district, the scale of district should be determined by walking distance or accessibility regardless of energy issue. From the experiments above, it can be envisioned whether the reasonable mix-used principles including proper density and floor area ratio can become one of the criteria to help us redefine the dimension of urban energy cell, in which the energy consumption of different functions can be balanced. In the preliminary design, if it is possible, energy efficiency has the potential to be improved by function arrangement following criteria of the mixed use ratio. It is not only useful for a new development to shape urban form but also for downtown regeneration to shape the energy micro grid. This research is a pilot research and the validation and application will be researched and discussed in future. References [1] Cervero R, Kockelman K. Travel demand and the 3Ds: Density, diversity,and design. Transportation Research Part D:Transport and Environment 1997; 2(3):199-219. [2] Hachem C. Design of a base case mixed-use community and its energy performance. Energy procedia 2015; 78:663-668. [3] Martin L, March L. Urban Space and Structure. Cambridge Press, UK,1972. [4] Baker N, Steemers K. The LT method. Batsford for the Commission of the European Community, London,1992.
Biography Yinan Zhou is a Ph.D. candidate at College of Architecture and Urban Planning, Tongji University and a visiting scholar in Eco Urban Lab, Georgia Institute of Technology. He is LEED Accredited Professionals and his work focus on ecological urban design and sustainable building design.
ScienceDirect Energy Procedia 103 (2016) 339 – 344
Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid, 19-21 April 2016, Maldives
Urban mixed use and its impact on energy performance of micro gird system Yinan Zhoua,*, Ziyue Lia, Xinyu Taoa a
Sino-US Eco Urban Lab, College of Architecture and Urban Planning, Tongji University, Shanghai, 200092, China
Abstract Urban mixed use as one of the key urban morphological factors, has the potential to impact the urban energy supply and demand, including not only transportation energy but also building energy. This paper is focusing on mix-used urban functions and building energy performance, such as residential building, commercial building, office and so on, to explore the correlation between them by computing simulation of simplified models. First of all, the district energy performance with different cover ratios, but the same mix-used ratio is examined. Then aiming for achieving stable energy profile, the energy fluctuation with different mix-used ratio is evaluated and analyzed based on the same physical model. Solar potential is also taken into consideration during the process. Finally, this paper concludes that urban mixed use can impact the energy efficiency in certain degrees, meanwhile its potential to guide urban design is discussed. © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license © 2016 The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and/or peer-reviewof under responsibility of REM2016 Peer-review under responsibility the scientific committee of the Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid. Keywords: Mixed use; Urban form; District energy performance; Energy fluctuation; Simulation; Micro grid system
1. Introduction As the basic urban morphological factor, mixed use is advocated by ecological urbanism and considered to be a pathway leading to a sustainable urban design. Various urban functions such as residential building, commercial building, office and so on, are planned meticulously to close to each other in the walking distance. This kind of community is inclusive and connected, and in some literatures, it is called compact district. It is pedestrian-oriented and contains elements of a live-work-play environment. However, as for the question how the compact city can achieve high energy efficiency, most of the current researches focus on transportation aspect, because the needs of residents' daily life can
* Corresponding author. Tel.: +86-185-1121-8126; fax: +86-021-6598-6707.
E-mail address: [email protected].
1876-6102 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, REM2016: Renewable Energy Integration with Mini/Microgrid. doi:10.1016/j.egypro.2016.11.296
340
Yinan Zhou et al. / Energy Procedia 103 (2016) 339 – 344
be satisfied without long-distance travel so that the gas of the automobile is reduced dramatically [1]. Different urban functions not only impact the transportation energy but also the fluctuation of energy profile of the district buildings in a certain period. So it can be applied as design criteria for urban planning in preliminary stage. Hachem [2] studies on the design of a solar mixed-use community and the analysis of its performance basing on potential energy generation and energy consumption of different functions. In the existing research mixed use is considered to be a prerequisite not a variable so that the impact of energy performance caused by the variety of mixed use is not clear. This paper lays out a research method for the above topic in the district level. 2. Research Question Two questions are raised corresponding to sequential steps of implementing this research as follows. (1) What density or cover ratio does the urban mixed use has the best energy performance with? It can be interpreted as how dense the designer layouts the buildings in the district with the certain mixed use ratio. Martin [3] proposed the question what kind of land use has the best performance and influenced subsequent researches, which indicates that different kind of functions in specific climate and geographic area has its most appropriate form for energy saving. Even though the floor area ratio of each function is fixed, the corresponding urban forms can be totally different. Building density (cover ratio) as the main urban form contributor can not only impact energy demand because of sunlight availability, wind fluent condition and so on, but also impact the capacity of potential energy generation when considering of solar. (2) Is there an ideal floor area proportion of different functions that has the best energy performance? It addresses the question that whether there is the best combination method of different functions that can reduce the peak energy use to sustain system stability so that the system can acquire the best operational efficiency. For instance, the energy consumption of residential building amounts to the peak in the morning and evening, but conversely for commercial building and office it appears in the daytime. If the total capacity of energy supply is constrained, it is the best way to balance the energy profiles of different functions, in terms of proper adjustment of the mixed use ratio, to avoid the longstanding energy surplus and deficiency. 3. Research method Two experiments are designed to address the questions raised above respectively. A simulation approach based on Martin's ideal model is applied in these experiments. It assumes that the objective district comprises three basic types, including residence, business and office. Each of them has its particular energy consumption profile due to different utility schedule in the same time span. If stacking up the three profile curves according to different weight or its floor area proportion, there is an obvious fluctuation indicating the stability of energy consumption of the whole district. By doing so, energy performance can be analyzed and estimated from architecture scale to district scale, in which the influence of urban context is inclusive. It is widely accepted that when the energy consumption curve turns to be stable, the efficiency of energy system can be improved. Thus intelligently adjusting the floor area proportion of single function to eliminate the energy peak and optimize the integrated curve shows its potential to improve the energy performance. Additional pressure to install and utilize micro grid system has increased in recent years due to the deteriorated environment. On-site renewable energy is a crucial impact factor for energy supply and is also considered in this research. As for the technology popularity in reality, solar energy as the representative is calculated and solar panels are assumed to cover all the roof areas of the buildings. Two experiments are basing on 3D model which are created in Rhinoceros5.0 and Grasshopper. EnergyPlusTM as a powerful tool not only to evaluate energy consumption, such as heating, cooling, ventilation, lighting, and plug and process loads, but also to investigate the complexities and non-linearity
Yinan Zhou et al. / Energy Procedia 103 (2016) 339 – 344
of various physical phenomena is used as a simulation tool. Two experiments are presumed in Shanghai weather conditions and utility schedules corresponding to each function refer to the standard from American Department of Energy and is adjusted to accommodate Chinese habits. ˖energy performance with different density 4. Experiment 1˖ 4.1. Objectives Experiment 1 is aiming to discuss how energy consumption of mix-used district varies with different density. It compares district energy consumption profiles with different cover ratio. All of the models have the same FAR (floor area ratio) and mixed use proportion. District energy consumption profile is to sum up the energy consumption of residential, commercial and office buildings and then subtract the solar energy potential.
Fig. 1. Four models with different cover ratio
Fig. 2. Simulation result
4.2. Constants and Variables Constants in this experiment are block size, FAR, and mixed use proportion. The testing model is an 800m X 800m urban block, whose FAR is 1.9. The mixed use proportion is constituted by 70% residential building, 15% commercial building and 15% office. Then four scenarios with different cover ratio, 0.48, 0.36, 0.24 and 0.12, are proposed (Fig.1). All of them are planned following the centralized development mode, which means that residence and office are located in the center and encompassed by residential area. Building form is from the simplification of local architecture prototype. The different cover ratio represents the typical development mode that is commonly used in China, from which the influence of urban context can be concluded. For example, when the cover ratio is 0.48, it represents a denser district with lower building height and relatively less open space. But when the cover ratio decreases to 0.12, the block is shaped by high rise buildings and the distance between adjacent buildings is wider. 4.3. Workflow The workflow includes sequentially three steps as follows. (1) Modeling. Simplified 3D model is an appropriate way for testing on district scale, in which due to the requirements of simulation accuracy and computing speed some architecture details can be ignored. (2) Energy consumption simulation. Testing models are divided into basic thermal zones for energy consumption simulation. Every one storey for each building should be divided into five thermo zones, including four zones adjacent to different orientations and one central zone. For each function, its corresponding parameters should be set respectively including window to wall ratio, heat transfer
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Yinan Zhou et al. / Energy Procedia 103 (2016) 339 – 344
coefficient, energy load, HVAC system, temperature set point, occupancy schedule, building materials and constructions conforming to local codes. Moreover, roof panels are set up independently for solar potential simulation. 80% of the roof panels are taken as effective area for calculation, while the efficiency index of PV module is set as 0.15. (3) Data analysis. The outputs are more valuable as relative indicators in comparative analysis so that the impact caused by density will be examined directly. After the simulation, energy consumption profiles of each density per typical day, per typical week and per year are graphed by hour. In this step, two aspects should be focused on. One is the total amount of energy consumption and the other is the degree of the fluctuation of energy consumption within a certain time span, which is measured by SD (Standard Deviation) and CV (Coefficient of Variation). The CV is a standardized measure of dispersion of a probability distribution or frequency distribution in probability theory and statistics. It is defined as the ratio of the standard deviation to the mean (or its absolute value). 4.4. Results Comparing the total energy consumption of the four scenarios, the result shows a negative correlation with cover ratio (Fig.2). When the density increases, the energy consumption decreases. The total energy consumption of a year decreases about 36% when cover ratio changes from 0.12 to 0.48. Due to Shanghai climate condition that cooling in summer accounts for the largest proportion of energy use, it can be understood that in the denser district the sunlight absorbed by the buildings is less. Meanwhile not as evident as energy consumption, the CV changes slightly, which means that the cover ratio almost doesn't make any impact on the stability of energy profile but it impacts the amount of total energy consumption. ˖energy performance with different mix-used ratio 5. Experiment 2˖
Fig.3. Four scenarios with different mixed use ratio
Fig. 4. CV comparison of four scenarios
5.1. Objectives Energy efficiency of mix-used district is demonstrated to be much better than those with single function as a result that different operational schedules make the peak hours of energy consumption staggered. For instance, the peak hour of residential building appears in the morning and evening but for office it appears in daytime. Nevertheless, is it more energy-efficient when floor area proportion of commercial and office buildings increases? The result of this experiment can help us to quantify the appropriate mixed use ratio from an energy perspective.
Yinan Zhou et al. / Energy Procedia 103 (2016) 339 – 344
5.2. Constants and variables In this experiment, all of the morphological factors are constants, including block size, cover ratio, FAR and so on. The testing area is an 800m x 800m block, while FAR is 5.87 and cover ratio is 0.59. Four scenarios with different mixed use ratio are proposed, including (residential building: commercial building: office) 1:0:0 (only residential building), 0.84:0.08:0.08, 0.68:0.16:0.16 and 0.36:0.32:0.32 (Fig.3). 5.3. Workflow The workflow includes three sequential steps similar to the previous experiment: (1) Modeling; (2) Energy consumption simulation; (3) Data analysis. As for modeling, high-rise buildings and shopping malls with huge volume are located in the central area, while low-rise courtyards enclose the center. Different colors represent different urban functions. Thermal zone division, parameter setting and solar simulation setting refer to experiment 1. 5.4. Results
Fig.5. Hourly energy consumption profile in a typical winter week
Because the urban form doesn't change under the different mixed use ratio, the solar potential related to roof area of the four scenarios is the same. So the difference of net energy consumption is manifested to be determined by the total energy consumption, which consists of three energy consumption curves: residence, commerce and office. The empirical investigation in Shanghai indicates that commercial building and office have much more energy consumption than residential buildings. Commercial building is about 8 times as much as residential building. Obviously, if the mixed use proportion of commercial building and office increases, no doubt that the total energy consumption should increase. However, the fluctuation degree of the energy profile is more valuable to study for system efficiency optimization. In comparison with the CV values of the annual energy profile of the four models, as the mixed use ratio increase, firstly it decreases and then increases (Fig.4). The second model with the ratio of 0.84:0.08:0.08 reaches the minimum CV value, which is 20% lower than maximum with the ratio of 0.36:0.32:0.32. With respect to a typical winter week (Fig.5), the minimum with a ratio of 0.84:0.08:0.08 is 26% lower than the maximum with a ratio of 1:0:0. In a typical summer week, the minimum with a ratio of 0.84:0.08:0.08 is 59% lower than the maximum with a ratio of 0.36:0.32:0.32. On a typical winter day, the minimum value is 60% lower than the maximum. On a typical summer day, the minimum value is 53% lower than the maximum. In conclusion, the fluctuation degree of energy consumption is impacted by mixed use ratio largely, but it is a non-linear correlation. The mixed use ratio with the most stable energy profile is approaching to 8:1:1.
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Yinan Zhou et al. / Energy Procedia 103 (2016) 339 – 344
6. Further discussion According to Baker and Steemers [4], building design accounts for a 2.5 times variation in energy consumption, while system efficiency accounts for a 2 times variation. However, the impact of urban context is unknown and to be explored. From above experiments, in specific climate condition such as Shanghai, urban mixed can impact the district energy performance dramatically, including the quantity of net energy consumption and fluctuation degree of energy profile. Research methodology is more important than results because in different cities and different climate conditions the result will be totally different or even conversed to each other. Thus a native research based on local weather data is suggested. The trend towards urban district with micro grid system is more distinct than ever before. Conventionally when urban planners design a mix-used district, the scale of district should be determined by walking distance or accessibility regardless of energy issue. From the experiments above, it can be envisioned whether the reasonable mix-used principles including proper density and floor area ratio can become one of the criteria to help us redefine the dimension of urban energy cell, in which the energy consumption of different functions can be balanced. In the preliminary design, if it is possible, energy efficiency has the potential to be improved by function arrangement following criteria of the mixed use ratio. It is not only useful for a new development to shape urban form but also for downtown regeneration to shape the energy micro grid. This research is a pilot research and the validation and application will be researched and discussed in future. References [1] Cervero R, Kockelman K. Travel demand and the 3Ds: Density, diversity,and design. Transportation Research Part D:Transport and Environment 1997; 2(3):199-219. [2] Hachem C. Design of a base case mixed-use community and its energy performance. Energy procedia 2015; 78:663-668. [3] Martin L, March L. Urban Space and Structure. Cambridge Press, UK,1972. [4] Baker N, Steemers K. The LT method. Batsford for the Commission of the European Community, London,1992.
Biography Yinan Zhou is a Ph.D. candidate at College of Architecture and Urban Planning, Tongji University and a visiting scholar in Eco Urban Lab, Georgia Institute of Technology. He is LEED Accredited Professionals and his work focus on ecological urban design and sustainable building design.