006 160719 urban environment analysis for new and existing neighborhood
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006 160719 urban environment analysis for new and existing neighborhood
- 1. NTNU-SJTU 2016 SEniC Summer School NTNU Teacher Team, Monday 18.07.2016 Urban Environmental Analysis for New and Existing Neighborhood Case studies and Experiences Example of an interdisciplinary approach Gabriele Lobaccaro Postdoctoral Research Fellow
- 2. EU Energy Roadmap 2050
- 7. 0 CLIMATE
- 10. Luca Finocchiaro
- 11. Luca Finocchiaro
- 14. Luca Finocchiaro
- 15. Luca Finocchiaro
- 20. The total solar energy absorbed from the earth is equal: 3,850,000 EJ The use of primary energy in 2009 was equal to: 510 EJ Electricity: 62EJ Energy Unused
- 23. International research activities SUBTASK C: Case studies and action research Lead: Gabriele Lobaccaro and Carmel Lindkvist, NTNU, Norway
- 24. Solar Radiation vs Orography
- 28. 20 Fenchurch Street - London
- 29. 20 Fenchurch Street - London
- 30. 20 Fenchurch Street - London
- 37. Palazzo della Regione Lombardia - Milan
- 39. Case study - Milan
- 41. Generative parametric solar optimization process
- 42. Solar irradiation simulations- District analyses Considering the surrounding (mutual reflections)
- 45. The empire state building- NYC
- 46. Burj Khalifa - Dubai
- 48. Simulation criteria and design strategies for solar availability Use of dynamic simulation tools for case studies of urban planning Clara Good - Gabriele Lobaccaro PhD Candidate - Postdoctoral research fellow Department of Architectural Design, History and Technology Siri Hårklau Master student Department of Electric Power Engineering IEA TASK 51 “Solar Energy in Urban Planning” Subtask C - Case study
- 49. Localization of the area Lerkendal district NTNU Gløshaugens Campus Lerkendal district Trondheim Centre N View of the area from the top - Source: google maps
- 50. Surrounding environment Lerkendal district - Stadium Top view from the East side - Source: http://www.info-stades.fr/
- 51. Solar Radiation in Norway Trondheim case study ZEB/BiPV commercial building View from the North side - Photo: Gabriele Lobaccaro
- 52. Solar Radiation in Norway Trondheim case study ZEB/BiPV commercial building Data • Total building area approx . 11000 m2 of which 7,300 m2; • Annual consumption not more than 84 kWh/m2 must meet energy class A. • The building is connected to district heating plants , power grids and also has its own production of electricity in a solar system. Solar System • 203 m2 on the south and west facades, 27.2 kWp, 9 strings; • The estimated annual production of approx. 18,000 kWh; • Actual production in 2013 approx . 15,000 kWh. 15% higher than simulated. Source: http://tronderenergi.no/
- 53. Surrounding environment Lerkendal district - Trondheim case study View before the construction of the Lerkendal Studentby - Source: http://lerkendalblogg.skanska.no/
- 54. Solar Radiation in Norway Lerkendal Studenby Rendering and model of the districtMasterplan of the new student houses Source: https://www.arkitektur.no/lerkendal-studentby
- 55. Solar Radiation in Norway Lerkendal studentby Different design solutions Source: https://www.arkitektur.no/lerkendal-studentby
- 56. Solar Radiation in Norway – Trondheim case study Lerkendal district View from the Tower Hotel - Source: http://www.skyscrapercity.com/
- 57. Surrounding environment Lerkendal district View from the South side - Photo: Gabriele Lobaccaro
- 58. Surrounding environment Tower Hotel View from the North side - Photo: Gabriele Lobaccaro
- 59. Solar Radiation in Norway - Trondheim case study Overshadowing effect - Lack of preliminary study View from the South side - Photo: Gabriele Lobaccaro
- 60. Solar Radiation in Norway - Trondheim case study Overshadowing effect - Lack of preliminary study View from the Tower Hotel - Source: http://www.adressa.no/
- 61. Solar Radiation in Norway - Trondheim case study Overshadowing effect - Lack of preliminary study View from inside the Lerkendal Studentby - Photo: Gabriele Lobaccaro
- 62. Methodology of Analysis using dynamic simulation tools Level of simulation 1: Local solar potential (isolated scenario) 2: Influence from surroundings (context scenario) 3: Evaluate solar technologies based on energy demand DiVA for Rhino Based on Radiance ray-tracing method Pvsyst PV simulation Polysun Solar thermal Source: Presentation from RERC 2014 presentation - Author: Clara Good
- 63. Solar Radiation in Norway - Trondheim case study Solar Mapping Analysis - Context scenario (entire building envelope) View from inside the Lerkendal Studentby - Author: Gabriele Lobaccaro Scenario Surface [m2] Direct radiation [kWh/yr] Global radiation [kWh/yr] Context scenario 5591.38 1416210.24 3261902.7 - 20% of direct radiation - 11.5% of global radiation N Compare to the isolated scenario
- 64. Solar Radiation in Norway - Trondheim case study Solar Mapping Analysis - Context scenario (South Façade and PV part) Scenario Surface South Facade [m2] Direct radiation [kWh/yr] Global radiation [kWh/yr] Context scenario 665 (entire) 232386 430666 Context scenario 194.5 (only PV part in blue) 68626 124007 - 49%of direct radiation for PV systems - 50%of direct radiation for South Facade - 42%of global radiation for PV systems - 40%of global radiation for South Facade + 7%of solar reflection contribution + 10%of solar reflection contribution Simulation analysis - Author: Gabriele Lobaccaro N Compare to the isolated scenario
- 65. Source: Presentation from RERC 2014 presentation - Author: Clara Good Area B Design criterion: Same system area (200 m2) Least affected areas Localization of the most irradiated areas
- 66. Output from area A (facade) has more even profile Solar energy output Area A – Façade Source: Presentation from RERC 2014 presentation - Author: Clara Good
- 67. Output from area B (roof) peaks in summer Solar energy output Area B - Roof Source: Presentation from RERC 2014 presentation - Author: Clara Good
- 68. Percentage of energy demand Comparison among systems Source: Presentation from RERC 2014 presentation - Author: Clara Good PV covers 3-6% of electricity demand Solar thermal covers 21-26% of thermal demand
- 70. Green actions and design solutions to mitigate heat wave risk in the city of Bilbao Gabriele Lobaccaro with collaboration: Acero Juan Angel (Tecnalia) Postdoctoral research fellowship Faculty of Architecture and Fine Art NTNU Group: Annemie Wyckmans, Naia Landa (KTH), Fernanda Pacheco, James Kallaos, NTNU Norwegian University of Science and Technology Krishna Bharathi 70 8th December 2015 - Berchem
- 71. 71 FP7 EU RAMSES Reconciling Adaptation, Mitigation and Sustainable Development for Cities http://www.ramses-cities.eu/
- 72. Reconciling Adaptation, Mitigation and Sustainable Development for Cities Extract of the plan of the “Anillo verde de Bilbao”: in green the routes of “Gran Recorrido de Bilbao, in red the auxiliary routes and in blue the path of the “Cammino di Santiago”. Connection between the green belt and city parks 72Source: http://www.bilbao.net/ Compact Midrise Compact Lowrise Casco Viejo Abando/Indautxu Open-set Highrise Txurdinaga
- 73. Reconciling Adaptation, Mitigation and Sustainable Development for Cities Connection between the green belt and city parks HOW Reduction of the heat wave risk in the city of Bilbao 73
- 74. Reconciling Adaptation, Mitigation and Sustainable Development for Cities Analysis of the Urban Areas Analysis of the built areas in the districts of Casco Viejo (compact lowrise), Abando/Indautxu (compact midrise) and the Txurdinaga (open-set highrise). Analysis of the streets in the districts of Casco Viejo (compact lowrise), Abando/Indautxu (compact midrise) and the Txurdinaga (open-set highrise). 74
- 75. 75 Reconciling Adaptation, Mitigation and Sustainable Development for Cities Analysis of the Urban Areas Category Urban Areas Height Width H/W Façades mat. Roofs mat. Soil Compact lowrise Casco Viejo 16 m 4.5 m 3.5 concrete/brick/stone terracotta brick/stone Compact midrise Abando / Indautxu 24 m 16 m 1.5 concrete/brick/stone terracotta /impervious asphalt Open-set highrise Txurdinaga 40 m 30 m 1.3 concrete/brick terracotta /impervious asphalt 16m 16m 24m 4.5m 30m 40m Compact Lowrise Compact Midrise Open-set Highrise
- 77. Methodology Reconciling Adaptation, Mitigation and Sustainable Development for Cities • Analysis conducted using ENVImet. • Meteorological parameters, albedo of the surface and solid angle proportion. • Outputs Predicted Mean Vote (PMV), Physiological Equivalent Temperature (PET) to evaluate the thermal stress affecting the body; • Building geometry/orientation, vegetation elements, urban parks, and street canyons; • Analysis of urban thermal comfort and impact assessment of climate change scenarios in urban areas. 77 Source: http://www.envi-met.com/
- 78. Input for the ENVI-met simulations based on real data Reconciling Adaptation, Mitigation and Sustainable Development for Cities Start and duration of the model Start Date of simulation (dd.mm.yyyy) Summer: 07.08.2010 Start time (hh:mm:ss) 04:00:00 Total simulation time (h) 44 Output settings Receptors and buildings (min) 10 (output interval for files) Initial meteorological conditions Wind speed measured in 10 m height (m/s) 4.0 m/s Wind direction (deg) 315 º (0º = from North …180º =from South…) Initial temperature of atmosphere (°K) 293.44 ºK (20.29 ºC) Relative humidity in 2 m height (%) 63.3 78The weather data used to initiate the models were provided by the meteorological station of Deusto, which is located in the northern part of the city at 3 m above sea level (latitude 43.28N, longitude 2.93W)
- 79. Reconciling Adaptation, Mitigation and Sustainable Development for Cities The study was conducted setting these local data • Materials: Facades: B2 - Brick wall (burned) Roofs : R1 - Roofing: tile • Soill: Street : Asphalt/Brick red stones Green areas: Loamy • Vegetation: Presence grass 50 cm average dense: 30% up to the total surface; Trees: Tree 5m; 1/3 without leaves, Platanus 5m , Platanus 10m Hypothesis 79
- 80. Scenarios 80
- 81. Reconciling Adaptation, Mitigation and Sustainable Development for Cities S0 Initial S1 Pedestrian S2 Grass S3 Grass + trees S4 Green roofs S5 Grass + green roofs S6 Grass + trees + green roofs
- 83. Scenarios of the Compact Lowrise urban areas Reconciling Adaptation, Mitigation and Sustainable Development for Cities 83S1 – Initial S2 – Grass S3 – Grass and Trees S4 – Green roofs S5 – Grass and Green roofs S6 – Grass, Trees and Green roofs
- 85. Scenarios of the Open set Highrise urban areas Reconciling Adaptation, Mitigation and Sustainable Development for Cities 85S0 and S1 Initial S2 – Grass S3 – Grass and Trees S4 Green roofs S5 – Grass and Green roofs S6 – Grass, Trees and Green roofs
- 87. Results of the Open set High-rise urban areas Reconciling Adaptation, Mitigation and Sustainable Development for Cities 87S1 – Initial S2 – Grass S3 – Grass and Trees S4 – Green roofs S5 – Grass and Green roofs S6 – Grass, Trees and Green roofs
- 88. 5 Others climate aspects Summer school SEniC 2015
- 89. Luca Italy Gabriele Italy Charles Sweden Liu YuTing 刘昱婷 China Xi Jia 席加 China Wang Kun 王琨 China Stergios Greece Zhou LiWei 周丽薇 China Li FangBing 李芳兵 China Li WeiZhe 李玮哲 China Yuan Chen 袁宸 China Zhang ZhengYang 张正洋 China Silvia Italy Xiang Can 向璨 China Li BoWen 李博文 China Shimantika Bangladesh Wang YuYuan 王钰圆 China
- 90. Shanghai, Zhoukanghang Six high rise residential buildings Height 50 m Volume 2400 m³/building Total volume 14400 m³ Site
- 91. Climate Climate
- 93. Temperature & Humidity Jun Jul Aug Average Temp(℃) 23 27.5 27.7 Maximum Temp(℃) 31 35.5 38 Average RH(%) 83.54 81.21 77.90 Dec Jan Feb Average Temp(℃) 6.5 4.3 6.1 Minimum Temp(℃) -4.3 -8.7 -7.5 Average RH(%) 74.54 74.44 74.86 In summer, there are 48 days in which maximum temp is over 30 ℃. It’s comfortable in Jun and needs cooling in Jul and Aug. In winter, there are 60 days in which minimum temp is below 10 ℃. We need heating in all these three months. Climate
- 94. Climate Winter Passive Strategies Summer Passive Strategies Passive solar heating Thermal mass Shading Natural ventilation
- 95. Passive solar heating Key components: windows size, windows inclination, materials Thermal mass Key components: construction, materials 0% 100% 0% 100% Jan Dec Year Jan Dec Year Winter Passive Strategies
- 96. Shading Key components: windows size & orientation and inclination, shading devices Summer Passive Strategies Natural Ventilation Key components: windows size, windows distribution/orientation 0% 100% Jan Dec Year 0% 100% Jan Dec Year
- 97. Wind
- 98. Wind Speed & Direction 0 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 9 10 11 12 Wind Speed Avg Daily Winter Summer Wind Direction Northwest Southeast & East Range of Speed 10-40km/h 5-30km/h Average Wind Speed 6.5m/s 6m/s Winter Summer Climate
- 99. Solar Radiation
- 100. Climate Radiation Angle Apr May Jun July Aug Sept Ranging Time (h) 10--16 10--16 9--17 7--18 7--18 9--17 Bearing Angle (°) E67--W82 E80--W94 E95-- W105 E105-- W110 E95-- W100 E68--W81 Altitude Angle (°) 55--68-- 32 58--75-- 35 48--81-- 24 19--75-- 12 17--68--6 38--53-- 12 0120 120 10 90 0120 120 10 90
- 101. Jun Jul Aug Sep Time we need shading (h) 9:00-17:00 7:00-19:00 9:00-17:00 11:00-15:00 Climate Sunlight Time - Shading
- 102. Air Pollution
- 103. Air Pollution Wind from north-west and south-east bring more pollutant
- 104. Solar Analysis
- 105. Building 1-6 and 7-9Solar Analysis
- 106. Model Created in Rhinoceros Environment Solar Dynamic Simulation Conducted Using DIVA for Rhino in Isolated & Context Scenarios MethodologySolar Analysis
- 107. Roof : F G H Facade: A B C D E Roof Facade Solar Radiation 0 200 400 600 800 1000 1200 1 382 763 1144 1525 1906 2287 2668 3049 3430 3811 4192 4573 4954 5335 5716 6097 6478 6859 7240 7621 8002 8383 kWh/m²yr Hours 0 100 200 300 400 500 600 700 1 366 731 1096 1461 1826 2191 2556 2921 3286 3651 4016 4381 4746 5111 5476 5841 6206 6571 6936 7301 7666 8031 8396 kWh/m²yr Hours
- 108. Decrease of Radiation Due to Surroundings kWh/ m2 Building 1 Building 2 Building 3 Building 4 Building 5 Building 6 Isolated Context Isolated Context Isolated Context Isolated Context Isolated Context Isolated Context Direct 27.3 23.3 27.6 23.7 27.6 27.1 26.7 25.0 27.5 26.2 27.6 27.1 Global 82.1 60.8 82.2 62.6 81.4 79.0 81.3 68.4 81.7 74.2 82.1 71.2 Diffuse 54.8 37.5 54.6 38.9 53.8 52.0 54.6 43.4 54.1 47.9 54.4 44.1 Direct 14.5% 14.1% 1.8% 6.4% 4.8% 1.8% Global 25.9% 23.9% 2.9% 15.9% 9.2% 13.3% Diffuse 31.6% 28.8% 3.4% 20.6% 11.4% 19.0% The worst one The best one Solar Radiation
- 109. Radiation Map and Overshadowing EffectSolar Radiation Percentage Decrease Facade B ab=0 Roof 708 -1389 kWh/m2yr Facade 73-281 kWh/m2yr Height(m) Width(m) 24 m Direct Component
- 110. Solar Radiation Roof 708 -1389 kWh/m2yr Facade 195-805 kWh/m2yr Height(m) Width(m) 32 m Radiation Map and Overshadowing Effect Percentage Decrease Facade B ab=1 Global Component
- 111. Optimized Orientation New layout Optimal orientation from solar analysis on Ecotect
- 112. Solar System 28° • System: photovoltaic solar shading louvre (imput from group B – Professor Dai) • Optimal inclination for the entire year: 28° (Data Source: Optimal tilt-angles for solar collectors used in China Runsheng Tang, Tong Wu) • Solar analysis on DIVA for calculating the optimal distance between the louvres: 75 cm
- 113. Solar System 24 m Current Design New Design
- 114. Wind Flow
- 115. • Wind speed less than 5m/s Below 1.5m • In summer the pressure difference of front and back side of the building has to be about 2 Pa to ensure enough natural ventilation • In winter the pressure difference of front and back side of the building has to be less than 5 Pa (except for the first row of the buildings towards wind) (Data Source: Green Building Evaluation Criteria & Ecological Residential Building Technology Assessment Manual of China) Wind Flow Simulation Assessment Standards
- 116. SUMMER (Wind Direction: SE) 3m/s 3m/s Wind Speed Close to 0 m/s Pressure Diff. 0-0.5 Pa
- 117. WINTER (Wind Direction: N) Wind Speed Close to 0 m/s Pressure Diff. 0-0.5Pa 3m/s 3m/s
- 119. SUMMER SE, 3 m/s Wind Flow Simulation
- 120. Green Strategies
- 121. Results • Green integrated in the facade of the building • Green roof Goals – Reduces the overheating effects, resulting in the reduction of the heating load – Filter the pollution from the air – Reduce local air and ground temperature – Improve of the environmental comfort of the construction site
- 122. Internal Layout
- 123. Mean Daylight Factor 2,47% Daylight Autonomy 56% Daylight Analysis
- 124. Modified Layout Layout Improvements Original Layout
- 125. We want to thank you all for the past two amazing weeks together!!!
- 127. NTNU#SmartCities http://smartsustainablecities.org/ Gabriele Lobaccaro NTNU - Norwegian of Science and Technology gabriele.lobaccaro@ntnu.no