- Email: [email protected]
Measurement of the Influence of Roof Pitch to Increasing Wind Power Density
Available online at www.sciencedirect.com
ScienceDirect Energy Procedia 65 (2015) 42 – 47
Conference and Exhibition Indonesia - New, Renewable Energy and Energy Concervation, [The 3 rd Indo EBTKE ConEx 2014]
Measurement of the Influence of Roof Pitch to Increasing Wind Power Density Dany Perwita Saria,* a
Research Centre for Biomaterials, Indonesian Institute of Sciences (LIPI), Jl. Raya Bogor km.46, Cibinong, Bogor 16911, Indonesia
Abstract The wind flows on the rooftop house in Semarang, Indonesia past were examined in a Computational Fluid Dynamics (CFD) analysis and indicate best performance for wind energy power density. The rooftop pitches of house can have huge impact on increasing wind power density. This paper deals with the study to increase wind power density of micro-wind turbine located on the rooftop house by design the roof pitch. CFD was performed to evaluate the performance of wind flow around the roof pitch of housing at different angle (20o, 30o, 40o and 50o) based on wind climate data analysis. The results showed that a pitched roof of 30o has the best wind potential density than another for same base house model height. © Authors. Publishedby by Elsevier Elsevier Ltd. ©2015 2015The D.P. Sari. Published 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 EBTKE ConEx 2014 Peer-review under responsibility of the Scientific Committee of EBTKE ConEx 2014 Keywords: CFD; roof pitch; wind flow; wind power density
Nomenclature U Uref Z Zref
wind velocity (m . s-1) wind velocity reference (m . s-1) the gradient height (m) the gradient height reference (m)
M atsl yr α
mega (106) above the sea level years power law exponent
* Corresponding author. Tel.: +62 813 2569 3808; fax: +62 21 8791 4511. E-mail address: [email protected]
1876-6102 © 2015 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 EBTKE ConEx 2014 doi:10.1016/j.egypro.2015.01.029
43
Dany Perwita Sari / Energy Procedia 65 (2015) 42 – 47
1. Introduction Indonesia has population of about 2450 M which grew by amount 1.5 % annually between 2000 and 2010 [1]. With the growing population, energy demand will surge in the future. Indonesia is endowed with conventional fossil fuel resources such as coal, oil, and gas, which dominated the energy portfolio of the country for decades. In 2011, more than 95 % of the national energy mix was dominated by fossil fuels and only 4 % for new renewable energy [2]. The heavy reliance on fossil fuel based energy threatens Indonesia’s energy security given the exhaustible nature of fossil fuels. According to Ministry of Finance of the Republic of Indonesia, Indonesia’s energy potential of oil and natural gas will be depleted in about 10 yr to 35 yr and coal in about 65 yr [3]. Recently, The Government of Indonesia commit to increase the share of new and renewable energy source up to 23 % by 2025 [4]. Main use of renewable energy is in electricity and transportation sectors. Several countries include Indonesia, close on 50 % of the energy that used is for servicing buildings [5]. The country needs to identify available energy resources such as wind energy to fulfill demand increasement. The objective of the research was to increase affordability and accessibility wind energy as well as energy saving. Recent study showed that roof geometry used in houses was significantly influenced wind velocity [6,7]. Comparative resulted from earlier research [8] showed that Semarang, Indonesia, has potential harvesting wind energy with roof mounted-micro wind turbine. Recent study [8] showed that Semarang wind power density is stable. Hip roof [8] had better performance than gable roof to increase wind velocity. This result led to estimate wind velocity on hip roof with roof pitches variations. Therefore, wind conditions in urban location are very complex and the adaptability of wind turbines [9]. The study elucidated that the investigation resulted to wind power density in coastal housing with different roof pitches (20o, 30o, 40o and 50o) at Semarang, Indonesia. Table 1. Roughness classification with power law α values [10] Wind power class
Zo (m)
α
G (m)
Wind power density . (a) (W m-2)
Mean speed range . (b) m s-1 (mph)
Sea
0.0002
0.09
213
< 100
< 4.4 (9.8)
Smooth
0.005
0.125
213
100-150
4.4 (9.8)/5.1 (11.5)
OC (open area)
0.03
0.15
274
150-200
5.1 (11.5)/5.6 (12.5)
Roughly open
0.1
0.2
274
200-250
5.6 (12.5)/6.0 (13.4)
Suburban (rough)
0.25
0.25
366
250-300
6.0 (13.4)/6.4 (14.3)
Very rough
0.5
0.3
366
300-400
6.4 (14.3)/7.0 (15.7)
Urban (closed)
1
0.33
366
> 400
> 7.0 (15.7)
2. Material and method To assess the best design of roof pitches with CFD simulations as a wind energy resource assessment tool, wind power density in Semarang city was analysis by means to predict the wind classes. Wind class is important to create the wind profile for CFD simulation. This data was used as the inlet velocity profile at the outer boundary layer of the CFD model in Fluent [10], to allow for comparison of the roof pitches, the models were analysis in the same inlet profile.
2.1. Determining Semarang wind power density and wind power classes Areas are often described by their wind class ranking. Therefore there is no wind class in Indonesia, using wind classes from roughness classification that already available [11]. Table 1 described the range wind power density and associated classes at meters height above ground. CFD analysis of two separate programs, Gambit and Fluent [10,12]. Gambit is used to construct the flow geometry, along with the mesh for solving the equations of motion and continuity at fixed points. Fluent 6.2.16 is the program which actually solves the equations for the geometries constructed using Gambit. The micro wind turbine will be installed in the north part of Semarang city which
44
Dany Perwita Sari / Energy Procedia 65 (2015) 42 – 47
elevation is 25 m atsl [13]. Wind power density and wind speed will change with every meteorological data. Long term mean wind speed at 10 m is 7 km . h-1 to 9 km . h-1 [14]. With the highest wind speed at January, 18 km . h-1 or 5 m . s-1. After calculate the wind power density and refer to table 1, Semarang wind class 2 (smooth) at 10 m has wind power density value 145.66 W . m-2. LAPAN, National Institute of Aeronautics and Space of Indonesia, categorized this wind power density is excellent wind resources [15]. 2.2. CFD simulation 2.2.1. Inlet wind profile The wind speed above the roof pitches were analyzed using CFD. The velocity profile at the inlet boundary of the CFD simulation should be accurately modeled to provide valid results [9]. The velocity profile at the inlet boundary using Semarang city’s forecasting within period five years (from 2008 to 2012) [10]. Wind class calculates form the wind power density. Wind direction evaluation at a height of 10 m above ground level was found that the highest wind power potential based on meteorological data is on north wind (5 m . s-1). For the roughness classification is using ASCE (1999) with smooth. Wind profile for CFD analysis in Semarang can be expressed on Figure 2. Power law which is shown in Equation (1) is used to model the wind profile at the inlet of CFD. (1) Where U is wind velocity (m . s-1), Uref is wind velocity reference (m . s-1), Z is the gradient height (m), Zref is the gradient height reference (m), and α is power law exponent. Figure 1 shows the wind velocity profile in Semarang, Indonesia. The wind speed profile measured in the CFD using the power law of an exponent of 0.125. The mean wind speed was 5 m . s-1 at 10 m above the sea level.
Wind Velocity (m . s-1) Fig. 1. Wind profile in Semarang, Indonesia
2.2.2. Modelled parameters CFD was used to simulate wind flow above gable roof which represents the basic shapes of traditional coastal housing in Semarang. This modeled was assumed as residential houses 45 m2 (4 m × 9 m). Simulations were undertaken with roof pitch’s angle 20o, 30o, 40o, 50o (Fig. 2). The selected roof pitches are commonly used in the houses and low-rise buildings with hip roof in Semarang, Indonesia. In consideration of the symmetric conditions of the building models, the height of the building is 6 m.
Dany Perwita Sari / Energy Procedia 65 (2015) 42 – 47
50o 40o 30o 20o
wind direction
Fig. 2. (Left to right): The roof pitch’s angle 20o, 30o, 40o, 50o
3. Result and discussion CFD simulation was implemented which is known to make use of the k-ε model and finite element technique. For each roof pitches, Semarang’s wind profile is applied. Specifying the optimum power electricity of roof pitches depends on the wind velocity. CFD is used for predicting wind velocity and wind flow above the roof profiles. Fig. 3a-d showed that the numerical resulted to velocity (contours and vectors) distributions around building models with different pitch angles. Fig.3a shows the average wind velocity result for roof pitch’s angle 20o. The simulation elucidated that wind velocity stable and increase in the height 1m above roof surface. From the simulation showed that there are no specific differences wind velocities before and after passing roof pitch’s at angle 40o (Fig. 3c). Roof pitch’s angle 50o position result (Fig. 3d) recorded similar with gable roof in 40o position result. The maximum average wind velocity occurs for pitched roof with inclination 30o (Fig. 3c). There is no significant effect on the increasing wind velocity for pitched roof with 20 o, 40o and 50o. It is observed that the pitched roof has a large influence on the wind velocity. The wind velocity is the highest nearest to the separation point and in the corner edge.
Fig. 3a. Average wind velocity contour for roof pitch’s angle 20o
45
46
Dany Perwita Sari / Energy Procedia 65 (2015) 42 – 47
Fig. 3b. Average wind velocity contour for roof pitch’s angle 30o
Fig. 3c. Average wind velocity contour for roof pitch’s angle 40o
Fig. 3d. Average wind velocity contour for roof pitch’s angle 50o
4. Conclusion Semarang has great potential for wind energy, located in coastal area where wind is abundant. Wind speed between (2 – 5) m . s-1 was suitable wind turbine to develop in Semarang are micro-wind turbine. Four gable roofed house model of 20o, 30 o, 40o and 50o roof pitch, have been tested in CFD simulation to investigate wind velocity over gable roofs. CFD analysis based on the finite element method was used to predict wind velocity contours in the roof pitches. The wind velocity measured on the gable roofs were compared with similar geometry. The model was created in three-dimensional model (Fig.2). Convergence and stability of the solution were verified at a certain number of finite elements and iterations. The results showed that a pitched roof of 30o has the best wind potential density than another for same base house model height. Compared with other roof, the worst wind velocity was 20o roof pitch. The wind velocity
Dany Perwita Sari / Energy Procedia 65 (2015) 42 – 47
contour has nearly the same trend between 40o and 50o roof pitches. It is recommended to use 30o roof pitch in Semarang City for optimizing wind energy using micro wind turbine, which are defined as wind turbines with capacity less than 2.5 kW. Acknowledgements The author would particularly like to thank Meteorological Department (BMKG) Semarang City for the climate data. The support from Research Center for Biomaterials, Indonesian Institute of Sciences (LIPI) is also appreciated. References [1] Pillai GM, Asian and Pacific Centre for Transfer of Technology (APCTT) of the United Nations Economic and Social Commission for Asia and the Pasific (ESCAP), New Delhi, India; 2014. [2] Hasrul, New energy and renewable energy, New and Renewable Energy Policies. [3] Directorate General of Debt Management, Ministry of Finance of the Republic of Indonesia (MoF), Wind hybrid power generation, Project document, Market development initiatives. [4] Directorate General of New Renewable Energy and Energy Conservation. Ministry of Energy and Mineral Resources. Renewable energy development; 2012. [5] Woolf J. Renew: a renewable energy design tool for architects. Renewable Energy 2003;28:1555-1561. [6] Xu YL, Reardon GF. Variations of wind pressure on hip roofs with roof pitch. Journal of Wind Engineering 1998;73: 267-284. [7] Guirguis NM, Abd El-Aziz AA, Nassief MM. Study of wind effects on different buildings of pitched roofs. Desalination 2007;209:190-198. [8] Sari DP, Kusumaningrum WB. A technical review of building integrated wind turbine system and sample simulation model in Central Java, Indonesia. In : Praptiningsih GA, Anggi N, Agus SY, Andi S, editors. Conf. and Exhibition Indonesia Renewable Energy & Energy Conservation 2013. Energy Procedia 2014;47:29-36. [9] Tabrizi AB, Whale J, Lyons T, Urmee T. Performance and safety of rooftop wind turbines: use of CFD to gain insight into inflow condition. Renewable Energy 2013;1-10. Article in press. [10] Fluent 6.2.16. CD-ROOM. Fluent Inc. 2012. [11] Ted S, Charalambos CB, Wind effects on buildings and design of wind-sensitive structure. Italy: Springer Wien New York; 2007. p. 10. [12] Gambit 2.2.30. CD-ROOM. Hummingbird. 2012. [13] Bakti LM, Kajian sebaran potensi rob Kota Semarang dan usulan pengembangannya,[The study of Semarang “rob” potential distribution and the suggestion for the development [Thesis] Diponegoro University. 2010. [Bahasa Indonesia] [14] Indonesian Agency for Meteorological, Climatological and Geophysics (BMKG). Data kecepatan arah angin, intensitas dan lamanya penyinaran matahari, temperature, kelembaban tahun 2008-2012. [Five years (2008-2012) data for wind speed, wind direction, intensity, temperature and humidity]. 2013. [Bahasa Indonesia] [15] Martosaputro S, Wind energy potential and development in Indonesia. The 2nd Clean Energy Power Asia, Denpasar-Bali, Indonesia; 2012.
47
ScienceDirect Energy Procedia 65 (2015) 42 – 47
Conference and Exhibition Indonesia - New, Renewable Energy and Energy Concervation, [The 3 rd Indo EBTKE ConEx 2014]
Measurement of the Influence of Roof Pitch to Increasing Wind Power Density Dany Perwita Saria,* a
Research Centre for Biomaterials, Indonesian Institute of Sciences (LIPI), Jl. Raya Bogor km.46, Cibinong, Bogor 16911, Indonesia
Abstract The wind flows on the rooftop house in Semarang, Indonesia past were examined in a Computational Fluid Dynamics (CFD) analysis and indicate best performance for wind energy power density. The rooftop pitches of house can have huge impact on increasing wind power density. This paper deals with the study to increase wind power density of micro-wind turbine located on the rooftop house by design the roof pitch. CFD was performed to evaluate the performance of wind flow around the roof pitch of housing at different angle (20o, 30o, 40o and 50o) based on wind climate data analysis. The results showed that a pitched roof of 30o has the best wind potential density than another for same base house model height. © Authors. Publishedby by Elsevier Elsevier Ltd. ©2015 2015The D.P. Sari. Published 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 EBTKE ConEx 2014 Peer-review under responsibility of the Scientific Committee of EBTKE ConEx 2014 Keywords: CFD; roof pitch; wind flow; wind power density
Nomenclature U Uref Z Zref
wind velocity (m . s-1) wind velocity reference (m . s-1) the gradient height (m) the gradient height reference (m)
M atsl yr α
mega (106) above the sea level years power law exponent
* Corresponding author. Tel.: +62 813 2569 3808; fax: +62 21 8791 4511. E-mail address: [email protected]
1876-6102 © 2015 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 EBTKE ConEx 2014 doi:10.1016/j.egypro.2015.01.029
43
Dany Perwita Sari / Energy Procedia 65 (2015) 42 – 47
1. Introduction Indonesia has population of about 2450 M which grew by amount 1.5 % annually between 2000 and 2010 [1]. With the growing population, energy demand will surge in the future. Indonesia is endowed with conventional fossil fuel resources such as coal, oil, and gas, which dominated the energy portfolio of the country for decades. In 2011, more than 95 % of the national energy mix was dominated by fossil fuels and only 4 % for new renewable energy [2]. The heavy reliance on fossil fuel based energy threatens Indonesia’s energy security given the exhaustible nature of fossil fuels. According to Ministry of Finance of the Republic of Indonesia, Indonesia’s energy potential of oil and natural gas will be depleted in about 10 yr to 35 yr and coal in about 65 yr [3]. Recently, The Government of Indonesia commit to increase the share of new and renewable energy source up to 23 % by 2025 [4]. Main use of renewable energy is in electricity and transportation sectors. Several countries include Indonesia, close on 50 % of the energy that used is for servicing buildings [5]. The country needs to identify available energy resources such as wind energy to fulfill demand increasement. The objective of the research was to increase affordability and accessibility wind energy as well as energy saving. Recent study showed that roof geometry used in houses was significantly influenced wind velocity [6,7]. Comparative resulted from earlier research [8] showed that Semarang, Indonesia, has potential harvesting wind energy with roof mounted-micro wind turbine. Recent study [8] showed that Semarang wind power density is stable. Hip roof [8] had better performance than gable roof to increase wind velocity. This result led to estimate wind velocity on hip roof with roof pitches variations. Therefore, wind conditions in urban location are very complex and the adaptability of wind turbines [9]. The study elucidated that the investigation resulted to wind power density in coastal housing with different roof pitches (20o, 30o, 40o and 50o) at Semarang, Indonesia. Table 1. Roughness classification with power law α values [10] Wind power class
Zo (m)
α
G (m)
Wind power density . (a) (W m-2)
Mean speed range . (b) m s-1 (mph)
Sea
0.0002
0.09
213
< 100
< 4.4 (9.8)
Smooth
0.005
0.125
213
100-150
4.4 (9.8)/5.1 (11.5)
OC (open area)
0.03
0.15
274
150-200
5.1 (11.5)/5.6 (12.5)
Roughly open
0.1
0.2
274
200-250
5.6 (12.5)/6.0 (13.4)
Suburban (rough)
0.25
0.25
366
250-300
6.0 (13.4)/6.4 (14.3)
Very rough
0.5
0.3
366
300-400
6.4 (14.3)/7.0 (15.7)
Urban (closed)
1
0.33
366
> 400
> 7.0 (15.7)
2. Material and method To assess the best design of roof pitches with CFD simulations as a wind energy resource assessment tool, wind power density in Semarang city was analysis by means to predict the wind classes. Wind class is important to create the wind profile for CFD simulation. This data was used as the inlet velocity profile at the outer boundary layer of the CFD model in Fluent [10], to allow for comparison of the roof pitches, the models were analysis in the same inlet profile.
2.1. Determining Semarang wind power density and wind power classes Areas are often described by their wind class ranking. Therefore there is no wind class in Indonesia, using wind classes from roughness classification that already available [11]. Table 1 described the range wind power density and associated classes at meters height above ground. CFD analysis of two separate programs, Gambit and Fluent [10,12]. Gambit is used to construct the flow geometry, along with the mesh for solving the equations of motion and continuity at fixed points. Fluent 6.2.16 is the program which actually solves the equations for the geometries constructed using Gambit. The micro wind turbine will be installed in the north part of Semarang city which
44
Dany Perwita Sari / Energy Procedia 65 (2015) 42 – 47
elevation is 25 m atsl [13]. Wind power density and wind speed will change with every meteorological data. Long term mean wind speed at 10 m is 7 km . h-1 to 9 km . h-1 [14]. With the highest wind speed at January, 18 km . h-1 or 5 m . s-1. After calculate the wind power density and refer to table 1, Semarang wind class 2 (smooth) at 10 m has wind power density value 145.66 W . m-2. LAPAN, National Institute of Aeronautics and Space of Indonesia, categorized this wind power density is excellent wind resources [15]. 2.2. CFD simulation 2.2.1. Inlet wind profile The wind speed above the roof pitches were analyzed using CFD. The velocity profile at the inlet boundary of the CFD simulation should be accurately modeled to provide valid results [9]. The velocity profile at the inlet boundary using Semarang city’s forecasting within period five years (from 2008 to 2012) [10]. Wind class calculates form the wind power density. Wind direction evaluation at a height of 10 m above ground level was found that the highest wind power potential based on meteorological data is on north wind (5 m . s-1). For the roughness classification is using ASCE (1999) with smooth. Wind profile for CFD analysis in Semarang can be expressed on Figure 2. Power law which is shown in Equation (1) is used to model the wind profile at the inlet of CFD. (1) Where U is wind velocity (m . s-1), Uref is wind velocity reference (m . s-1), Z is the gradient height (m), Zref is the gradient height reference (m), and α is power law exponent. Figure 1 shows the wind velocity profile in Semarang, Indonesia. The wind speed profile measured in the CFD using the power law of an exponent of 0.125. The mean wind speed was 5 m . s-1 at 10 m above the sea level.
Wind Velocity (m . s-1) Fig. 1. Wind profile in Semarang, Indonesia
2.2.2. Modelled parameters CFD was used to simulate wind flow above gable roof which represents the basic shapes of traditional coastal housing in Semarang. This modeled was assumed as residential houses 45 m2 (4 m × 9 m). Simulations were undertaken with roof pitch’s angle 20o, 30o, 40o, 50o (Fig. 2). The selected roof pitches are commonly used in the houses and low-rise buildings with hip roof in Semarang, Indonesia. In consideration of the symmetric conditions of the building models, the height of the building is 6 m.
Dany Perwita Sari / Energy Procedia 65 (2015) 42 – 47
50o 40o 30o 20o
wind direction
Fig. 2. (Left to right): The roof pitch’s angle 20o, 30o, 40o, 50o
3. Result and discussion CFD simulation was implemented which is known to make use of the k-ε model and finite element technique. For each roof pitches, Semarang’s wind profile is applied. Specifying the optimum power electricity of roof pitches depends on the wind velocity. CFD is used for predicting wind velocity and wind flow above the roof profiles. Fig. 3a-d showed that the numerical resulted to velocity (contours and vectors) distributions around building models with different pitch angles. Fig.3a shows the average wind velocity result for roof pitch’s angle 20o. The simulation elucidated that wind velocity stable and increase in the height 1m above roof surface. From the simulation showed that there are no specific differences wind velocities before and after passing roof pitch’s at angle 40o (Fig. 3c). Roof pitch’s angle 50o position result (Fig. 3d) recorded similar with gable roof in 40o position result. The maximum average wind velocity occurs for pitched roof with inclination 30o (Fig. 3c). There is no significant effect on the increasing wind velocity for pitched roof with 20 o, 40o and 50o. It is observed that the pitched roof has a large influence on the wind velocity. The wind velocity is the highest nearest to the separation point and in the corner edge.
Fig. 3a. Average wind velocity contour for roof pitch’s angle 20o
45
46
Dany Perwita Sari / Energy Procedia 65 (2015) 42 – 47
Fig. 3b. Average wind velocity contour for roof pitch’s angle 30o
Fig. 3c. Average wind velocity contour for roof pitch’s angle 40o
Fig. 3d. Average wind velocity contour for roof pitch’s angle 50o
4. Conclusion Semarang has great potential for wind energy, located in coastal area where wind is abundant. Wind speed between (2 – 5) m . s-1 was suitable wind turbine to develop in Semarang are micro-wind turbine. Four gable roofed house model of 20o, 30 o, 40o and 50o roof pitch, have been tested in CFD simulation to investigate wind velocity over gable roofs. CFD analysis based on the finite element method was used to predict wind velocity contours in the roof pitches. The wind velocity measured on the gable roofs were compared with similar geometry. The model was created in three-dimensional model (Fig.2). Convergence and stability of the solution were verified at a certain number of finite elements and iterations. The results showed that a pitched roof of 30o has the best wind potential density than another for same base house model height. Compared with other roof, the worst wind velocity was 20o roof pitch. The wind velocity
Dany Perwita Sari / Energy Procedia 65 (2015) 42 – 47
contour has nearly the same trend between 40o and 50o roof pitches. It is recommended to use 30o roof pitch in Semarang City for optimizing wind energy using micro wind turbine, which are defined as wind turbines with capacity less than 2.5 kW. Acknowledgements The author would particularly like to thank Meteorological Department (BMKG) Semarang City for the climate data. The support from Research Center for Biomaterials, Indonesian Institute of Sciences (LIPI) is also appreciated. References [1] Pillai GM, Asian and Pacific Centre for Transfer of Technology (APCTT) of the United Nations Economic and Social Commission for Asia and the Pasific (ESCAP), New Delhi, India; 2014. [2] Hasrul, New energy and renewable energy, New and Renewable Energy Policies. [3] Directorate General of Debt Management, Ministry of Finance of the Republic of Indonesia (MoF), Wind hybrid power generation, Project document, Market development initiatives. [4] Directorate General of New Renewable Energy and Energy Conservation. Ministry of Energy and Mineral Resources. Renewable energy development; 2012. [5] Woolf J. Renew: a renewable energy design tool for architects. Renewable Energy 2003;28:1555-1561. [6] Xu YL, Reardon GF. Variations of wind pressure on hip roofs with roof pitch. Journal of Wind Engineering 1998;73: 267-284. [7] Guirguis NM, Abd El-Aziz AA, Nassief MM. Study of wind effects on different buildings of pitched roofs. Desalination 2007;209:190-198. [8] Sari DP, Kusumaningrum WB. A technical review of building integrated wind turbine system and sample simulation model in Central Java, Indonesia. In : Praptiningsih GA, Anggi N, Agus SY, Andi S, editors. Conf. and Exhibition Indonesia Renewable Energy & Energy Conservation 2013. Energy Procedia 2014;47:29-36. [9] Tabrizi AB, Whale J, Lyons T, Urmee T. Performance and safety of rooftop wind turbines: use of CFD to gain insight into inflow condition. Renewable Energy 2013;1-10. Article in press. [10] Fluent 6.2.16. CD-ROOM. Fluent Inc. 2012. [11] Ted S, Charalambos CB, Wind effects on buildings and design of wind-sensitive structure. Italy: Springer Wien New York; 2007. p. 10. [12] Gambit 2.2.30. CD-ROOM. Hummingbird. 2012. [13] Bakti LM, Kajian sebaran potensi rob Kota Semarang dan usulan pengembangannya,[The study of Semarang “rob” potential distribution and the suggestion for the development [Thesis] Diponegoro University. 2010. [Bahasa Indonesia] [14] Indonesian Agency for Meteorological, Climatological and Geophysics (BMKG). Data kecepatan arah angin, intensitas dan lamanya penyinaran matahari, temperature, kelembaban tahun 2008-2012. [Five years (2008-2012) data for wind speed, wind direction, intensity, temperature and humidity]. 2013. [Bahasa Indonesia] [15] Martosaputro S, Wind energy potential and development in Indonesia. The 2nd Clean Energy Power Asia, Denpasar-Bali, Indonesia; 2012.
47