Impact of Building Layouts on Wind Turbine Power Output in the Built Environment: A Case Study of Tsu City

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1 Journal of the Japan Institute of Energy, 94, (2014) 315 Special Articles: Sustainable Energy Technologies 特集 : 持続可能なエネルギー技術 Impact of Building Layouts on Wind Turbine Power Output in the Built Environment: A Case Study of Tsu City Akira NISHIMURA *1, Takuya ITO *1, Masanobu KAKITA *1, Junsuke MURATA *1, Toshitake ANDO *1, Yasunari KAMADA *1, Masafumi HIROTA *1 and Mohan KOLHE *2 (Received July 26, 2013) In city planning, it is important to consider the future growth of renewable energy systems in the built environment. Wind speed analysis in the built environment is very important for analysing the wind turbine performance installed in the built environment. In this work, building topologies / layouts in Tsu city are considered for investing the wind speed distributions and directions. Wind speed profile in the built environment are developed by using CFD-ACE+. This work focusses on the analysis of the wind speed directions and distribution characteristics for finding out the proper location of the wind turbines in the built environment. The wind speed profiles and their directions and wind turbine characteristics are always changing; therefore a model has to put forward for estimation of the wind turbine power outputs. This work is useful for designing the building layouts in such a way to make the nozzle of the wind by using wind directions and then finding out the proper location of the wind turbine in the built environment. In this work, building layouts like nozzle is proposed and investigated to obtain the contracted flow by blowing wind through the buildings. Key Words Wind turbine, Wind speed profiles, Wind energy estimation, Energy resource assessment, Smart city 都市計画において, ビル設置環境における再生可能エネルギーシステムの将来的な発展を考えることは重要である ビル設置環境における風速分布解析は, ビル設置環境に設置した風力タービンの性能を分析する上でとても重要である 本研究では, 津市に設置を想定したビルの幾何形状や配置について, 風風速分布 方向データを用いて考慮した ビル設置環境での風速分布は CFD-ACE+ を用いて明らかにした 本研究では, ビル設置環境における風力タービンの適切な設置方法を見出すため, 風速方向 分布特性の解析に注力した 風速分布 風向, 風力タービン特性は常に変化している それゆえ, 本モデルは, 風力タービン出力評価方法を提案しなければならない 本研究は, 風向を利用して風の通過するノズルを作るようにビル配置を設計することに有益である そしてビル設置環境における風力タービンの適した設置方法を見出す 本研究では, ノズル状ビル配置を提案し, ビル間を吹き抜ける風によって縮流を得ることについて検討する キーワード風力タービン, 風速分布, 風力エネルギー概算, エネルギー資源評価, スマートシティ 1. Introduction In smart city planning, it is very important to consider the future growth of building integrated environment friendly energy systems. Energy output from the intermittent renewable energy sources in the built environment depends on the availability of natural resources (e.g. wind speed, solar radiation etc) in the urban *1 Division of Mechanical Engineering, Graduate School of Engineering, Mie University 1577 Kurimamachiya-cho, Tsu-shi, Mie , Japan; * 2 Faculty of Engineering & Science, University of Agder Grimstad, NO-4879, Norway area. Wind speed analysis in the built environment is very important not only for finding the mechanical stress on the building structures, but also for analysing the wind turbine performance in the urban area. In developing environment friendly smart cities, it is needed to analyse the intelligent integration of intermittent renewable energy sources in the built environment. A smart city development and demonstration with integrated renewable energy system has to harmonize with expansion of the power system infrastructure, the information and communication infrastructure and integration of new monitoring and

2 316 J. Jpn. Inst. Energy, Vol. 93, No. 4, 2014 control applications 1). This study intends to propose the smart city which utilizes renewable energy sources as much as possible. For example, the city consists of many buildings and the buildings are thought to be an obstacle to natural wind flow. If the wind blowing through building is controlled, this wind can be utilized for power generation of wind turbine. This study has a plan to investigate the larger scale power generation by wind turbine and photovoltaics integrated with building in the near future. Hence, the present paper treats the horizontal axis wind turbine as a target for integrating with building since the output of commercial horizontal axis wind turbine is larger compared to the vertical axis wind turbine generally. The wind speed profiles on the tall building rooftops are presented in reference 2) for analysing the usage of roof wind energy, but it has not considered the building topologies of the city. Numerical simulation on wind flow around building carried out by turbulent model such as standard k - ε, LES and DNS was reported 3) ~ 9). In addition, wind tunnel experiment on wind flow around building was also reported 10) ~ 13). Although these reports investigated the wind velocity profile around various building models and various conditions, there is no report considering building size and layout in order to utilize the wind around building for power generation of wind turbine 3) ~ 13). To realize the wind energy utilization in the built environment, it is important to conduct the feasibility study on the power generation performance of wind turbine under the actual wind condition. Although the power generation performance of wind turbine was predicted and tendency of wind condition such as frequency distribution of wind speed and wind direction was estimated considering each city and country situation by some studies, these studies did not intend to design the smart city consisting of wind turbine integrated with building and to utilize the wind around building for wind turbine 14) ~ 23). In our previous study 24), assessment of wind turbine power output in the built environment has been presented. It has also discussed the wind speed distribution in the built environment. The wind speed acceleration in the built environment has been reported in the literature, but the impact of building topologies / layouts have not been investigated on wind speed profiles and also on their utilization for wind turbines in the urban area 24). It is important to examine the feasibility of installing wind turbines in the planned building models for analysing the wind electricity generation and their role on meeting the electrical energy demand of the city. In this study, the objective is to estimate the electrical power output from wind turbines of the urban area by considering the wind speed profiles / variations in the built environment. It focuses on analysis of the wind speed distribution around the buildings and to investigate the wind turbine power generation performance. Also, this study presents the changes in wind speed profile and wind turbine electrical energy output with reference to the various building topologies / sizes in the smart city planning. This study considers building layouts which can produce higher wind turbine power output. The configuration of building layouts like nozzle is proposed and investigated to obtain the tapered wind flow through the buildings (Fig. 1). Also the wind speed distributions across the buildings according to the proposed building layouts are investigated. The wind speed data base of the Japan Meteorological Agency 25) is used in this study. The meteorological data are utilized for evaluating the wind speed profile across the building and for finding the electrical energy output of the wind turbines. Two buildings are configured as a nozzle (Fig. 1) and building size is 10 m width, 40 m length, 40 m height. The representative length of this model L, which is a hydraulic diameter of horizontal cross area, is 16 m. Other dimensions (e.g. angle between two buildings i.e. 90 degree, distance between two buildings 40 m etc) of the building layouts are given in Fig. 1. In city planning, there will be several buildings, but this study considers only two buildings. In further work, multi building layouts will be considered for wind speed distribution in the downstream. Also it will consider the ground surface elevation / topologies. The results of this study may be useful for city planner for finding the proper locations of the Fig. 1 Building layouts for wind speed profile and wind power generation

3 J. Jpn. Inst. Energy, Vol. 93, No. 4, buildings for effective utilization of wind energy resources in the built environment. 2. Analysis procedure of building model In this work, the wind speed distribution across the buildings is developed / simulated through CFD- ACE+. The previous work 24) has also used this CFD- ACE+ for assessment of wind turbine power output in the built environment. The wind speed distribution model and simulation procedure, which have been used in this study, have been presented in the Section 2 of our previous study 24). In the present paper, the wind speed estimation procedure which includes different steps compared to the previous study 24) is explained as follows. The wind at the area at the back of building is thought to be available for power generation by wind turbine, since the wind would be accelerated by blowing through buildings. Three points at the back of building which are apart from the building by 20, 30, and 40 m (x/ L = 1.25, 1.875, 2.50) is assumed as the installation point of wind turbine. The wind speed for calculating the power generated by wind turbine is obtained on 1049 points located in the area where the rotor of wind turbine rotates, that is, the swept rotor area. The wind speed at each point on the swept rotor area is the averaged speed in the local area of 0.5 m 0.5 m. By considering the wind speed distribution of this local wind speed, the wind energy can be calculated. Average wind speed to x axis direction is estimated by using the following equation: 1/3 2Q x U ave= NρA (1) where U ave is the average wind speed to x axis direction, Q x is the summation of wind energy to x axis direction on each point for calculating wind speed distribution, N is point for calculating wind speed distribution in the swept rotor area A (= 1049 points), ρ is the density of wind, A is the swept rotor area. Wind energy at each point on the swept rotor area is calculated by the following equation: 3 Q x= Σ 1049 Q x,i Σ = ρa i U i (2) i=1 i=1 2 where Q x,i is the wind energy to x axis direction at each point, A i is the area of each point which is equal to 0.5 m 0.5 m, U i is the wind speed to x axis direction at each point for calculating wind energy. Vave which is the average wind speed to y axis direction is estimated by the same calculation way of U ave. The average wind speed to horizontal surface of the swept rotor area U h,ave is calculated by the following equation: U h,ave= (3) U 2 ave+v 2 ave Here, the wind speed and wind energy to z axis direction are ignored since the rotor of wind turbine can t move toward z axis direction and wind energy to z axis direction can t be utilized. Building design procedure has been explained in reference 24). Also the other parameters e.g. wind turbine specifications, power curve for estimation of wind power output has been reported in reference 24) and they are also used in this study. Table 1 lists the specification of wind turbine. In this study, the real commercial wind turbine is adopted for estimating the power generated by wind speed distribution. AEOLOS wind turbine of 50 kw class 26) is adopted in this study. The hub height and rotor radius of this turbine is 30 m and 9 m, respectively, resulting that the height of building of 40 m is almost same as axis height of wind turbine. Table 2 lists the simulation condition in this study. Numerical simulation has been carried out under steady state by standard k - ε model. Calculation number is set This calculation number should be appropriate since the residue of each parameter under each numerical simulation condition keeps a stable low value after 500 times calculation. Wind speed at inlet of the model is set by the following equation: 0.25 U= U z 0 (4) 30 where U is the wind speed in x direction, U 0 is the initial wind speed at z = 30 m which is changed from 3.0 m/s to 12.0 m/s, z is height. U 0 = 10.0 m/s is the rated Table 1 Specification of wind turbine Rated power [kw] 50 Start wind speed [m/s] 3 Cut-in wind speed [m/s] 3 Cut-out speed [m/s] 25 Rotor diameter [m] 18 Rotor speed [rpm] 60 Hub height [m] 30 Table 2 Simulation condition Density of wind at inlet [kg/m 3 ] Temperature of wind at inlet [K] 293 Pressure of wind at inlet [MPa] 0.10 Kinetic viscosity of wind [m 2 /s] Wind speed at inlet [m/s] U = U 0 (z/30) 0.25 (U 0 = 3.00 ~12.00) Slip on side wall of building V = (0.41 l ) 0.25 U Turbulent flow model Standard k - ε model Turbulent energy [m 2 /s 2 ] Dissipation rate [m 2 /s 2 ] ( )/z Calculation number [-] Residue of each parameter [-] < Calculation state Steady state

4 318 J. Jpn. Inst. Energy, Vol. 93, No. 4, 2014 wind speed of AEOLOS wind turbine of 50 kw class 26). In this equation, it is assumed that U equals to U 0 at z = 30 m which is the hub height of wind turbine when the wind reaches to the building. In this work, wind speed data for Tsu city are used from the Japan Meteorological Agency 25). The wind speed data of five years (from 2007 to 2011) is used. In this study, the buildings are located as nozzle, therefore the wind inflow direction is important for obtaining the wind blowing through the buildings. The layouts of the buildings are decided based on the wind speed direction. The wind speed directions and building layouts are given in Fig. 2. If the main wind speed direction is North (N), the wind from North-West (NW), North-North-West (NNW), North-North- East (NNE) and North-East (NE) including North can be utilized for blowing the wind among the buildings through nozzle. Assuming the symmetry to the main wind direction, the wind speed distributions around the buildings for the in-flow angles β of 22.5 degree and 45 degree are simulated to evaluate the effect of four angular inflows on the wind speed distribution. Wind speed at inlet of the model is set by Eqs. (5) and (6), when the effect of inflow angle is considered U = cos β U z 0 (5) V= sin β U z 0 30 (6) where V is the wind speed in y direction, β is in-flow angle. 3. Results and discussion 3.1 Wind speed distribution around buildings The contours of wind speed distribution in x direction (U) around the buildings for U 0 = 10 m/s at z = 30 m are given in Fig. 3 and they are on x - y cross section of the building. It shows the distribution of U in case of β = 0 degree, (i.e. the model faces the main wind direction). In this model, x = 0 m and y = 0 m is located at the centre of distance between the nearest edge of adjacent two buildings. In this Fig. 3, black lines mean the separation lines, which distinguish the different calculation domain in the model used for numerical simulation. It has been observed that the wind is accelerated within the intervening space between the buildings since some wind is over the U 0 of 10 m/s. To investigate the location point of wind turbine, the contours of wind speed U distribution for U 0 = 10 m/s in the swept rotor area at the back of buildings for x/l = 1.25, Fig. 2 Wind speed directions and layouts of buildings Fig. 3 Contour of wind speed U distribution around buildings at z = 30 m on x-y cross section (U 0 = 10 m/s) Fig. 4 Contour of wind speed U distribution at the area at the back of buildings for x/l = 1.25, 1.875, 2.50 on y-z cross section (U 0 = 10 m/s)

5 J. Jpn. Inst. Energy, Vol. 93, No. 4, and 2.50 on y-z cross section are analysed and it is presented in Fig. 4. In the Fig. 4, black cross line shows the blades of wind turbine, if the wind turbine is located there. Black block line shows the building wake position. Although the wind speed decreases in the building wake, the wind is accelerated within the intervening space between the buildings at the area of the back of buildings for x/l = 1.25, and The wind speed distribution in the swept rotor area of wind turbine is important for estimating the wind power output. The frequency distribution of U in the swept rotor area at x/l = 1.25, and 2.50 is given in Fig. 5. It has been observed that the U > U 0 of 10 m/s is confirmed at the area at the back of buildings of x/l = 1.25, and Additionally, it is known that the higher U is obtained near the buildings. This study carries out the 3D model simulation and investigates the wind speed distribution towards y direction as well as x direction in order to calculate U h,ave. The frequency distribution of wind speed towards y direction (V) in the swept rotor area for U 0 = 10 m/s at x/l = 1.25, and 2.50 are given in Fig. 6. It is observed from Fig. 6 that V is small compared to U shown in Fig. 5. Therefore, it can be said that U h,ave is decided by U ave mainly. The variations of U h,ave in the swept rotor area at the back of buildings for x/l = 1.25, and 2.50 with the different U 0 condition are given in Table 3. U h,ave is estimated from the simulation results. It is seen that U h,ave is greater than U 0 for each U 0 condition. Hence, it can be concluded that the proposed building model can provide the wind acceleration irrespective of U 0. Considering the location point of wind turbine, the highest U h,ave is obtained at x/l = 1.25 under these investigating conditions. Therefore, this study has examined the wind turbine power generation performance for turbine location at x/l = Power generation performance of wind turbine located at proposed building layouts in actual area of Tsu city In order to decide the location of the wind turbine in proposed building layouts, the wind directions are considered (Figs. 1 and 2) in the actual area of Tsu city. Annual wind speed direction distribution in Tsu city is given in Fig. 7 and it is based on the wind speed data of Japan Meteorological Agency 25). The hourly measurement data from 2007 to 2011 are used for estimation of annual Fig. 5 Frequency distribution of wind speed U in the swept rotor area at x /L = 1.25, 1.875, 2.50 (U 0 = 10 m/s) Fig. 6 Frequency distribution of wind speed V in the swept rotor area at x /L = 1.25, 1.875, 2.50 (U 0 = 10 m/s) Table 3 U h,ave under different U 0 conditions U 0 [m/s] U h,ave at x/l = 1.25 [m/s] U h,ave at x/l = [m/s] U h,ave at x/l = 2.50 [m/s]

6 320 J. Jpn. Inst. Energy, Vol. 93, No. 4, 2014 Fig. 7 Annual wind direction distribution in Tsu city wind direction distribution. It is observed that the main wind direction throughout the year is North-West (NW). In this study, it is assumed that the open tip of building model is located to be faced with the main wind direction (refer to Fig. 2). West (W), West-North-West (WNW), North- North-West (NNW) and North (N) in addition to North- West (NW) are the wind directions. Therefore the proposed building layouts make the nozzle by utilizing the wind speed directions. In this study, it is assumed that the wind blowing from the directions except for the above described five wind directions can t be utilized for power generation of wind turbine. The different inflow angle conditions are considered in the simulation for finding the direction of wind in the proposed layout. As an example of the simulation results, the contours of wind speed U distribution around buildings for U 0 = 10 m/s at z = 30 m on x - y cross section for angular inflow conditions are given in Fig. 8. Although the wind blows through the intervening space between the buildings, the wind acceleration is not high. Hence, the wind power generation through wind speeds coming from the main wind direction is important. The hourly data on wind speed and direction are obtained for Tsu city from the Japan Meteorological Agency 25). These are used as inputs in the simulation for finding the wind turbine power output at a location of wind turbine in the proposed building layouts. The daily wind turbine power outputs (wind turbine located at location of the proposed building layout) for months January, April, July and October are given in Figs. 9, 10, 11 and 12 respectively. These four months are considered as representative of four Fig. 8 Contour of wind speed U distribution around buildings at z = 30 m on x-y cross section for angular inflow conditions (U 0 = 10 m/s) Fig. 9 Wind energy output variation in January for installing proposed building layouts in Tsu city (x /L = 1.25) Fig. 10 Wind energy output variation in April for installing proposed building layouts in Tsu city (x /L = 1.25)

7 J. Jpn. Inst. Energy, Vol. 93, No. 4, Fig. 13 Frequency distribution of wind speed direction in July at Tsu city Fig. 11 Wind energy output variation in July for installing proposed building layouts in Tsu city (x /L = 1.25) blowing from the restricted five directions is small in July relatively, resulting that the wind energy production is lower compared to the other months. Therefore, while selecting the building orientations, it is very important to consider the wind speed directions in order to maximize annual wind energy production. In future study, the building layouts will be considered to accelerate the wind speed for more wind energy production. In addition, the power generation performance of the proposed building model will be verified to fulfil the electric demand for several consumption patterns. As an application model to meet the electric demand, the building integrated photovoltaic and fuel cell systems also will be considered. Fig. 12 Wind energy output variation in October for installing proposed building layouts in Tsu city (x /L = 1.25) seasons. From these figures, it is observed that the higher power energy of wind turbine is obtained in the daytime irrespective of month / season. In addition, the higher amount of total wind energy through a day is obtained in January, while the lower amount of total wind energy through a day is obtained in July (in comparison with these four representative months). The direction of main wind speed in July is East-South-East (ESE) and it is shown in Fig. 13, while the direction of main wind speed throughout the year is North-West (NW). In this study, it is assumed that the wind blowing from the restricted wind direction can be utilized for power generation of wind turbine. The restricted wind direction means five directions whose center is main wind direction, and the other four directions are located symmetry to the main wind direction. The amount of wind energy production is estimated to be zero for the wind blowing from the other directions. The monthly main wind direction is East-South-East (ESE) in July as shown in Fig. 13 while the monthly main wind direction in the other months is North-West (NW). The frequency of wind 4. Conclusions In this study, building topologies / orientations in a smart city are investigated for finding out the wind speed profile in the built environment. The analysis of wind speed distribution and directions are very important for not only to find the mechanical wind stress but also to find the energy content in the wind. This analysis is also useful for designing the building layouts in such a way to make the nozzle of the wind by using wind directions and then finding out the proper location of the wind turbine in the built environment. In this work, building layouts like nozzle is proposed and investigated to obtain the contracted flow by blowing wind through the buildings. The output power of the wind turbine is estimated by using the power curve of real commercial wind turbine and the wind speed distribution around buildings by using the wind speed data for Tsu city. (1) The wind is accelerated within the intervening space between the buildings at the area at the back of buildings for x/l = 1.25, and 2.50, and it is observed that U > U 0 (of 10 m/s) is confirmed in the proposed area. (2) Since Uh, ave at the back area of buildings for x/l = 1.25,

8 322 J. Jpn. Inst. Energy, Vol. 93, No. 4, and 2.50 is higher than U 0, and hence the proposed building layouts can provide the wind speed acceleration irrespective of U 0. (3) In this study, the building layouts are considered at Tsu city. It is observed that the higher wind energy output is obtained in the daytime irrespective of the month / season. The higher wind energy output throughout the day is available in January, while the lower wind energy output is available in July. References 1)Kolhe, M., The Electricity Journal, 25, (2012) 2)Zhenglin, Z.; Hongyan, W.; Xiaolong, B.; Hongxiang, X., Prrep International Conference (IEEE) on Materials for Renewable Energy & Environment (ICMREE), pp , May 20-22, 2011, Shanghai, China 3)Yoshie, R.; Tominaga, Y.; Mochida, A.; Kataoka, H.; Yoshikawa, Y., Wind Engineers, 30, (2005) 4)Murakami, S.; Hibi, K.; Mochida, A., J. Archit. Plann. Environ. Engng, 425, (1991) 5)Kataoka, H.; Mizuno, M., J. Archit. Plann. Environ. Eng, 504, (1998) 6)Nishimura, K.; Yasuda, R.; Ito, S., J. Jpn. Soc. Atmos. Environ., 34, (1999) 7)Nozu, T.; Tamura, T., J. Struct. Constr. Eng., 538, (2000) 8)Nozu, T.; Tamura, T., J. Struct. Constr. Eng., 503, (1998) 9)Kose, D. A.; Fauconnier, D.; Dick, E., J. Wind Eng. Ind. Aerodyn., 99, (2011) 10)Meng, Y.; Hibi, K., J. Wind Engineering, 72, (1997) 11)Meng, Y.; Oikawa, S., J. Jpn. Atmos. Environ., 32, (1997) 12)Oikawa, S.; Ishihara, T.; Yasuda, R.; Nishimura, K.; Hase, M., J. Jpn. Soc. Atmos. Environ., 34, (1999) 13)Zaki, S. A.; Hagishima, A.; Tanimoto, J., J. Wind Eng. Ind. Aerodyn., 103, (2012) 14)Ouammi, A.; Dagdougui, H.; Sacile, R.; Mimet, A., Renewable and Sustainable Energy Reviews, 14, (2010) 15)Oyedepo, S. O.; Adaramola, M. S.; Paul, S. S., Int. J. Ene. Environ. Eng., doi: / (2012) 16)Olaofe, Z. O.; Folly, K. A., Renewable Energy, 53, (2013) 17)Saito, S.; Sato, K.; Sekizuka, S., JSME Int. J. Series B, 49, (2006) 18)Khadem, S. K.; Hussain, M., Renewable Energy, 31, (2006) 19)Firtin, E.; Guler, O.; Akdag, S. A, Applied Energy, 88, (2011) 20)Rocha, P. A. C.; Sousa, R. C.; Andrade, C. F.; Silva, M. E. V., Applied Energy, 89, (2012) 21)Usta, I.; Kantar, Y. M., Applied Energy, 89, (2012) 22)Mostafaeipour, A., Renewable and Sustainable Energy Reviews, 14, (2010) 23)Wang, Li; Yeh, T. H.; Lee, W. J.; Chen, Z., IEEE Transactions on Industry Application, 47, (2011) 24)Nishimura, A.; Ito, T.; Murata, J.; Ando, T.; Kamada, Y.; Hirota M.; Kolhe, M., Smart Grid and Renewable Energy, 4, 1-10 (2013) 25)Japan Meteorological Agency, go.jp/obd/stats/etrn/index.php (Last access: ) 26)AEOLOS wind turbine, com/ (Last access: )