Parametric study of influencing parameters for micro urban wind turbines

Transcription

1 7th World Summit for Small Wind on 17 and 18 March 2016 in Husum Parametric study of influencing parameters for micro urban wind turbines Dr. Matthias Haase, SINTEF Building and Infrastructure, Trondheim, Norway Technology for a better society 1

2 Content Introduction Objectives Methodology Results Conclusions Technology for a better society 2

3 Introduction Large Wind Turbine (LWT) refers to the ones rated above 100kW Small Wind Turbines (SWT) are between 10kW and 100kW Micro Wind Turbines (MWT) are below 10kW urban wind turbines" (UWT) with capacity generally between 1 and 20 kw. Technology for a better society 3

4 Introduction Rotor types with the following sub-division Horizontal axis wind turbine (HAWT) Vertical axis wind turbine (VAWT) Building mounted wind turbine (BMWT) Building integrated wind turbine (BIWT) Building augmented wind turbine (BAWT) Technology for a better society 4

5 Introduction Hau, 2000 Technology for a better society 5

6 Building mounted wind turbine Horizontal axis Technology for a better society 6

7 Building mounted wind turbine Vertical axis Technology for a better society 7

8 BIWT Horizontal axis Vertical axis Technology for a better society 8

9 BAWT Horizontal axis Technology for a better society 9

10 BAWT Vertical axis Technology for a better society 10

11 BAWT Technology for a better society 11

12 Integrasjon Technology for a better society 12

13 Objectives In order to get a better understanding of the parameters that influence the effectiveness of urban wind turbines a parametric analysis was undertaken. The aim was to be able to compare those parameters that will influence wind energy production. The results should not be used for exact energy prediction but rather be understood as estimation that allows wind energy potential comparisons. Technology for a better society 13

14 Objectives Based on wind data for three different locations (Oslo, Trondheim and Tromsø) a parametric study was conducted that considered the influence of the following parameters: wind turbine type axis height turbine area surrounding topography wind channeling effect Technology for a better society 14

15 Methodology Parameter Influence on wind velocity Influence on wind power Wind turbine type Power coefficient cp Axis height Rotor axis height hb Turbine area Turbine's active area A Surrounding topography Roughness R, α Wind channelling effect Wind velocity factor fw Location Wind data file Technology for a better society 15

16 Turbine type Hau, 2000 Technology for a better society 16

17 Wind theory: Technology for a better society 17

18 Roughness Technology for a better society 18

19 Chanelling effect Technology for a better society 19

20 Location Tromsø Trondheim Tromsø Oslo Trondheim Oslo Technology for a better society 20

21 Methodology Wind data is taken from weather data measurements. These are measured for specific locations, often airports, with specific topography. The transformation of measured data to specific sites is not straight forward. In wind projects and relevant literature, often specific data about the surrounding topography of the measurement devices is not available. In addition, PAD and roughness of the surrounding areas of the building where a wind turbine is planned to be installed is not available. For three location, Oslo, Trondheim and Tromsø measured wind data was taken from measurement stations (MET) and transformed using equations (1-12). Technology for a better society 21

22 Results wind energy production [kwh] Oslo Trondheim Tromsø 20m 35m 50m city urban country axis height surrounding surface roughness wind factor Figure 1 Effect of influencing parameters axis height, surface roughness and wind factor for Oslo, Trondheim and Tromsø Technology for a better society 22

23 Results It can be seen that wind energy production varies between 100kWh and 1348kWh for different wind for Oslo. In order to be able to evaluate the influence of each parameter on wind energy production it was divided by the wind energy production of the weather file for each location. Figure 1 shows the influence of parameters axis height, surface roughness and wind factor for Oslo, Trondheim and Tromsø in percent compared with energy production from the reference weather data file (v_meteo). It can be seen that axis height varies between 25 and 59%. Surrounding surface roughness has a much higher influence with values between 25 and 330%. Here, country roughness is much more favorable than urban and city roughness. For wind factor the values vary between 25 and 210%. Technology for a better society 23

24 Results wind energy production [kwh] Oslo Trondheim Tromsø Savonius Darrieus 3-blade rotor Savonius Darrieus 3-blade rotor Savonius Darrieus 3-blade rotor 12m2 18m2 24m2 Figure 2 Effect of influencing parameters turbine type and area for Oslo, Trondheim and Tromsø Technology for a better society 24

25 Results The other three influencing parameters turbine type, turbine area and location also have a large impact on wind energy potential. Figure 2 shows that size as well power coefficient cp of a turbine as has a linear relation with wind energy potential. This is due to the simplifications in the energy calculations that power coefficient is assumed to be constant. Important is also the location. Wind profiles in Trondheim have higher velocities as Oslo, and Tromsø higher velocities than Trondheim. Wind energy potential is accordingly higher in Trondheim than in Oslo and higher in Tromsø than in Trondheim. Technology for a better society 25

26 Conclusions This could be useful information for designers and planners of small urban wind turbines. The effect of location is very important, together with turbine size type and size. Different turbine types have different power coefficients which influence the potential wind energy production for same wind profiles. Turbine size is of course beneficial but larger turbines become more difficult to integrate into the built environment. Technology for a better society 26

27 Conclusions The wind profiles can also be influenced by designers and planners by taking urban and building design in to account and specifically focusing on the parameters axis height, surrounding topography and wind channeling effect. The axis height is strongly linked to the building geometry and especially height as a restricting parameter. The wind channeling effect is most prominent in building augmented projects. But due to the rough assumptions the channeling effect might also be overestimated. Technology for a better society 27

28 Summary Introduction Objectives Methodology Results Conclusions Technology for a better society 28