Site Resource Assessment and Rotor Design
Published: 2023-08-07 07:32:10

The first step in my blade design process was to assess the wind condition of the site my wind turbine will operate. In this step, my main objective was to estimate the main parameters that will define my wind turbine model, calculate airfoil aerodynamic properties, and most importantly, define the blade geometry. 

One might ask 

>
why did you perform a site assessment before designing your turbine blades? 


Site assessment provided me an insight into my blade design and how suitably my blades can operate at the given site, through a clear description of the Design tip speed ratio, Weibull probability distribution, Power curve, and Annual energy production (AEP). 

The AEP is based on the annual wind speed distribution (10 min. average) at a particular site. In simpler form, the AEP is a direct measure of how much energy a wind turbine can generate annually while operating on a particular site. 


> Maximizing wind turbines' annual energy production (AEP) is important for economic reasons.
 

By knowing the AEP at my given site, I was able to optimize the design of the turbine blades to capture the maximum amount of energy from the prevailing wind conditions at the site. In this process I tailored the blade design parameters, such as blade maximum length and aerodynamic profile to match the specific wind characteristics at the site, thereby maximizing energy capture.

**Mean Wind Speed at Site:**
The mean wind speed at the 100m hub height is 6.20m/s and this was obtained from the Weibull scaling factor A of 7 and Weibull shape parameter k of 2.15. 


## Rotor Sizing

The blade is expected to operate on an IEC type-class IIIb wind turbine with the following calculated sizing parameters: 


> Maximum Blade Length (Referenced) = 50m
> Hub Radius = 1.25m
> Hub Height (Referenced) = 100m
> Maximum Tip Speed (Referenced) = 75
> Rated RPM = 13.9746
> Rated Electrical Power = 1.5MW
> Mechanical Efficiency = 94.55%
> Electrical Efficiency = 94.69%
> Total Conversion Efficiency = 47% (obtained from the mechanical and electrical efficiency)

```
Rotor Radius = Maximum Blade Length (Referenced) + Hub Radius = 51.25m

Required Wind Power = Rated Electrical Power/Total Conversion Efficiency = 3.19GW

Estimated Rated Wind Speed = The estimated rated wind speed of 8.58m/s (9m/s, rounded up) was obtained at the maximum blade length and required wind power. 

Design Tip Speed Ratio (TSR) = Maximum Tip Speed (Referenced)/Estimated Rated Wind Speed = 8.33
```

> The TSR is a very important parameter stepwise in designing my blade because I used it in determining the Chord Length and Twist Angle of my blade. 

## Weibull Distribution

Weibull distribution is a statistical analysis method that I employed to model the probability distribution of wind speeds at 100m turbine hub height at the given site. With this distribution, I can understand the wind speed characteristics and the likelihood of different wind speeds occurring over the lifetime of my turbine. The Weibull distribution is a key step in determining the AEP at the given site.



![Weibull Distribution](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/ptj60f2v2dyby1dp2z19.png)

## Power Curve 

The Power Curve shows a relationship between the power output from my turbine and the wind speed. The power curve describes the cut-in, rated, and cut-out wind speeds of my turbine. The cut-in is the minimum speed at which the turbine starts producing energy. The rated wind speed is the speed at which the turbine produces maximum power output and the cut-out could be described as a run to safety, that is the maximum speed at which the turbine shuts down to prevent damage. 


![Power Curve](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/ly0fsxeahb1ih4s4uthy.png)

The average wind speed at the given site is 6.20m/s and the cut-in speed for my turbine is 3.5m/s.

> This power curve is only a theoretical approximation (ideal case). Most power curves, in reality, do not look exactly like this. In practical situations, the turbine most times reaches rated speed before it reaches its rated power and does not shut down automatically it reaches cut-out speed as seen in the power curve above but shuts down gradually even as speed increases. 


## Annual Energy Production (AEP):

To calculate the AEP, I typically multiplied the Weibull probability distribution with the power curve of my turbine.

```
AEP = sum([wind_speed_freq_distribution[i] * power_output_data[i] for i in range(len(wind_speed_data))])
```

![Annual Energy Production](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/gagf4fb7fao3jnahgg9g.png)

In conclusion, my wind turbine is planned to operate at a low wind speed site with a total net annual energy production (AEP) 5.53GWh. 

On a final note, we have now completed our site assessment, we have determined how much energy we can produce from our site, and we have sized our turbine to match the energy yield and obtained vital blade design parameters. This information will now be applied in designing the turbine blades which will perform the most important job of harnessing the wind energy at the site. 

To be continued...

## Acknowledgement

- Design of Wind Energy Masters' Course Tutorial - University of Oldenburg, Germany

***Please note, this episode of my "Blade Design Series" was created as an excerpt of my tutorial project work in my Wind Energy Design Course.***