The project viability of a wind farm is an iterative and multi-disciplinary process which encompasses technical, regulatory, commercial and financial elements� Due to the complex nature of the investment case, key stakeholders should approach the process through a step-by-step decision-making procedure, which will gradually assess the viability of the business case� The figure below provides a visual roadmap of the development process for onshore wind projects�
Development process for wind energy projects
The project viability of a wind farm is an iterative and multi-disciplinary process which encompasses technical, regulatory, commercial and financial elements. Due to the complex nature of the investment case, key stakeholders should approach the process through a step-by-step decision-making procedure, which will gradually assess the viability of the business case. The figure below provides a visual roadmap of the development process for onshore wind projects.
Figure 8: Development process line for onshore wind projects.
The diagram below shows the basic contractual structure of a project financed wind farm.
Figure 9: Stakeholders and parties involved in the development of wind energy projects.
The detailed contractual structure will vary from project to project, depending also on the procurement strategy used, the contract terms and the allocation of liabilities and risks.
Figure 8: Development process line for onshore wind projects.
The diagram below shows the basic contractual structure of a project financed wind farm�
Figure 9: Stakeholders and parties involved in the development of wind energy projects.
The detailed contractual structure will vary from project to project, depending also on the procurement strategy used, the contract terms and the allocation of liabilities and risks�
Nevertheless, the business case of onshore wind projects may be enclosed in these main assessment areas:
• Wind resource assessment
• Site selection
• Grid proximity and connection
• Planning and environmental approvals
• Power sale
• Project financing and bankability
• Procurement process and construction
• Operation and maintenance
• Decommissioning or repowering
The themes mentioned above will be described in details, and specific analysis and guidance will be provided for the Ethiopian case� It should be mentioned that this report focuses on pre-development, project management and operational aspects of onshore wind farms� Therefore, analysis won´t be provided for the decommissioning or repowering process of wind farms, since it is out of scope for this specific work�
1. w ind r esourCe a ssessment
An accurate wind energy resource assessment is probably one of the most important elements in identifying viable wind projects� Since the power available in the wind is a cube function of the wind speed, small changes in average wind speeds have a large impact on the energy output� Just for reference, if the wind speed is doubled, the wind power increases by a factor of 8� Hence, the project viability of a wind farm is extremely sensitive to accuracy and magnitude of wind resources� Figure 10 provides an exhaustive explanation of this strict correlation comparing the costs of wind projects as a function of the wind speed and the capacity factor�
Figure 10: Wind energy costs as a function of wind speed and capacity factory (Milborrow, 2017).
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Furthermore since winds vary both on short and long-term (time of day, seasons, etc�), accurate wind studies on specific sites have to focus on multiple aspects of the data such as mean annual wind speed, frequency distribution of the wind at various speeds, turbulence intensity, wind shear, and maximum gusts (extreme wind events)� These parameters are critical for estimating the potential energy in the wind as well as the choice of turbine technology for the specific site�
For project developers and governments which would like to exploit wind resources, the starting point of the wind resource assessment is the examination of wind resource maps for a specific country or region (if they already exist)� The most accurate way to develop wind resource maps is through the Wind Atlas methodology and advanced programs such as Computational Fluid Dynamics and WAsP/WindPRO� The method makes it possible to transform wind data from existing meteorological masts and extrapolate wind properties at specific sites with a radius up to 200 km� This new set of data enables project developers to develop accurate calculations on the expected energy yield at the selected sites�
However, the sensitivity of energy production to wind speed requires further analyses by actual on-site measurements� This is usually achieved during the project feasibility stage through the installation of wind monitoring equipment on-site� The longer the duration of the wind study is, the more accurate the production estimates will be� Generally, the time window of wind data acquisition for on-site wind measurement campaigns ranges from 1 to 5 years with a 10-minute time resolution�
The data collected can be then sorted into bins of wind speed classes of 1 m/s each and the energy contained in the wind at a certain site may then be expressed by a frequency distribution� Usually, the Weibull distribution is often a precise approximation for the wind speed distribution� From a mathematical point of view, the Weibull function is strictly dependent on two site-specific parameters: A and k� The former is called Weibull scale parameter, which is proportional to the mean wind speed of the site, while k is called shape parameter� Small values for k imply very variable winds with repeating extreme winds events, while constant winds are characterized by larger k values� For k=2, the Weibull distribution yields to a Rayleigh distribution�
and maximum gusts (extreme wind events). These parameters are critical for estimating the potential energy in the wind as well as the choice of turbine technology for the specific site.
For project developers and governments which would like to exploit wind resources, the starting point of the wind resource assessment is the examination of wind resource maps for a specific country or region (if they already exist). The most accurate way to develop wind resource maps is through the Wind Atlas methodology and advanced programs such as Computational Fluid Dynamics and WAsP/WindPRO. The method makes it possible to transform wind data from existing meteorological masts and extrapolate wind properties at specific sites with a radius up to 200 km. This new set of data enables project developers to develop accurate calculations on the expected energy yield at the selected sites.
However, the sensitivity of energy production to wind speed requires further analyses by actual on-site measurements. This is usually achieved during the project feasibility stage through the installation of wind monitoring equipment on-site. The longer the duration of the wind study is, the more accurate the production estimates will be. Generally, the time window of wind data acquisition for on-site wind measurement campaigns ranges from 1 to 5 years with a 10-minute time resolution.
The data collected can be then sorted into bins of wind speed classes of 1 m/s each and the energy contained in the wind at a certain site may then be expressed by a frequency distribution.
Usually, the Weibull distribution is often a precise approximation for the wind speed distribution.
From a mathematical point of view, the Weibull function is strictly dependent on two site-specific parameters: A and k. The former is called Weibull scale parameter, which is proportional to the mean wind speed of the site, while k is called shape parameter. Small values for k imply very variable winds with repeating extreme winds events, while constant winds are characterized by larger k values. For k=2, the Weibull distribution yields to a Rayleigh distribution.
Figure 11: Weibull distribution of the wind speeds at the Danish site Hvide Sande (DEA et al., 2017).
Production estimate
When wind data has been collected and quality is checked, the annual energy production (AEP) of a wind farm may be evaluated. Its calculation is strictly dependent on several parameters:
Figure 11: Weibull distribution of the wind speeds at the Danish site Hvide Sande (DEA et al., 2017).