Abstract
The assessment of the production capacity of wind farms is a crucial step in wind farm design processes, where a poor assessment can cause significant economic losses. Data from Canadian wind farms benefiting from national production incentive programs show that wind farms are typically characterized by an overestimation of the production capacity. In this context, a study has been done to provide insight on the origin of the discrepancies between the energy production estimates and the measured energy generation, and to develop a method to reduce these discrepancies. To this end, the WAsP and MS-Micro models have been studied. Besides the wind speed measurements, topography indices have been developed to identify the influence of the various characteristics of the site on the error in the annual energy production (AEP). In addition, roughness classes have been created, including a reference roughness and a roughness complexity. The indices have also allowed establishing correlations and developing equations to evaluate the error based on the site characteristics and the positions of wind turbines on the measured annual energy production. An average reduction of up to 83% on the AEP errors was obtained when the methodology was applied to five wind farms in Canada.
Highlights
For the wind farms located in simple sites, the annual energy production (AEP) of Wind Farm IV is overestimated by WAsP and MS-Micro; the AEP errors are relatively low, which is expected for a simple terrain wind farm
These results show that the largest AEP errors occur for wind farms in complex terrains
Similar observations are applicable for the AEP errors and the absolute average AEP errors for the wind turbines, where the corrected errors are respectively below 2% and 5%, with the exception of Wind Farm V
Summary
Bowen and Mortensen [13] [14] developed a methodology to evaluate the accuracy of the WAsP model in complex terrains It has been shown [13] [14] [15] that a relationship, called the ruggedness index (ΔRIX), exists between the mean wind speed errors and a flow separation indicator. Four sites correlated well with each other, with mean wind speed errors up to 2%, while the two other sites gave significant mean wind speed errors These studies show that methodologies to increase the accuracy of the WAsP model in complex terrains can give relatively good results. A short conclusion and recommendations for future work ends the paper
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call