Technical asset management of a wind asset can be challenging. It requires not only supervision of the wind farm production, but also wind farm performance analysis in order to detect if the turbine is under or over performing.
Data performance analysis is key when managing a wind asset. By transforming data into insight, the asset manager and owners are provided with a set of information useful to challenge the turbine manufacturer. We will illustrate in this article, using a specific example, as shown on the below layout and more particularly on WTG1, WTG2 and WTG3.
When initially only analysing the power curves of the three wind turbines, WTG3 seems to underperform compared to other turbines. You can see this clearly indicated by the graph below.
However, after further analysis, it was found that the relative underperformance was actually due to the transfer function of the corresponding nacelle anemometer. Therefore, you can already see that only analysing one aspect of the turbine, in this instance, the power curve, the data is not sufficient in order to understand the true, comprehensive turbine performance.
Below are outlined some key performance indicators that can be used to further understand wind turbine behaviour and to detect possible underperformance. This is known as wind farm performance analysis.
Which analysis are to be taken into account?
Ratio
To avoid the impact of nacelle anemometer measurements, we recommended to work directly with production data.
The first performance indicator is the ratio R as described in the below formula. The ratio is the difference between the specific wind turbine and the average production over the whole wind farm, on the same period:
Where
PWTi is the production of the wind turbine
N is the number of wind turbines
When a reliable pre-construction yield assessment is available, the aforementioned ratio can be calculated for each turbine and used as reference. Two parameters are taken into account to estimate the reliability of the pre-construction ratio:
- Wind flow modelling: errors in wind variations increase with the terrain complexity.
- Wake modelling: when the layout does not respect the recommended inter-turbine spacing, corresponding input conditions are outside of the validation envelope, leading to biased results in some cases.
The table below shows the calculated ratios during pre-construction and during various operational stages:
Period 1 = November 2016
Period 2 = January 2016 to November 2016
By calculating this parameter each month, any abnormal events, compared to expectations (pre-construction), will be noticeable. A difference of more than 5% will need to be further investigated as it can be due to a change in the wind distribution or an issue with the turbine performance itself.
Scatter plot
Another useful tool is the scatter plot. By plotting a time series of production data, measured at a wind turbine considered as reference (WTG1) against another series of production data, it enables us to highlight any discrepancies. In the example below, production data was plotted for November 2016.
These graphs not only show the general consistency in the production between all turbines but also the outliers. In this particular case, WTG1 and WTG2 have similar trends. More discrepancies are observed between WTG1 and WTG3 due to different exposure to wake effects (see the layout). In any case, no major underperformance has been observed in November 2016.
Understanding wind farm performance analysis is key
In this particular example, by analysing other indicators, and provided that terrain is simple and layout respects inter-distance (to limit wake effects), we can come to conclusion that WTG3 is performing at its optimum levels. It is similar compared to the other wind turbines in the same park, during the same studied time period.
Data analysis is therefore key to understand operational wind farm performances. It can highlight whether there are underperformances and allow you to fix these promptly. Get in touch with our experts to discuss your wind farm performance analysis!
