The long-term correction is a critical step of the determination of the P50 in an energy yield assessment. Given its importance in the energy yield calculations, errors can lead to impacts up to 5 points on the P50 estimates, which greatly impacts the valuation of assets.
Greensolver has identified a set of actions that should be considered in order to minimize the risk of error on the long-term wind speed estimate and reduce the P50 uncertainty:
- First of all, Greensolver recommends to check that the consistency of the chosen reference data and long-term period have not been affected by any changes in instrumentation or in the exposure of the meteorological stations. The history of instrumentation and mast location will be studied as well as the reported changes in the environment of stations.
- Moreover, the reference sources must have a similar climatology to the site. The following parameters will be analyzed to ensure the reference data is representative of the site climatology:
- monthly and annual trends in average wind speeds,
- inter-annual variations,
- wind frequency and energy distribution over the measurement period and the long-term period,
- correlations between site and reference data for the concurrent period
- cross-correlations between all reference data.
- The generation of a wind index across the considered region, based on data from different meteorological stations and mesoscale models can be a solution to limit inconsistencies. The combination of various validated sources increases confidence in the homogeneity of the long-term data and robustness of the long-term correction results.
- When possible, the MCP (Measure Correlate Predict) method will be preferred as a long-term correction technique in order to preserve the variation in wind frequency distribution over the historical period. Different sorting methods (by direction, month, time of day) can be tested to choose the configuration giving the best level of correlation.
- The sensitivity of the long-term correction results to the selected long-term period or reference data can be tested in order to strengthen the choices made. The various tests of sensitivity will be used as well to determine the uncertainty levels.
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