A true understanding of wind variability reduces project risk.
Long-term wind and energy variability are the key drivers in financial risk for existing or planned wind energy production facilities. Quantifying the future variability of the fuel supply to wind plants is a critical element for enterprise success. To address this business need, WindLogics developed its patented Enhanced-MCP™ process (US Pat. 7,228,235) to assess exposure to financial risk.
The Enhanced-MCP process overcomes several limitations of commonly used Measure-Correlate-Predict techniques, which correlate on-site tower data to nearby reference data (typically a local airport) using simple linear regression. Instead, Enhanced-MCP combines on-site tower or energy production data with the best available long-term reference data (often NCEP/NCAR Reanalysis), using advanced multi-parameter nonlinear regression. The result is a much clearer expectation for long-term performance.
The output of this rigorously validated process is a 40-year time-series data file of hub-height wind speed, direction and energy production for the exact tower location. From this data, a wide variety of “normalized” statistics can be calculated, most notably predictive interval values (P90, P75, P95, P99) of expected annual average wind speeds or energy production.
With this information, developers and owners have improved understanding of the expected energy production variability and associated revenue risk profiles for proposed or operating wind plants. The long-term energy time series can also be used to generate monthly and annual average graphs, diurnal graphs, histograms, wind roses, and 24x12 tables. The data is ideal for micrositing, where the long-term values can be used to optimize wind turbine layouts.
WindLogics is recognized as an industry expert in the research and application of long-term wind variability analysis. Please contact us for more information on the advantages of Enhanced-MCP data and the process behind it. For more on how we apply these methods, please see Due Diligence Analysis.