Application of Measure–Correlate–Predict (MCP) Methodology for Long-Term Evaluation of Wind Potential and Energy Production on a Terrestrial Wind Farm Siting Position in the Hellenic Region

The current work focuses on the study of the long-term evaluation of wind potential and energy production for a specific wind farm siting position over a mountainous region in Hellas. It aims to calculate the probability of exceedance of the twenty-year normalized average annual net production of the wind farm based on ground wind measurements coupled with Copernicus ERA5 data via a measure–correlate–predict (MCP) method. The study proposes an integrated long-term wind resource assessment workflow that couples short-term mast data with a twenty-year ERA5 record via a refined MCP procedure including temporal shifting for complex terrain. It introduces a practical uncertainty framework that jointly treats measurement, MCP, and terrain effects through dRIX and propagates these to energy yield using a bin-wise power curve and Weibull weighting. The proposed methodology is both fast and readily available to end-users and provides a realistic estimate of the energy production and long-term wind distribution in the investigated area. The data and assumptions employed in the calculations are given in detail. The uncertainty of the parameters in the estimation of the wind potential of the broader area and the energy calculation is analyzed. The results of the calculations and the probability of exceedance curve of the normalized twenty-year average annual net production of the wind farm summarize all uncertainty sources, delivering bankable long-term energy projections for the specific case study.