Site-Adaptation of Modeled Solar Radiation Data: The SiteAdapt Procedure

Carlos M Fernández-Peruchena,Jesús Polo,Luis Mazorra,Luis Martín

doi:10.3390/rs12132127

Abstract

The adaptation of modeled solar radiation data with coincident ground measurements has become a standard practice of the industry, typically requested by financial institutions in the detailed solar resource assessments of solar projects. This practice mitigates the risk of solar projects, enhancing the adequate solar plant design and reducing the uncertainty of its yield estimates. This work presents a procedure for improving the accuracy of modeled solar irradiance series through site-adaptation with coincident ground-based measurements relying on the use of a regression preprocessing followed by an empirical quantile mapping (eQM) correction. It was tested at nine sites in a wide range of latitudes and climates, resulting in significant improvements of statistical indicators of dispersion, distribution similarity and overall performance: relative bias is reduced on average from −1.8% and −2.3% to 0.1% and 0.3% for GHI and DNI, respectively; relative root mean square deviation is reduced on average from 17.9% and 34.9% to 14.6% and 29.8% for GHI and DNI, respectively; the distribution similarity is also improved after the site-adaptation (KSI is 3.5 and 3.9 times lower for GHI and DNI at hourly scale, respectively). The methodology is freely available as supplementary material and downloadable as R-package from SiteAdapt.

Highlights

The bankability of a solar power project requires the best possible information about the quality and reliability of the solar resource for both technical and financial aspects of the project
It was tested at nine sites in a wide range of latitudes and climates, resulting in significant improvements of statistical indicators of dispersion, distribution similarity and overall performance: relative bias is reduced on average from −1.8% and −2.3% to 0.1% and 0.3% for Global horizontal solar irradiation (GHI) and direct normal solar irradiance (DNI), respectively; relative root mean square deviation is reduced on average from 17.9% and 34.9% to 14.6% and 29.8% for GHI and DNI, respectively; the distribution similarity is improved after the site-adaptation (KSI is 3.5 and 3.9 times lower for GHI and DNI at hourly scale, respectively)
The solar radiation coming from a small solid angle of the sky, centered on the position of the sun’s disk itself is the direct normal solar irradiance (DNI), which is of particular interest for concentrating solar power (CSP) and concentrating photovoltaic (CPV) technologies

Summary

Introduction

The bankability of a solar power project requires the best possible information about the quality and reliability of the solar resource for both technical (planning, dimensioning and designing stages) and financial aspects of the project. Due to the significant short-term and long-term variability in solar irradiance [1,2,3], the solar resource assessment should consider solar irradiance time series—and not just mean annual averages—to understand the solar dynamics over intraday, daily and seasonal scales [4,5,6] and the interannual variability which defines the plant performance in different probability of exceedance scenarios [7,8,9,10] These scenarios, as well as their corresponding uncertainties, are modeled to evaluate a project’s ability to return the investment for these projects [10,11]

Methods

Results

Discussion

Conclusion