Solar resource assessment in Ireland, comparison of satellite data versus ground measurement

Accurate solar resource assessments are essential to project a solar photovoltaic (PV) plant’s energy production – and ultimately forecast its revenue.

Solar resource assessments are the bedrock of the ‘Revenue’ line in PV financial models. In today’s competitive financing environment, the assumptions underlying solar resource assessment often have make-or-break impact on project valuations. It’s critical that investors trust the numbers provided.

To quantify solar resource, industry typically compares different irradiation databases derived from multiple physical sources – whether measurements or satellite images. There is always some level of scatter; in Western Europe this is often around 3%, after excluding outliers.  Satellite database are never as good as accurate ground measurement.  And the rather narrow variation observed is due to past calibration of satellite derived model with data from weather stations.  The reality can be different when it comes to Ireland. 

The solar sector is currently experiencing a rapid development in the Republic of Ireland, making the yield assessment and by extension the solar resource estimation key for the bankability of the projects.

The aim of our work was the validate the accuracy of different databases, available in Ireland.

The first step of this analysis will be to qualify our data sources. Everoze and Brightwind have access to measurement campaigns from multiple solar projects in Ireland. All the gathered dataset will be processed, applying state of the art quality control, to retain only trustable information.  The quality check will also include the sensors themselves, with a verification of the accuracy and calibration certificates of the different pieces of equipment.

In a second step, the qualified datasets will be used to compare satellite derived data.  We plan to use CAMS, SolarGIS and Meteonorm.  The intention is to categorise our results in regions, classified based on the difference in annual irradiation between different databases in order to reduce uncertainty – and ultimately boost investor confidence in energy yield assessments.