Impact of Data Quality on Renewable Energy Potential Estimations

TL;DR

This study compares land use data sources for renewable energy potential estimations, develops scenarios for wind and solar potentials, and provides a validated, accessible database to improve consistency in energy planning.

Contribution

It highlights the impact of data source choice on potential estimations and offers a comprehensive, validated database for renewable energy potential analysis in Germany.

Findings

Corine Land Cover overestimates potential areas by factor of 4.6-5.2

Developed scenarios for wind and photovoltaic potentials

Published a validated, accessible database for energy modeling

Abstract

Potential analyses identify possible locations for renewable energy installations, such as as wind turbines and photovoltaic arrays. The results of previous potential studies, however, are not consistent due to different assumptions, methods, and datasets. In this study, we compare commonly used land use data sources with regard to area and position. Using Corine Land Cover leads to an overestimation of the potential areas in a typical wind potential analysis by a factor of 4.6 and 5.2 in comparison to Basis-DLM and Open Street Map, respectively. Furthermore, we develop scenarios for onshore wind, offshore wind, and open-field photovoltaic potential estimations based on land eligibility analyses and calculate rooftop photovoltaic potential using 3D building data. The potential capacities and possible locations are published for all administrative levels in Germany in the freely accessible database trep-db, for example, to be incorporated into energy system models. The investigations are validated using high-resolution regional potential analyses and benchmarked against other studies in the literature. Findings from the literature, which can be used by legislators to design regulation, are rarely comparable and consistent due to differences in the datasets used.