4.7 Article

Solar Energy Communities: An open data and georeferenced based modelling framework to pre-assess deployment potential at urban level

Journal

ENERGY
Volume 282, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2023.128838

Keywords

Electricity demand; Energy communities; Solar PV potential; Open -data GIS tool

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This study presents an innovative approach to estimate the potential of solar community deployment at the urban level, using an open and georeferenced-based modeling framework. The assessment is performed based on photovoltaic solar potential, buildings, and families' characteristics data. The results show that the availability of rooftop area and the number of dwellings influence the deployment of photovoltaic systems. The study also found that there are no significant economic differences when comparing energy communities at the city-block scale to single average buildings.
With the ongoing transition to renewable and decentralized energy systems, energy communities are anchoring the increase of prosumerism, specially in urban environment.This work presents an innovative approach by creating an open and georeferenced-based modelling frame-work to pre-assess the potential of solar communities' deployment at urban level, based on three layers of data: photovoltaic solar potential, buildings and families' characteristics. This framework also compares community outputs at different scales: from building to city-block scale. The assessment is performed in economic and environmental terms, and was tested for three different neighbourhoods in Lisbon, Portugal.Results: show that for communities established at building level, the ratio of available rooftop area versus number of dwellings will dictate if photovoltaic deployment should take the total available area or just a fraction of it. Further, no great economic differences in percentage terms are found when comparing energy communities at city-block scale to a single average building. When implementing net-zero energy building approach, self-sufficiency rates stabilize in 34-40%, and discounted paybacks from 8 to 16 years are found. Finally, this methodological framework is dependent on availability of open data, being more suitable for urban environ-ments where data is more populated and accurate.

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