An Artificial Intelligence‐Based Framework to Accelerate Data‐Driven Policies to Promote Solar Photovoltaics in Lisbon

Abstract

Due to the unavailability of up‐to‐date and georeferenced information about Lisbon’s existing solar energy systems, tracking the progress of solar energy adoption in relation to the city’s Climate Action Plans 2030 is a complex task, thus hindering the potential of data‐driven decision making for a targeted and tailored implementation of photovoltaics (PV) in buildings and urban infrastructure. To overcome the challenges posed, an integrated approach to accelerate policy‐making based on artificial intelligence (AI) resources and local citizens and stakeholders participation has been developed and piloted in Lisbon. By creating an information provision test‐policy aiming towards the mapping of PV installations in the city, a 2‐step AI model was set up to identify, geolocate and derive spatially resolved KPIs to inform policy‐makers about the evolution of PV deployment in the city and contribute to tailor future incentives to more depressed or energy poor districts. The AI model based on open data orthophotos from 2016 allowed estimates for the installed peak power at city level, in that year, to be delivered in a few minutes, whereas manual inspection of aerial images would have taken several months. Although the PV capacity determined is 30% lower than the historical official numbers, the proof of concept for the proposed data‐driven framework for PV policies promotion was achieved and validated by local stakeholders.This article is protected by copyright. All rights reserved.