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Renewable Energy Site Selection using Artificial Intelligence and Geographic Information System

Project description

AI-based identification and development of optimal clean energy sites

Supported by the Marie Skłodowska-Curie Actions programme, the RESSAIG project aims at developing AI-powered solutions to streamline the identification of optimal sites for diverse renewable energy systems such as photovoltaic arrays, concentrated solar power (CSP) and onshore/offshore wind farms. By integrating deep learning, remote sensing, data from geographic information systems (GIS), and official datasets, the project will enable a more efficient and sustainable planning of energy. RESSAIG will reduce costs and development times while supporting the production of green hydrogen and accelerating the transition to low-carbon energy systems.

Objective

The RESSAIG project (Renewable Energy Site Selection using Artificial Intelligence and Geographic Information System) aims to enhance the identification and development of sites for clean renewable energy sources, such as photovoltaic (PV) arrays and both onshore and offshore wind farms. Utilizing a blend of Artificial Intelligence (AI), deep learning, remote sensing data, Geographic Information Systems (GIS), and government datasets, the project seeks to optimize site selection for renewable energy and water desalination necessary for hydrogen production.
Amidst the global shift towards sustainable energy solutions to combat climate change, there is an urgent need for more efficient and precise methods for identifying optimal sites for renewable energy installations. Traditional methods often overlook critical environmental, economic, and social factors that RESSAIG's integrative approach will consider, thus ensuring more sustainable and economically viable energy production.
The urgency for sustainable and low-carbon energy solutions is accentuated by increasing environmental concerns and international commitments to reduce carbon footprints. RESSAIG's advanced mapping technologies come at a crucial time to meet the growing demand for renewable energy infrastructure and support the transition towards green hydrogen as a key energy carrier for the future.
Our team brings together leading experts in AI, GIS, remote sensing, and renewable energy, uniquely positioning us to tackle this complex challenge. Our interdisciplinary approach combines cutting-edge technology with extensive field knowledge, enabling us to provide innovative solutions that are both scientifically rigorous and practically applicable.
RESSAIG enhances renewable energy site selection, reducing costs and driving investment through detailed cartographies and economic analyses, fostering informed decisions and promoting sustainability, economic growth, and job creation.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

(opens in new window) HORIZON-MSCA-2024-PF-01

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Coordinator

UNIVERSITA DEGLI STUDI DI TRENTO
Net EU contribution
€ 209 483,28
Address
VIA CALEPINA 14
38122 Trento
Italy
Region
Nord-Est Provincia Autonoma di Trento Trento
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data