Renewable Energy Site Selection Model

Participants are tasked with developing an algorithm or model to determine the best locations for renewable energy projects in Australia. Using the data and tools provided by the Network Map Renewables website, the challenge is to balance factors such as energy output, environmental impact, grid connectivity, and land use. This challenge requires innovative approaches that consider both technical and societal aspects to ensure the long-term sustainability of Australia’s energy future.

Participants are expected to deliver a comprehensive solution that includes a detailed report and a functioning algorithm or model. The report should outline the methodology, data sources, and criteria used in the decision-making process. The algorithm should be capable of analysing multiple variables, including geographical data, renewable energy potential, and existing infrastructure, to recommend optimal locations for new renewable energy projects. Creativity and innovation are highly encouraged, as the goal is to find solutions that are not only technically sound but also applicable in real-world scenarios. The solution should be presented in a format that allows for easy interpretation and implementation by stakeholders in the renewable energy sector.

Rosetta Analytics is dedicated to advancing sustainability through data-driven innovation. By supporting this challenge, we aim to empower the next generation of thinkers to contribute to the global transition towards renewable energy. Our commitment to diversity and inclusion ensures that a wide range of perspectives are brought to the table, fostering solutions that are both equitable and effective.

Datasets to Highlight

Data from the Network Map Renewables website, including spatial data on existing renewable projects, transmission networks, and environmental factors, serves as a base. This data is further enhanced by blending it with other publicly available datasets to provide a comprehensive view for analysis.


External Links
https://renewables.networkmap.energy
Datasets downloadable directly from the website.


Image Credit: CC BY-NC