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Evidence of Work

DIS_Solar

Project Info

Team Name


DIS


Team Members


Ivan

Project Description


We're using data to show how solar energy production could be optimised based of environmental factors such as temperature, irradiation levels and air pollution levels.


#renewable energy #solar energy

Data Story


As we played around with Rosetta's network map for renewable energy sources, solar panels and their distribution around Sydney caught our collective eye. Solar panels and solar energy have only recently become more cost-effective and powerful, meaning now is a great time to optimise solar panel placements for maximal solar energy production! The greatest obstacle in the way of finding optimal locations are environmental factors. Through hours of research, we've found that the most impactful factors of any given location include irradiation levels, air pollution and average temperature. We aim to find an intersection, and show optimal locations to place solar panels where irradiation levels are highest, air pollution is minimal and the average temperature is low.


Evidence of Work

Team DataSets

Peclet Technologies - LGA data

Description of Use We are searching for optimal locations for solar energy production pinpointing potential locations with Local Government Areas.

Data Set

BoM climate/temperature data

Description of Use In alignment with research on the effectiveness of solar panels, the average temperature of areas may have an impact on solar energy production. We're using this data, along with other data we have collected, to determine which areas are most suited to produce solar energy

Data Set

Air Quality NSW Government

Description of Use Since we are considering air pollution levels as one of the key contributing factors in the effectiveness of solar panels, this data is essential to the calculation of optimal locations

Data Set

Solcast API

Description of Use As we are considering irradiation levels as one of the key factors in the effectiveness of solar panels, this data is paramount to us calculating optimal locations

Data Set

Rosetta Renewable Energy Network Map

Description of Use We use this information to show how the existing grid may coincide with our predicted optimal locations for solar panel placement

Data Set

Challenge Entries

Renewable Energy Site Selection Model

How can we optimally position renewable energy projects across Australia to maximize efficiency, minimize environmental impact and integrate seamlessly into the existing grid?

Go to Challenge | 7 teams have entered this challenge.