Team Name

SustainAI

Team Members

Project Description

Empower Australia's Renewable Future with SustainAI

SustainAI offers cutting-edge AI solutions to optimize site selection, forecast energy production, and enhance monitoring for wind and solar projects across the continent. Maximize efficiency, reduce costs, and accelerate Australia's transition to clean energy with our comprehensive suite of tools.

Key Features

1. Energy Forecasting

• Measure of available solar energy: Accurately predict solar energy availability based on environmental factors.
• Cloud cover: Cloud cover has a significant impact on solar panel efficiency, and our AI accounts for this in its forecasts.
• Temperature: Higher temperatures can reduce solar panel efficiency, and this is incorporated into our model.
• Historical performance of solar panels: Analyze and factor in historical data to enhance future predictions.

2. Site Selection

• Weather: Evaluate solar irradiance, cloud cover, and temperature to find the optimal location.
• Geographical location: Consider terrain and proximity to energy demand areas.
• Distance to human settlement: Optimize locations based on distance to populations and infrastructure.

3. Monitoring AI System

• Real-time Analysis: Continuously processes data from sensors and equipment to detect anomalies and anticipate potential failures.
• Proactive Maintenance: Schedules maintenance activities intelligently, minimizing downtime and reducing costs.

4. Visualization

Create graphical representations of complex data related to renewable energy systems, helping stakeholders to understand:
- Energy production: Interactive maps, charts, and 3D models for visualizing energy outputs.
- Consumption patterns: Clear insights into how energy is used across regions and timeframes.
- System performance: Detailed views of the status and efficiency of renewable systems.

Maximize your renewable energy potential with SustainAI!

Data Story

Renewable Energy Site Selection and Solar Potential Prediction

Dataset Information

We have utilized a dataset from Rosetta:

Link to Dataset

This dataset provides detailed information on renewable energy assets and projects across various regions in Australia, including:
- Asset type
- Site name
- Technology type
- Fuel type
- Geographical coordinates
- Associated organizations

Weather Information Integration

We have augmented this dataset with weather data for specific geographical locations (latitude and longitude). This includes:

• Solar Irradiance Data from NASA POWER:
  
  NASA POWER API

• Temperature Data from Open Meteo:
  
  Open Meteo API

These data sources allowed us to factor in essential environmental variables that impact the efficiency of solar power generation.

Methodology

Based on the combined dataset (energy assets and weather data), we have conducted the following analysis:

1. Solar Potential Prediction:

   • We used the integrated data to predict the solar potential for various locations in Australia. This prediction is based on factors such as solar irradiance and temperature.

2. Clustering of Sites:

   • We clustered the locations to identify optimal regions for solar energy projects. This allows for efficient energy production and resource management.

3. Visual Presentation:

   • The results are visually presented through interactive maps, heatmaps, and other visualization techniques, providing stakeholders with clear insights into potential solar energy locations.