Lagos State Rooftop Solar Potential Mapping

Note: You can access the repo here.

In Lagos State, Nigeria, sustainable energy solutions are crucial to addressing power supply challenges and reducing environmental impacts. The increasing adoption of rooftop solar systems requires accurate, data-driven insights into solar potential across various regions of the state.

Project Demo Video

Task

I set out to develop a detailed analysis and visualization of Lagos State's rooftop solar potential. My primary goal was to create a comprehensive dataset, clean it for analysis, and visualize actionable insights using modern data tools to support decision-making for stakeholders like policymakers, businesses, and individuals interested in solar energy adoption.

Action

1. Data Preparation:

   • Worked with a large dataset of approximately 1.5 million rows, containing geospatial and energy-related data.

   • Performed data cleaning and preprocessing in Python to handle inconsistencies, and null values effectively.

2. Analysis and Insights:

   • Identified key variables influencing solar potential, including rooftop area, solar irradiance, and geographical location.

   • Used Python libraries like pandas, numpy, and matplotlib for exploratory data analysis.

3. Visualization in Power BI:

   • Imported the cleaned dataset into Power BI to create dynamic dashboards showcasing Lagos State's solar potential at various granularities.

   • Integrated geographical map using Lagos State LGA geojson file and interactive visuals to highlight high-potential areas for solar installation.

4. Stakeholder Engagement:

   • Designed the dashboard to be intuitive and accessible, enabling stakeholders to filter data by region, building type, or estimated energy output.

Result

• Delivered an interactive, data-driven dashboard that visualizes Lagos State's rooftop solar potential in an actionable format.

• Empowered stakeholders to identify key areas for solar adoption, paving the way for increased renewable energy usage in Lagos.

• Demonstrated my ability to manage and process large datasets, integrate multiple data tools (Python and Power BI), and produce impactful insights.

Thanks for coming this far!