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Solar Panel Company Efficiency Analysis

Project Overview

In the renewable energy sector, efficiency is everything. I partnered with a solar panel company to analyze installation performance across regions, factoring in weather conditions, terrain, and panel specifications. The goal was to optimize energy output, reduce maintenance costs, and improve ROI.

The project involved modeling how tilt, orientation, and sunlight exposure affected performance across hundreds of installations. Using Excel, I built regression models to quantify these relationships. Power BI was used to visualize energy generation, installation costs, and degradation patterns, enabling stakeholders to make data-driven decisions about deployment and maintenance.

Data Preparation & Exploration

Using Excel, I cleaned and structured the dataset, which included:

  • Energy output logs
  • Installation metadata (panel type, location, angle)
  • Weather data (sunlight hours, temperature, humidity)
  • Maintenance records and cost breakdowns

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    I performed exploratory analysis to uncover:

  • Regional variations in energy yield
  • Correlations between environmental factors and panel degradation
  • Patterns in maintenance frequency and downtime
  • ROI timelines across different installation types

    • This work helped define KPIs such as energy efficiency, cost recovery rate, maintenance frequency, and regional ROI.

    Dashboard Development & Visualization

    With Power BI, I built dashboards tailored to different teams:

  • Efficiency Map: Comparing energy output across regions
  • ROI Tracker: Visualizing cost recovery and profitability
  • Maintenance Predictor: Forecasting service needs based on performance dips

    • Each dashboard featured dynamic filters, trend lines, and predictive alerts to support weekly planning and long-term strategy.

    Key Insights & Strategic Recommendations

    The analysis revealed several high-impact findings:

  • Coastal installations had higher corrosion rates, reducing long-term efficiency
  • Optimal tilt and orientation improved energy yield by 15 percent
  • Predictive maintenance reduced downtime and extended panel lifespan
  • ROI varied significantly by region, guiding future deployment strategy

    • These insights informed engineering protocols, maintenance schedules, and investment decisions.

    Operational Impact

    The project delivered measurable improvements:

  • Improved energy output by 20 percent
  • Reduced maintenance costs by 30 percent
  • Enhanced sustainability and profitability
  • Provided a data-backed roadmap for future installations

    • Collaboration & Workflow

    I worked closely with cross-functional teams:

  • Engineering: To refine installation protocols and optimize panel placement
  • Operations: To schedule preventive maintenance and reduce service disruptions
  • Finance: To model ROI and budget future deployments

    • Dashboards were used in weekly planning meetings to align strategy across departments and track performance metrics.

    Lessons Learned

  • Environment matters: Weather and terrain have a major impact on performance
  • Preventive action saves money: Predictive maintenance is more cost-effective than reactive fixes
  • Data drives sustainability: Smart modeling leads to greener, more profitable outcomes