Achieve Peak
Efficiency with Solar
Data Analytics
Intelligent solar energy
analytics for prediction and forecasting.
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Did You Know?
The use of big data analytics in the
energy sector is rapidly growing
- In 2022, the market was worth $7.5 billion
- By 2031, it’s expected to grow to $19.31 billion
- That’s a growth rate of 11.08% each year
This growth shows how energy companies are increasingly relying on data-driven insights to improve efficiency, reduce costs, and drive innovation.
Advanced Solar Data Analytics Services
Detect Complex Solar Photovoltaic
- Insights Into Energy Patterns: Get detailed understanding into energy generation and consumption.
- Unified Data Dashboard: Collect data from multi-energy portfolios in a single dashboard.
- Underperforming Components: Visualize underperforming solar plants inverters, strings or sensors.
Artificial Intelligence for Longevity
- Maintenance Forecasting: Automate maintenance alerts based on predicted vs actual energy levels data.
- Plant Inspections: Schedule plant checks to uplift solar energy production.
- Inventory Management: Optimize spare parts inventory using predictive demand analysis.
- Fault Prevention: Prevent unexpected breakdowns, minimize repair costs and lengthen the lifespan of solar installations via predictive maintenance approach.
Billing Dashboards with Real-Time Data
- kWh Produced and Estimated kWh: Provide transparent billing on kilowatt-hours (kWh) produced based on historical data.
- Invoice Amount: Automated invoicing screens with detailed breakdowns of costs, including usage charges, tariffs, etc, fostering trust between solar providers and consumers.
- Customer Payments: Track incoming payment statuses and send payment reminders to customers.
- Invoice Aging: Prioritize follow-ups by categorizing outstanding invoices based on their aging period such as 30 days, 60 days, etc.
Solar Sales Analytics
- Lead Conversion Rate: Track the effectiveness of your solar sales pipeline by monitoring conversion rates at each stage.
- Customer Acquisition Cost (CAC): Study spending across sales and marketing channels to lower CAC without compromising lead quality.
- Customer Lifetime Value (CLV) Prediction: Use historical analytics to estimate the long-term value of each customer.
Solar Operations Analytics
- Project Operations Analytics: Monitor if the solar project is adhered to its planned schedule for timely resource allocations.
- Installation Analytics: Dataplatr's solar analytics monitoring platform gathers and stitches data at every stage of the installation process for 360 degree visibility into project timelines.
- Supply Chain Analytics: Avoid delays due to stockouts and reduce excess inventory by analyzing inventory levels and supply chain data to ensure timely availability of components.
Our Proven Solar Energy Data Analysis
Framework
Aggregation of performance data from panels, inverters, and weather sensors.
Gather HR data from various systems (Core HR, payroll, performance, etc.).
Consolidate data into a unified platform.
Consolidate data into a unified platform.
Refinement of raw data elimination outliers, missing data for accuracy before
analysis.
Use historical data to predict solar energy output and optimize planning.
Early identification of issues like equipment failures using advanced analytics
tools.
Insights into performance data to improve system efficiency and reduce operational
costs.
From Traditional Metrics to Advanced KPIs
Advanced KPIs
Real-Time Production vs. Expected Output
Anomaly Detection Rate
Carbon Offset Metrics
Customer Satisfaction Index
Predictive Maintenance Accuracy
Energy Forecasting Accuracy
Traditional KPIs
Total Energy Generated (kWh)
Equipment Uptime/Downtime
Capacity Utilization
System Availability
Return on Investment (ROI)
Energy Yield (kWh/kWp)
Our Clients