Remote Monitoring of Solar Farm

Sun is the most abundant source of energy on the Earth. Solar energy is free to capture and easily available during daytime throughout the globe. Tapping this source of energy in an efficient manner is utmost important in order to produce usable energy for large masses. In today’s world, the best Mono Crystalline solar cells can convert at the most 23% of the input Solar Energy to DC Output Power. Typical PV Cells have an efficiency of 17% to 18% which is nominal.

Our Solar Farm Monitoring Dashboard is a complete solution for monitoring and maintenance of Solar Farms located in different geographical regions. The Dashboard fetches real-time information of each Solar Farm and displays them in Interactive Graphs which can be drilled down further to the Panel Level.

Each Solar Farm consists of an array of Solar Panels placed in series to generate power to large masses. IoT Sensors to capture Temperature and input Solar Irradiance falling on the Panel is collected. Using these details, we can calculate the theoretical DC Power Output and electrically measure the actual DC Power Output from the Panel.


Dashboard: Remote Monitoring of Solar Farm

Building Smart Solutions

Solar Farm Map Locations:

This Section shows the Solar Farms being monitored currently. The Farm marker shows a high level overview of the farm as to how much DC Output Power / Energy was generated on the previous Day and AC Output Power / Energy converted from DC, whether the Farm has any alerts like Panel Efficiency degraded severely and needs to be replaced or if Ambient temperature is very high for power generation. We can select any farm by clicking the marker and the Analytical data for that selected farm gets loaded on the Dashboard.

Edge Data Collection
Remote Monitoring
Actual vs Ideal Cycle Statistics
Preventive Maintenance

Edge Data Collection:

  • Sensors installed at the farm level captures the Average ambient temperature for the whole farm and sends an alert on the dashboard if the ambient temperature reaches the threshold.
  • Sensors capture the panel DC Output Current and calculates the Power output and sends an alert if the generated output power is very low compared to the ideal Power Output.
  • All the parameters from the Panels and the Farm is collected and stored in AWS Dynamo DB.

Remote Monitoring:

  • Using the real-time data, we can monitor all the panels remotely and based on the alerts we can identify if any repairs are necessary for panels having issues.
  • If panels are irreversibly damaged, then we can notify it to be replaced in the next maintenance window.
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Preventive Maintenance:

  • Warnings and Alerts are notified to the responsible people in real-time.
  • Thereby decreasing the turnover time if the issue needs to be rectified.
  • Downtimes are reduced as the alerts are captured almost instantly.
  • Periodic Maintenance can be planned and executed in a smooth manner based on the historical performance of the Solar Panels in the farm avoiding sudden downtime.
  • Reduce overall maintenance cost by efficiently planning the activity economical use of maintenance personnel.

Actual Vs Ideal Productivity:

  • Admins can have a quick look at the current productivity of the Solar Farm and easily gauge if there is a noticeable gap between the ideal and actual productivity like the Theoretical and Measured DC Output Power of the Panels.
  • If the gap is considerable large, we can drill down and find the reason for the low efficiency based on different parameters like weather in the particular region, input Sunlight Irradiance, Temperature of the Panel beyond the threshold thereby decreasing the efficiency of the PV cell.


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Disclaimer: I am the author at PLM ECOSYSTEM, focusing on developing digital-thread platforms with capabilities across CAD, CAM, CAE, PLM, ERP, and IT systems to manage the product data lifecycle and connect various industry networks. My opinions may be biased. Articles and thoughts on PLMES represent solely the author's views and not necessarily those of the company. Reviews and mentions do not imply endorsement or recommendations for purchase.