After explaining Condition-based maintenance last week, this week we will be shedding light on the topic of Predictive maintenance of a solar PV site.
The provision of a Preventive Maintenance strategy is emerging nowadays as an essential field to keep high technical and economic performances of solar PV plants over time. Analytical monitoring systems have been installed therefore worldwide to timely detect possible malfunctions through the assessment of PV system performances.
At a solar PV site, many things can go wrong to cause the actual performance to deviate from the expected performance. If failures and/or unanticipated degradation issues go undetected, they will lead to reduced energy generation (and associated electricity credits) and/or potential loss of component warranty because of manufacturer turnover. if an individual cell of a single panel is compromised, the power output and efficiency of the entire system is reduced. Unfortunately, without taking performance measurements, it is not possible to identify and assess these issues. Furthermore, considering the turnover of solar energy industry component manufacturers, quickly responding to potential warranty issues is key to optimizing return on investment. If failures and/or unanticipated degradation issues go undetected, this will lead to loss of energy generation (and associated electricity credits) and/or potential loss of component warranty because of manufacturer turnover. Given the size of the problem and gaps with current solutions, we propose that PV system owners need an unbiased third-party off-the-shelf system-level predictive maintenance tool to optimize return-on-investment and minimize time to warranty claim in PV installations.
A monitoring solution like TrackSo helps you in executing maintenance by monitoring your solar PV assets as it provides real-time data, error and anomaly detection, visual analysis of data through charts and graphs. This helps in maintaining the health and conditioning of your PV assets as well as helps take measures required for optimum output. All the real-time data collected along with historical data can be easily extrapolated and used for prediction of upcoming scenarios and hence indicate problems even before they occur.
In summary, predictive maintenance has the following advantages:
- Reduced component repair and replacement costs
- Reduced revenue loss owing to downtime
- Focussed O&M activity
- Better inventory management
- Improved component longevity owing to better operational practices
In the current power economy where the performance of renewable energy assets is key to its project feasibility and future investment, predictive maintenance is the way to go…
