PV plant performance analysis at string level is one of the most in-depth reviews that can be undertaken through remote, online monitoring – going far beyond what SCADAs can reach. Whilst this sort of analysis is not uncommon in itself, at QE we have been able to automate the process through IT solutions in order to be able to apply it as often as is required and across entire portfolios. This tool has been developed on a visually intuitive platform, allowing for interactive visualisation and insights.
A major benefit of strict string monitoring is that it allows faults at PV plants to be tracked right from their inception in the DC field, meaning that they can be discovered more quickly and that their locations can be more accurately identified. Faults such as disconnected strings, hot spots and burnt cells, dust and shadows due to overgrown grass or weeds, isolation issues and Riso faults, clipping, peak power/nominal power rate issues, underperformance due to panel temperature, broken panels or diode issues and open circuits or open DC fuses can all be detected using this analysis. Followed up correctly, this can lead to production losses being significantly minimised.
QE’s Performance Analysis Tool at String Level enables the evaluation of string currents and string voltages against reference values for specific periods of time. This allows us to evaluate patterns, deviations and tendencies of strings in order to analyse behaviours and underlying faults.
A major benefit of strict string monitoring is that it allows faults to be tracked from their inception in the DC field, meaning that they can be discovered more quickly and that their locations are more accurately identified.
The results are then presented in Power BI, an interactive and visually intuitive platform, making the accurate scrutiny of problem areas possible. This all leads to a level of control over vast amounts of actionable data that does not exist in the market and that is a real differentiator in modern back office and asset management practices. The picture below shows the main dashboard of the string analysis tool that QE has developed for this purpose.
Once potential issues are detected through string analysis, they are followed up by our engineers initially and then escalated to our legal team if contractual enforcement becomes necessary. Initially, QE would use string analysis results to plan and focus site visits so that our operations managers prioritise the inspection of suspected problem areas.
This may lead to the confirmation of defects – such as Riso faults – at site, which would be notified to QE’s legal team who would be then able to enforce EPC defect warranty provisions where sites have not yet reached Final Acceptance. As well as EPC issues, results may reveal that O&M operators have not been undertaking their maintenance activities, for example, where shading on panels is discovered due to a lack of cleaning or vegetation maintenance. This would also typically be followed up by our legal team, who would seek to enforce O&M obligations.
Digging deeper into PV plant data leads to higher levels of vigilance and control over the assets that we manage.
String analysis forms one part of QE’s larger VEIL project which comprises the extraction, transformation and loading of data from different sources. Crucially, this process results in the normalisation of data, which, once clean and complete, can be combined and used as the basis for calculations and in order to visualise all aspects of a given portfolio.
VEIL allows us to hone in on what is important from large sets of data in terms of outlier analyses, rankings, tendencies, trends and more. Both contractor and asset performance can be evaluated if the right data is available. Analytical exercises can go into great amounts of detail – for example, where QE know the exact models of all key components, reference values from each manufacturer can be introduced into the study. Raw data from SCADA is also immensely valuable in this process – this allows for a broad variety of parameters to be measured including string current, voltage current, ambient and panel temperature, DC power, AC power, irradiance etc, all of which can facilitate the deep technical analysis that a PV Plant requires.
Our experience at QE has been that digging deeper into PV plant data leads to higher levels of vigilance and control over the assets that we manage, and that is why we continue to invest time and resource in developing this aspect of our work.
If you would like to speak to us about this, or any related matter, please contact QE’s Head of Engineering, Irene Reyes, via the enquiries section of our website.
This article is written and edited by Shirine Azzi. She can be contacted at: firstname.lastname@example.org