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Reasons for solar power systems underperformance

image credit: https://pixabay.com/fr/photos/oiseau-crow-plumage-black-gray-4922622/

At first sight, it might seem that solar farms give the less maintenance headache to the operators among other renewables. One might think: “The solar panels are relatively cheap and easy to replace”; “There are no rotational parts” and “The sun will always shine”. In fact, inefficient maintenance operations in a solar farm make up for over 25% of the overall O&M costs. They could be significantly reduced by implementing the latest predictive maintenance solutions and as a result, reduce downtime and production loss. 

However, the lion’s share of production loss in solar energy comes not from the unplanned downtime, but from underperformance issues.   

To maximize energy production and the long-term revenue of solar farms it is crucial to identify small problems as early as possible. One damaged cell in one solar array counts as cents per kWh but the math over the life of the module can grow up to tens of thousands of Euros. Therefore, solar panel degradation should be always tracked and analysed in order to detect if a panel is producing less energy than it should.  

But why do some solar strings underperform? 

There are numerous reasons for that, starting from snow coverage during the wintertime, for example in Russia and Kazakhstan, and coming to the hidden reasons that require more efforts from operators to be detected. It could be, for instance, a broken connector, problems with inverters, a configuration of a string, etc. 

First things first. The solar strings should be set up correctly, ensuring that all available sunlight is being captured and converted. Each solar farm has its individual optimal azimuth that depends on the solar farm’s latitude. If the angle of PV modules is not optimal, it leads to tilt and orientation losses. They can take up to 4%. 

Once the solar farm is set up in an optimal and smart way, there are other things that can prevent capturing the maximum sunlight. It could be snow, dirt and debris (soiling), plants, and products excreted by birds. Just soiling itself has a huge range of 2% to 25% loss, depending on the geographical location of a farm. 

Losses can also appear at the next stage when the direct current produced by a solar farm is converted into alternating current by the inverter. These losses are represented by mismatch loss, wiring losses, light-induced degradation, connection losses

Speaking about inverters, they also make their contribution to solar farms underperformance. The amount of direct current might be greater than the amount of power that the inverter can convert, so the inverter will operate in a non-efficient way. 

Luckily, modern solar farms are smart and they have numerous sensors to collect the data. This data can be used by software applications to simulate system performance and maximise energy production

Discussions

Matt Chester's picture
Matt Chester on Sep 2, 2020

Luckily, modern solar farms are smart and they have numerous sensors to collect the data. This data can be used by software applications to simulate system performance and maximise energy production. 

Collecting that data is just the first step-- how do you think that data can best be used? Might there be AI/ML solutions in the works? Predictive maintenance? 

Dana Sultanova's picture
Dana Sultanova on Sep 2, 2020

Yes, there are solutions in the market to analyse this data, but the majority show indicative and static information. Only a few companies work with real-time data and provide predictive maintenance. For instance, at ANNEA we collect data from all the available sensors and drones images (when available), weather forecasts, etc. Then we use AI/ML combined with physical modelling to automatically detect and predict any underperformance event and its root-causes. Not all underperformance can be eliminated but a high percentage of it. From our experience, we can optimize solar farm's energy production up to 10%.

Dana Sultanova's picture

Thank Dana for the Post!

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