Introduction to Aerial Inspections

PV systems present unique challenges to system operators, particularly since these systems are often physically large or distributed over a large geographic area. In utility applications, for example, a PV system may integrate 40,000 to 8 million individual modules along with the corresponding fuses, combiners and conductors. Portfolios of customer-sited PV systems, meanwhile, often include hundreds of distributed systems, many of which are roof mounted, each with its own set of components and site-access restrictions. The sheer scale of these systems and portfolios is inherently challenging for the system operators and asset managers tasked with monitoring and managing these assets and distributed fleets.

The relative inaccuracy of performance measurements and data analysis tools further compounds these issues. According to Sandia National Laboratories’ 2008 report, “Comparison of PV System Performance-Model Predictions with Measured PV System Performance,” the absolute accuracy of data modeling is on the order of 5%–10%, and the accuracy of relative measurements is on the order of 3%–5%. This means that site operators do not have visibility into any on-site performance issues that reduce system output by an amount lower than these margins of uncertainty. To address this lack of visibility, operators often rely on manual field tests—including I-V curve traces and thermal images captured with handheld infrared (IR) cameras—to locate defects within the array. Since these tests are labor intensive and costly, operators generally inspect only 10%–25% of the modules per site annually.

These combined factors mean that PV systems can incur undetected phantom losses, which reduce energy yield and economic performance. System operators can benefit from new methodologies and technologies for detecting system faults. Aerial inspections, which capture IR and visible imagery, approach this problem from an entirely new vantage point—namely, from the air.

Aerial Inspection Process

Manned aircraft, unmanned aerial vehicles or aircraft systems (drones), and even balloons are all potential platforms for the flyover component of an aerial inspection. The main factors influencing vehicle selection include inspection time, accuracy, repeatability and scalability. On one hand, aircraft with a pilot on board can inspect a PV system at a rate of 0.5 MW–1 MW per minute and do not require physical site access or regulatory approval for the flight plan. On the other, unmanned aerial vehicles (UAVs) have slower flying speeds, lower-resolution cameras and limited battery life; as a result, inspections with UAVs take more time and generally require multiple flights per site. A UAV inspection also requires physical site access and regulatory approval for the specific flight path.

Fault detection. Energy balance is the basic principle behind the thermal component of aerial inspections. Generally speaking, the surface of all the modules at a given site receive approximately the same amount of irradiance. Modules that are operating properly convert roughly 15%–20% of this incident energy into electricity. Those modules that are not operating properly convert that same energy into heat. The end result is that underperforming or nonperforming modules are warmer than the surrounding operational modules.

Aerial inspections provide system operators with IR measurements for all the modules in a roof- or ground-mounted PV system. These thermal images allow operators to precisely identify and map underperforming portions of the array. When properly implemented, an aerial inspection campaign can identify a wide range of dc fault mechanisms. As such, aerial inspections can largely replace manual dc measurements as part of an annual preventative maintenance scope of work. IR inspections can detect any fault mode that causes a significant decrease in module output.

Common faults. As shown in Figure 1, the most common fault modes in PV systems deployed with crystalline silicon (c-Si) modules include string-level failures, submodule failures and cell-level hot spots. String-level thermal signatures indicate some type of open-circuit condition, perhaps due to a blown or missing fuse, an open fuseholder or module interconnection, or a failure within a module or source-circuit conductor. Submodule thermal signatures, often involving 33% of the cells within a module, generally indicate that a bypass diode is engaged or has failed. Cell-level hot spots can reveal resistive losses within modules, perhaps due to cell cracking or solder joint deterioration.

Compared to c-Si PV systems, thin-film arrays generally have shorter source circuits and require more series strings for the same power capacity. As a result, aerial inspections tend to reveal relatively higher rates of string failures in thin-film systems. IR inspections of thin-film arrays can also identify isolated hot spots, major differences in module efficiency caused by differential degradation rates, or internal variations in thin-film deposition quality.

To complement the IR imagery, aerial inspections should also capture high-resolution images in the visible spectrum. These conventional aerial images can reveal the presence and distribution of soiling, locations or regions requiring additional vegetation control, physical damage to racking, site erosion, encapsulant degradation or discoloration, and so forth. As shown in Figure 2, investigators can correlate these datasets to add further insight into failure modes and allow more-accurate root cause analysis of failures.

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