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MerCo Publishing Inc.
525 Route 73 N, Suite 104
Marlton, NJ 08053

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Quality over quantity: solar PV monitoring data

By Gwendalyn Bender

As the global installed base of solar PV capacity expands, project owners, asset managers, and operators are consistently breaking new ground. The majority of operational utility-scale sites are less than 10 years old, which means there are still unknowns when it comes to managing the demands of long-term operations on installed equipment.

The good news is that with the increasing amount of data available, PV owners and investors are able to analyze and optimize their operations more effectively than ever before.

Of the many reasons to take advantage of these capabilities, perhaps the most important is to enable performance enhancement, for instance by separating the impact of weather on production from that of equipment. This allows a plant to proactively identify and correct performance issues-with an impact on day-to-day returns.

As the market for secondary acquisitions grows, plant data also helps facilitate the evaluation of a solar power plant by a potential buyer or for bank refinancing. Similarly, changes to feed-in tariffs in some countries have led to a need for owners and operators to perform detailed liquidity analyses and assess if they will be able to meet debt service during low irradiation months. In this case, the historical performance of the plant is a more relevant indicator of future performance than the theoretical P50 forecast data.

Recording performance data can also make it easier to meet regulatory requirements, as regulators often require the storage of specific datasets to prove compliance with national or federal energy regulations. Operators may also wish to track revenue loss and potential compensation for lost output events, and these will need to be documented in detail and stored for a considerable period of time.

Finally, while it may be some years down the line for many operators, the requirement to re-power or add storage to assets is undoubtedly on the horizon. In such cases, having detailed historical performance data is critical for making sound engineering and financial decisions.

What, then, are the key data sources available? First and foremost for solar PV plants is the PV monitoring system. This displays data captured from the many measuring devices at a solar plant and produces large amounts of performance data, while providing a vast array of fault detections and other alarms.

In addition to this performance data, however, the industry is increasingly looking at parallel datasets to validate existing datasets or correct for missing or erroneous data. Independent weather data is therefore increasingly a key input, as it can validate measurements from on-site pyranometers or provide an alternative source of information when a weather station is not available at a plant. Pyranometers are often considered the best tool for assessing site conditions; however, their accuracy is highly dependent on the type of equipment used and how well it is maintained.

In addition, extreme weather conditions, such as heavy snow or hail, can have a detrimental effect on the performance of measurement equipment. Independent data feeds are therefore of great importance in either validating or correcting on-site irradiance measurements. These data feeds also provide a baseline for comparison across multiple projects or projects that use different measurement equipment, allowing evaluation across a portfolio for weather-adjusted performance.

Satellite-derived solar irradiance data is the industry standard. However, this data can come from a variety of other sources with variations in quality, price, and availability.

Project operators will therefore need to consider whether suppliers can offer data coverage across entire existing portfolios, and whether they can guarantee that data will be reliably available all year round.

A further critical dataset for many asset management activities is a plant's utility data. This can sometimes be hard to obtain, depending on the territory or utility involved, and is the reason why in certain markets these datasets are being offered by third-party providers in an easily digestible format.

Detailed field information is another important data source, and one whose benefits are often overlooked or undervalued. Field technicians on the ground are usually closer to actual operations and frequently provide a high level of insight. Their experience can prove invaluable in allowing operators to improve or safeguard the plant's performance long before monitoring systems detect a potential problem.

Following the assessment of the available data sources, and the selection of those most suitable, the next step is to ensure that the quality of data being collected is as high as possible. This will be significantly improved if operators have a data validation process in place.

This could, for instance, involve the comparison of two similar datasets, such as inverter data against utility meter data, with automated algorithms or manual validations. However, regardless of the method, the process should be auditable, such that there is a record of what changes were made and the reason for making them, who made the changes, and what data source was used.

As the quantity of data available to PV plant owners and operators increases, the focus must now be on the quality and site-suitability of that data-since its application will be crucial to optimizing performance, unlocking O&M cost savings, and creating investment-grade assets that deliver long-term power and profitability.

Gwendalyn Bender is the Product Manager for Energy Services at Vaisala (www.vaisala.com), a global leader in weather measurements and services for weather impacted business.