Identifying and Addressing Underperforming Solar Assets
Inside this Article
PV is a constantly evolving global industry. Equipment, tools and vendors are continuously entering or exiting the market. Codes change. Weather fluctuates. Tariffs are imposed. In spite of these challenges, the costs to build and operate PV assets have generally been shrinking relentlessly. To keep pace with this market and mitigate risks without cutting corners, stakeholders need to have regular and robust O&M practices in place at the portfolio level.
In this article, we provide insight into maintaining a healthy portfolio of assets by identifying and remediating performance problems on the dc side of the PV system. We base the lessons learned, case studies and recommendations on observed data from a fleet of several hundred PV assets, ranging in capacity from 200 kW to 300 MW, deployed in different climates and across the continental US.
The adage that “you can’t manage what you can’t measure” holds true for solar assets. To understand asset health, you need an analytics platform that leverages multiple data streams and sources—such as performance models, remote site data, satellite irradiance, preventative and corrective maintenance logs, and financial metrics—so that you can analyze individual assets, specific asset groups or the collective fleet.
This analytics platform is the foundation of any effort to understand asset health and identify underperforming assets. An increasing number of vendors offer case-by-case or fleet-level analytic services. While it is beyond the scope of this article to elaborate on the process of creating or evaluating an analytics platform, the International Electrotechnical Commission (IEC) has published a suite of technical standards that relate to PV system performance monitoring (IEC 61724-1), capacity evaluation (IEC 61724-2), and energy evaluation (IEC 61724-3).
Consider key performance indicators across the entire fleet. The benefit of a robust analytics platform is that it allows stakeholders to track and compare key performance indicators (KPIs) over time, looking for trends and outliers. While many metrics and methods are useful for monitoring asset health, stakeholders can learn a lot simply by monitoring a handful of KPIs, such as baseline performance index (BPI), performance index (PI), weather-corrected performance ratio, yield and availability. When used together, these five KPIs provide powerful insights regarding underperforming asset identification. (See “PV System Energy Test Evaluations,” SolarPro, October/November 2014.)
Baseline performance index. BPI is a basic metric that evaluates the measured plant output in relation to its predicted output (BPI = measured output ÷ predicted output). While this analysis is useful for understanding asset performance relative to a financial model, it is less useful for O&M purposes since it does not consider actual weather conditions. A site with 10% of its capacity offline could have a BPI of 100% because the weather is 10% sunnier than average.
Performance index. PI evaluates asset health by comparing the measured output to the expected output (PI = measured output ÷ expected output). Using the expected output rather than the predicted output corrects for weather. In the aforementioned scenario, a site with 10% of its capacity offline would show a PI of 90%, which would flag the site for investigation. The accuracy of the PI value is closely tied to the accuracy of the underlying performance model and the weather data used by the model. Even high-quality weather data can hold several percentage points of uncertainty. The more distributed a fleet and the smaller the individual projects, the more challenging it becomes to obtain clean irradiance data with minimal uncertainty. Regardless of this uncertainty, PI provides valuable information about asset health.
Weather-corrected performance ratio. This performance indicator compares a plant’s actual energy production to its theoretical energy-generating potential and describes how efficient a PV power plant is in converting sunlight incident on the PV array into ac energy delivered to the utility grid. While you can use performance ratio (PR) values to compare PV power plants in different locations, it is important to correct these results for weather bias. The authors of the NREL technical report “Weather-Corrected Performance Ratio” define a way to modify PR calculations to help reduce weather bias.
Yield. Specific yield evaluates PV plant performance by comparing its total annual energy output to its nameplate capacity rating (yield = kWhac ÷ kWpdc). This metric is useful for making a levelized comparison or peer-to-peer evaluation of PV assets, as it allows stakeholders to flag underperforming assets without needing to account for weather. It is especially powerful in sites with many generation blocks because you can compare the performance of each block side by side and look for outliers. At sites with multiple array orientations, you can normalize yield to account for different azimuth or tilt angles.
Availability. This metric is important because it characterizes the percentage of time that a PV power system is generating energy. As detailed in the Sandia report “A Best Practice for Developing Availability Guarantee Language on Photovoltaic (PV) O&M Agreements,” there are many ways to calculate availability. To identify underperforming assets, we recommend calculating and comparing the raw component availability, which quantifies the percent of time that an inverter generates energy during daylight hours without any exclusions. Contractually focused availability metrics often exclude periods of downtime and therefore provide less useful detail for understanding plant performance.