How to improve solar asset performance
Solar development is increasing rapidly, with approximately 19 GW installed in the U.S. in 2020 according to PV Tech, over a 40% increase from 2019. There are no signs of slowing down either, with most projections of deployment in 2021 exceeding 2020 totals.
With so many projects to choose from, owners and investors are increasingly scrutinizing the performance of their assets and potential acquisitions, which directly links to their profits. In many cases, small investments can potentially be made to increase performance of their assets. But to do so effectively, asset owners need to know the cause of system underperformance.
Our team is working with project stakeholders to narrow down the large culprits of underperformance with operating asset reviews. Such reviews can also be used by asset owners, potential buyers, or financing entities to hold operations and maintenance (O&M) providers responsible, produce new P50 production estimates for refinance or sale, or quantify potential losses to investors and other equity partners.
Develop a model
By helping project stakeholders correlate the operating conditions of a project to the expected performance at each time interval, underperformance can be quantified and categorized. Starting with the original financing model, we utilize the on-site SCADA system to adjust the model to actual operational conditions of the project and develop a forecasted production during the period of interest.
The model will then undergo an initial tuning process based on these conditions and known operational outages such as availability or curtailment losses. After this initial tuning, the tuned forecasted production can be compared to actual production and periods of misalignment can be identified. The question that the model is designed to answer is why this misalignment exists.
The goal is to solve this problem analytically, utilizing operating reports, discussions with on-the-ground staff, verification of site weather conditions with third party data, and statistical analysis to diagnose the causes and potential solutions for project underperformance.
Review the data
We recently worked on a project, located in an island community, that was performing below expectations. Through detailed review of weather data measured on site, energy production data, and tracker positioning data, we were able to identify and investigate specific causes of system underperformance. We found imperfect tracking during backtracking hours, leading to a potential 0.5% loss. This was likely due to the tracking system not being effectively optimized at installation to account for the existing terrain.
In this example, correction of the issue required minimal labor and equipment costs yet resulted in an estimated 0.5% additional production and improved project revenue. We also analyzed the impacts of clipping due to sub-hourly changes in irradiance, which was not considered standard modeling practice at the time of financing. Without material design changes, sub-hourly clipping is not generally considered recoverable. However, understanding the specific cause of the underperformance allowed the project owner to reset on certain performance expectations and improve future generation forecasts and operating metrics. By showcasing techniques that can be utilized across their entire operating portfolio, we helped the asset owner to identify underperformance that O&M providers may not be reporting or even catching themselves.
In a second example, we supported a project owner with a detailed review of two operating projects in the western U.S. Utilizing regression analysis, we reviewed the operating data for signals of proper tracker performance. At one site, we noticed several months during which the performance oscillated from poor to strong. We saw two distinct alignments during these periods: one in the morning hours, which displayed poor performance, and one in the afternoon hours when performance was strong. Using only energy production and weather data, we were able to identify daily trends in tracker performance that were causing energy losses.
We also reviewed inverter performance on a peer-to-peer basis to identify patterns of unavailability and underperformance. The project owner understood that there were some losses on site that were speculated to be from inverter or stringing issues, and we identified specific inverters for further investigation by field technicians.
We also utilized measured soiling data to determine a daily soiling rate for the project. Using more than 20 years of historical precipitation data at the project location, we re-projected estimated P50 soiling losses, which were nearly double those assumed in the original P50 financing generation estimates. This allowed the client to reevaluate the economics of the existing washing schedule and improve soil monitoring on site.
Identify project underperformance
Within the solar industry, undiagnosed project underperformance is causing headaches for stakeholders. With appropriate analysis, causes of underperformance can usually be identified and often require minimal capital investment to correct or improve. Underperformance may be the result of systems design choices or uncharacterized losses in establishing production models. In these cases, options to improve production may be limited, but improved models still allow for critical knowledge for stakeholders to monitor, operate, and invest in projects.
