In this document
We will explain how you, a Solargis Monitor user, can leverage Solargis Evaluate to enhance your asset performance analyses.
As an asset manager, you rely on Solargis Monitor for high-precision, near-real-time data to track the solar resource and theoretical power production of your PV portfolio. While Solargis Monitor provides the necessary data streams, understanding the drivers behind a plant’s actual performance often requires a more detailed technical representation of the asset.
By utilizing Solargis Evaluate, our advanced design and simulation platform, you can supplement your monitoring workflow with detailed modeling to conduct a more thorough performance analysis.
Typical use cases
Establishing a realistic performance baseline
A common challenge for operators is seeing yields that are consistently lower than the projections made during the design phase. This often occurs when the initial baseline was created using tools or assumptions that may have overestimated the yield. When your reference point is overly optimistic, performance evaluations will show negative deviations that do not necessarily reflect technical faults.
Recalculating your baseline within Evaluate provides a more realistic target for your asset. This ensures that your Performance Ratio (PR) and other key performance indicators (KPIs) reflect the actual technical health of the plant based on its specific configuration and local conditions.
Solargis Evaluate achieves this by using a sophisticated simulation chain that includes 3D backward raytracing and detailed electrical models. This technical representation allows for a more accurate simulation of how the specific plant components will perform in their actual environment.
Detailed loss analysis through system modeling
While Solargis Monitor provides the data used to identify production drops, Solargis Evaluate helps you investigate the underlying causes by modeling the system's technical characteristics. Although there are limitations to modeling highly complex layouts, Evaluate allows you to create a representative model of your asset to better understand environmental and technical impacts.
Detailed system modelling is essential when deciding on operational interventions, such as adjusting cleaning cycles or investigating hardware-specific issues. This geometric modeling identifies losses that standard monitoring data alone cannot fully explain.
By recreating the site's geometry - including row spacing and terrain - you can analyze how near shading impacts Global Tilted Irradiation (GTI) throughout the year. The simulation also allows you to isolate specific categories of energy loss, such as soiling losses, snow losses, and inverter power limitations known as clipping.
Benchmarking yearly production with long-term degradation
Performance assessment is a dynamic process due to PV power plant's efficiency changing over time. To accurately evaluate an operational asset, the baseline must also account for the age of the equipment.
Solargis Evaluate allows you to generate high-level yearly expected yield figures for the current year of your plant's life. By comparing your measured operational data against a simulation that considers these year-on-year losses, you can determine if the plant is performing as expected for its current lifecycle stage considering the expected PV module degradation.
Solargis Evaluate models long-term degradation for up to 25 years into the future. It takes the historical long-term average of the PV power production (PVOUT) and applies the degradation specified for the PV modules used in the design to predict yearly PVOUT - as illustrated in Figure 1 below. Note, however, that these figures are a projection into the future only and do not consider specific meteorological conditions in any particular year.
Figure 1: Example Solargis Evaluate calculation of expected yearly production considering long-term degradation
Benchmarking time series with long-term degradation
If you require more detailed benchmarking than high-level yearly figures, the degradation can be applied manually with more detail in post-processing. In this time series-based analysis, you simulate the period under review (e.g., the past calendar year) in Solargis Evaluate using the actual weather input data and then apply the degradation to the simulated time series of PVOUT.
By following this guide, you can analyze your PV power plant's performance with extreme precision. Furthermore, you can "drill deeper" by using extra simulation parameters to analyze only the DC power output, which filters out the impact of the AC part of the power plant.
The process begins by using the Energy System Designer to create a digital model of your plant with technical specifications from the PV Components Catalog.
You then run the simulation using 15-minute Solargis Time Series data to represent the actual weather sequences experienced by the plant for the period under review.
After exporting the simulated energy system data, you use an analytical software (such as Solargis Analyst) to apply the expected degradation to derate the PV power output. See the section below for a short guide to calculating the derated time series.
Calculating the derated time series manually
To manually derate the time series, you estimate the percentage of nominal power lost due to degradation for the time period you are analyzing. Typically, modules are assumed to degrade 0.8% in the first year and 0.5% in each subsequent year, but you can use your own figures based on information from the PV module manufacturer. The yearly derating coefficient Cd in the nth year, assuming the 0.8% and 0.5% degradation rates, is calculated as:
The monthly derating coefficient Cdm for the kth month after the start of the operation (but after the first year of operation):
The actual power Pact would then be calculated from the nominal power Pnom as:
In Solargis Analyst you can use the Calculator tool to calculate the actual power from the simulated PVOUT by applying the derating coefficient to the year or month of Time Series you are analyzing. Note that the coefficient will be different for each year or month of operation, and therefore this analysis must be done on a yearly or monthly basis.
Note: The real effect of PV module degradation on the output AC power is complex due to non-linearities in the power conversion process, such as clipping losses. Modeling long-term degradation requires approximations, and the analysis described above should not be expected to yield values exactly matching measurements.
Depending on the focus of your analysis, you should use different parameters from the Solargis Evaluate simulation. For instance, use the PVOUT_DC_THEOR parameter for investigation of the degradation effect on the DC output of the PV modules only, and the PVOUT_AC_GRID parameter for investigating the final power delivered to the grid.