Data Science, advanced analytics, and digital tools
In the framework of our firm commitment to R&D and innovation, and in line with our mission of providing the best service to our clients, we have developed a series of innovative Data Science and Machine Learning tools that allow to efficiently analyze and manage the data received from our clients’ solar PV projects.
There is an increasing amount of data available from PV assets and data science, advanced analytics tools are essential to elaborate a correct interpretation of this information. The input drawn from these analyses constitutes a powerful strategic tool to guide our clients’ decision-making processes and maximize their return on investment.
Advanced Performance Analytics Application (A-PAA)
Our Advanced Performance Analytics Application (A-PAA) tool enables our technical experts to perform a more detailed and faster analysis of the long-term performance of PV assets.
A-PAA provides unique insight using Machine Learning and Data Science techniques and supports our consultants’ analysis to detect underperformance and to protect the present and future value of the assets with:
- Identification of recoverable unavailability and systemic underperformance
- Detection of periods of Point of Interconnection (POI)/ Point of Common Coupling (PCC)-level and inverter-level downtime and quantify the lost energy
- Calculation of long-term average annual degradation
- Calculation of a site-specific daily soiling rate
- Calculation of realistic soiling losses based on the production data of the asset
- Calculation of actual AC losses between the inverter and Point of Interconnection (POI)/ Point of Common Coupling (PCC)
- Interactive visualizations that can show performance from a high-level annual view down to the highest granularity available
- Direct comparisons to P50, and Weather-Adjusted P50 from both an energy and performance ratio perspective
The Enertis Applus+ Soiling and Snow Application (TESSA)
This web-based soiling calculator follows the Kimber and Townsend models to accurately estimate the annual loss in power due to dirt, snow, and/or other particle accumulation on the surface of PV modules.
Being able to accurately estimate a PV project’s soiling rate allows for practical decision making – like when and how often to schedule cleanings – to maximize the investment rate of return (IRR).
TESSA’s features include:
- Parameters for both snow and dirt
- Weather datasets up to 20 years pulled from the National Oceanic and Atmospheric Association (NOAA) and the Spanish State Meteorological Agency (AEMet)
- Annual, monthly, and daily soiling rates
- Precipitation effects
- Map view to compare projects with nearby NOAA stations
- Multi-project viewing to compare portfolios at a glance
- Non-U.S. clients can utilize the tool with a pre-existing TMY file