Copernicus for Commercial Assessments of PV Installations
The Energy Challenge
Accurately predicting the energy yield generated by a specific solar photovoltaic (PV) energy system over the course of a system’s lifetime (20+ years) can be a challenge. A multitude of variables such as solar irradiation, shadow effects, and even temperature and wind speeds impact the electricity generated. In turn, inaccuracies in the yield lead to under- or overestimations of the return on investment.
In addition, uncertainties on the energy market, related both to the price of electricity, and the price at which surplus electricity is sold back to the grid, has made this challenge even more prevalent for financial institutions.
This has driven Raiffeisen Bank to seek a solution able to generate accurate forecasts of electricity yield and investment returns that can be used to assess the commercial viability of a PV installation in any location in Czechia.
Solution powered by CAMS and C3S
The team at Paris-based ARMINES have developed a state-of-the art solar yield estimation solution powered by Copernicus data, including CAMS for solar radiation data and C3S for inputs on variables like wind speed and temperature. This web-based application allows the user to select any area or rooftop in Czechia, select the PV technology foreseen to be used, and generate an accurate forecast of the power produced in a typical meteorological year. The solution furthermore considers shadow effects, coming from nearby trees or buildings, to further increase the accuracy. As a second step, the solution enables the user to select the type of building (commercial shop, household, factory, etc.) to generate an estimated yearly power consumption profile. These insights are combined with the solar PV production forecasts to estimate how much of the generated electricity is consumed by the building, and how much is considered surplus (which may be sold back to the grid or stored in a battery). To assess the commercial viability of such a system, the team at Evenflow have developed a financial model that uses production and consumption data to provide insights on the return on investment by estimating capital and operational expenditures, accounting for government subsidies, various financing options, and more. This enables the user to immediately understand the commercial viability of the selected system, and understand how each variable (e.g. loan interest rates, PV panel efficiency, grid buyback prices, etc.) impacts the return on investment over the course of the system’s lifetime.
About Copernicus CAMS and ERA5
The Copernicus Atmosphere Monitoring Service (CAMS) offers comprehensive solar radiation time-series data, spanning from 2004 to the present. These datasets are available globally for clear-sky conditions and (within specific satellite fields of view) for all-sky conditions, with temporal resolutions ranging from 1 minute to monthly intervals.
Complementing this, the ERA5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) provides high-resolution temperature and wind speed data. ERA5 delivers hourly estimates of atmospheric variables, offering a detailed representation of weather patterns over time. Utilizing both CAMS solar radiation data and ERA5 temperature and wind speed data enables precise modelling of PV system performance.
Key Outcomes and Next Steps
The implemented demonstration showcased the capabilities of a CAMS and C3S-powered solution to assess the commercial feasibility of a solar PV installation anywhere in Czechia. This proof-of-concept highlights how freely available EO technologies can decrease the financial risks associated with renewable energy investments at small and larger scales.
Following the success of this pilot project, Raiffeisen Bank, ARMINES and Evenflow are exploring the potential to operationalise this solution within Czechia and beyond. This collaboration underscores how innovative use of space data can decrease risks associated with the financing of renewable energy assets and support the green transition.
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