Performance of Solar Power Plant Based on ERA5 Data

This simulation is modelling the potential energy output of a solar power plant located in Okres Louny, Czech Republic. Simulation is based on historical meteorological data from the ERA5 reanalysis dataset to determine an energy production estimates over a year. This kind of simulation can help potential investors into solar power plants - both households as well as commercial entities to calculate feasibility of installation of the solar power plant based on potencial energy production and their electrical power consumption.

Methods

Simulation is created using Monte Carlo method.

Technologies used were Python 3.12 for downloading and processing ERA5 GRIB data and Microsoft Excel for running the Monte Carlo simulation.

Workflow

1. Data downloading and processing

ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 8 decades. Data is available from 1940 onwards. It provides hourly estimates for a large number of atmospheric, ocean-wave and land-surface quantities one of which is 'surface solar radiation downwards'. Data were thus downloaded from ECMWF public archive of ERA5 using ECMWF CDS API and Python in GRIB data format.

The data was then processed using 'xarray' and 'pandas' library into CSV file containing columns 'valid_time,latitude,longitude,ssrd_j,ssrd_wh' where valid_time is date and time of row entry, latitude and longitude is geographical location to which this data corresponds, ssrd_j is value of surface solar radiation downwards in J/m^2 and ssrd_wh is value of surface solar radiation downwards in Wh/m^2. ssrd_wh was computed from ssrd_j by multiplying this value by 0.000277777778 (1 J = 0.000277777778 Wh).

2. Excel data aligning

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References

Czech Educational and Scientific Network (CESNET). (n.d.). ERA5. Metacentrum Documentation. Accessed on: 1st December 2024. Accessible at: https://docs.metacentrum.cz/related/collgs/era5/

Copernicus Climate Change Service, Climate Data Store, (2023). ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.adbb2d47. Accessed on: 1st December 2024. Accessible at: https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels

Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023). ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.adbb2d47. Accessed on: 1st December 2024. Accessible at: https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels

Panasonic. (2022). Evervolt(R) 360K Specification Sheet. EVERVOLT(R) SOLAR MODULE BLACK SERIES. Accessed on: 1st December 2024. Accessible at: https://ftp.panasonic.com/solar/evervolt/evervolt_black_series_datasheet.pdf

Photovoltaic-software.com. (2024). How to calculate the annual solar energy output of a photovoltaic system?. In Photovoltaic-software.com. Acessed on: 1st December 2024. Accessible at: https://photovoltaic-software.com/principle-ressources/how-calculate-solar-energy-power-pv-systems

Šalamon, T. & Svatoš, O. (2024). Lectures for 4IT496 Simulations of Systems. Faculty of Informatics and Statistics University of Economics and Business Prague. Accessed on: 1st December 2024. Accessible via document server in InSIS (insis.vse.cz)

Wikipedia contributors. (2024). Monte Carlo method. Wikipedia, The Free Encyclopedia. Accessed on: 30th December 2024. Accessible at: https://en.wikipedia.org/w/index.php?title=Monte_Carlo_method&oldid=1262423747