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  4. Power Generation Time Series for Solar Energy Generation: Modelling with ATlite in South Africa
 
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March 7, 2025
Journal Article
Title

Power Generation Time Series for Solar Energy Generation: Modelling with ATlite in South Africa

Abstract
The global energy landscape is experiencing growing challenges, with energy crises in regions such as South Africa underscoring the drive to accelerate the shift toward renewable energy solutions. This paper presents an approach for improving solar energy planning, specifically focusing on leveraging the capabilities of the ATlite software in conjunction with custom data. Using mathematical models, ATlite (which was initially developed by the Renewable Energy Group at the Frankfurt Institute for Advances Studies) is a Python software package that converts historical weather data into power generation potentials and time series for renewable energy technologies such as solar photovoltaic (PV) panels and wind turbines. The software efficiently combines atmospheric and terrain data from large regions using user-defined weights based on land use or energy yield. In this study, European Centre for Medium-Range Weather Forecasts reanalysis data (ERA5) data was modified using Kriging to enhance the resolution of each data field. This refined data was applied in ATlite, instead of utilizing the standard built-in data download and processing tools, to generate solar capacity factor maps and solar generation time series. This was utilized to identify specific PV technologies as well as optimal sites for solar power. Thereafter, a simulated power generation time series was compared with measured solar generation data, resulting in a root mean square error (RMSE) of 19.6 kW for a 250 kWp installation. This approach’s flexibility and versatility in the inclusion of custom data, led to the conclusion that it could be a suitable option for renewable energy planning and decision making in South Africa and globally, providing value to solar installers and planners.
Author(s)
Botha, Nicolene  
Stellenbosch University, Council for Scientific and Industrial Research
Coleman, Toshka
Wessels, Gert  
Stellenbosch University, Council for Scientific and Industrial Research
Kleebauer, Maximilian  
Fraunhofer-Institut für Energiewirtschaft und Energiesystemtechnik IEE  
Karamanski, Stefan  
South African Council for Scientific and Industrial Research -CSIR-, Pretoria  
Journal
Solar  
Project(s)
Development and Demonstration of a Sustainable Open Access AU-EU Ecosystem for Energy System Modelling
Funder
Bundesministerium für Bildung und Forschung -BMBF-  
Open Access
DOI
10.3390/solar5010008
10.24406/publica-4363
File(s)
791_Volltext.pdf (6.97 MB)
Rights
CC BY 4.0: Creative Commons Attribution
Language
English
Fraunhofer-Institut für Energiewirtschaft und Energiesystemtechnik IEE  
Keyword(s)
  • ATlite

  • solar energy

  • energy system modelling

  • open source software

  • renewable energy planning

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