A Systematic Open Source Modeling Method for Energy and Power Systems: Solar PV Application

Open source modeling has emerged as a transformative paradigm in energy and power systems studies by enabling transparent, reproducible and collaborative development of tools and models. However, limited access to high-resolution, localized input data restricts the accuracy and contextual relevance of many models, especially in regions with diverse climatic and infrastructural conditions. This paper introduces a novel, systematic Open Source Modeling Method for Energy and Power Systems (OSM-MEPS). Derived and synthesized from foundational steps outlined in modeling literature, OSM-MEPS is grounded in first-principles thinking, the scientific method and the engineering design process frameworks, ensuring technical rigor, empirical validation and adaptability. To demonstrate effectiveness, OSM-MEPS guided the modeling and simulation of a solar photovoltaic (PV) system using high-resolution weather and irradiance data for the year 2024 from Solcast-DNV. At the Serres-C site in Greece, OSM-MEPS model results achieved a strong fit with real-world solar PV energy data (MAE: 469.57 kWh, RMSE: 584.62 kWh, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>: 0.887), outperforming PVLIB (MAE: 1,400.39 kWh, RMSE: 1,526.11 kWh, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>: 0.232). Seasonal testing showed similar results: in May 2024, the OSM-MEPS model achieved <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>: 0.917 vs. PVLIB’s –0.039; in December, it maintained <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>: 0.873 vs. PVLIB’s 0.638. Geographic validation demonstrated generalizability. In Pretoria, the OSM-MEPS model outperformed PVLIB (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>: 0.443 vs. –0.239); in Adelaide, it maintained accuracy (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>: 0.866) while PVLIB failed (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i><sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>: –0.959). In Kisumu, both models had low correlation despite matching MAE (0.88 kWh), due to data gaps and limited shading metadata. A rooftop energy feasibility study was carried out in Njagu-Mhasibu-Ruiru Estate in Kenya, based on a solar PV installed capacity of 8.75 kW. The OSM-MEPS model predicted an annual yield of 14,329 kWh/year, compared to PVLIB’s estimate of 10,048 kWh/year and the GSA reference of 12,784 kWh/year. Overall, the results confirm that the OSM-MEPS method and its resulting model are robust and adaptable tools for high-resolution solar PV energy modeling across diverse geographic regions and weather conditions.