2026-06-13T12:53:58Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/759142025-09-04T09:31:31Zcom_10324_1169com_10324_931com_10324_894col_10324_1363

Dávila Sacoto, Miguel 92e0c437-a324-449d-89e0-91cfc4a8ada1 600 González, Luis Gerardo 7b1f9fb6-3474-4c22-89f7-8c4d133daf70 600 Zorita Lamadrid, Ángel Luis c774bed1383ebe80 600 Espinoza, Juan Leonardo 1a433cad-f12c-43b2-8b1c-5766be970309 600 2025-06-09T10:13:13Z 2025-06-09T10:13:13Z 2025 Renewable Energies. 2025;3(1) 2753-3735 https://uvadoc.uva.es/handle/10324/75914 10.1177/27533735251342114 1 Renewable Energies 3 2753-3735 Producción Científica Simulating microgrids that incorporate electric vehicles and photovoltaic solar energy, along with their penetration levels, is a complex task that requires considering realistic grid parameters. This study presents an integrated simulation method using Python and OpenDSS, enabling researchers to analyze factors such as load curves, communication links, electric vehicle demand, photovoltaic generation, electric vehicle penetration levels, and connection event probability curves. Additionally, the software includes smoothing algorithms for solar radiation to mitigate voltage fluctuations. The simulation tool also allows for the evaluation of communication delays between the system aggregator and charging stations when modifying the charging setpoint at customer connection bars. The results indicate that communication delays significantly impact voltage stability at consumer connection points. Smoothing algorithms, such as the Savitzky-Golay filter, reduce voltage fluctuations by up to 8% in high PV penetration scenarios. Moreover, PV penetration levels around 0.6 were found to create the highest transformer loads, highlighting the need for adaptive control strategies. Voltage deviations at customer loads ranged from +1.5% to −3.2% depending on the delay time and PV penetration. application/pdf eng Sage Journals info:eu-repo/semantics/openAccess Ingeniería Eléctrica Microgrids, electric vehicle, high photovoltaic penetration, openDSS, python 3306 Ingeniería y Tecnología Eléctricas Effect of latency and charge control of electric vehicles in power grids with high penetration of photovoltaic solar energy info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://journals.sagepub.com/doi/full/10.1177/27533735251342114 SI THUMBNAIL davila-sacoto-et-al-2025-effect-of-latency-and-charge-control-of-electric-vehicles-in-power-grids-with-high-penetration.pdf.jpg davila-sacoto-et-al-2025-effect-of-latency-and-charge-control-of-electric-vehicles-in-power-grids-with-high-penetration.pdf.jpg IM Thumbnail image/jpeg 2325 https://uvadoc.uva.es/bitstream/10324/75914/3/davila-sacoto-et-al-2025-effect-of-latency-and-charge-control-of-electric-vehicles-in-power-grids-with-high-penetration.pdf.jpg 7c1b717c7cdf576520c7da4057bbde4a MD5 3 LICENSE license.txt license.txt text/plain 3929 https://uvadoc.uva.es/bitstream/10324/75914/2/license.txt 289d98c1665ee0d20312360f0e8643c8 MD5 2 ORIGINAL davila-sacoto-et-al-2025-effect-of-latency-and-charge-control-of-electric-vehicles-in-power-grids-with-high-penetration.pdf davila-sacoto-et-al-2025-effect-of-latency-and-charge-control-of-electric-vehicles-in-power-grids-with-high-penetration.pdf Artículo principal application/pdf 4555861 https://uvadoc.uva.es/bitstream/10324/75914/1/davila-sacoto-et-al-2025-effect-of-latency-and-charge-control-of-electric-vehicles-in-power-grids-with-high-penetration.pdf 70a0338f9c49ff9b4968f9813483eccd MD5 1 10324/75914 oai:uvadoc.uva.es:10324/75914 2025-09-04 11:31:31.515 UVaDOC repositorio@uva.es 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