Probabilistic and Time-Series Analysis of the Combined Impact of Electric Vehicles and Photovoltaic Systems on Voltage Profiles in a Real Low-Voltage Distribution Network |
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E. Simonič(1), K. Sredenšek(1,2), J. Počivalnik(1), D. Kuhar(1), B. Stergar(1), K. Zupanc(3), S. Seme(1,2) 1. Faculty of Energy Technology, University of Maribor 2. Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia 3. Elektro Gorenjska, Kranj, Slovenia
2026-06-27 |
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Abstract
The increasing integration of electric vehicles and photovoltaic systems significantly affects voltage conditions in low-voltage distribution networks. This paper presents a probabilistic assessment of their impact on voltage profiles in a real low-voltage feeder. A Monte Carlo-based framework is employed to progressively allocate electric vehicle chargers and photovoltaic systems across network nodes and to quantify the probability of voltage violations under critical operating conditions, including peak load and maximum solar radiation. Based on a predefined probability threshold, representative integration levels are selected for detailed weekly time-series simulations. The results indicate that moderate integration levels remain within acceptable limits, whereas higher deployment of electric vehicles and photovoltaic systems substantially increases the risk of undervoltage and overvoltage, particularly at electrically distant nodes. Furthermore, the temporal distribution of electric vehicle charging is shown to significantly influence voltage performance, with regulated charging strategies mitigating critical voltage deviations. The findings highlight the importance of combining probabilistic and time-series analyses for hosting capacity assessment and provide practical insight into integration limits and operational measures in real low-voltage networks.Key words: photovoltaic systems, electric vehicles, distribution networks, voltage profiles, Monte Carlo simulation.
Published in: Renewable Energies, Environment
& Power Quality Journal (REE&PQJ) |
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| ISSUE: Vol. 26. No.3 | Pages: 367-372 |
| E-ISSN: 3020-531 X | Date of Current Version: 2026-06-27 |
| REF: 348-26 | Issue Date: 2026-07-15 |
| DOI:10.24084/reepqj26-348 | Publisher: AEDERMACP/ EA4EPQ |
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