Empirical EV Load Model for Distribution Network Analysis
Electric vehicles (EVs) have introduced new operational challenges for distribution network service providers (DNSPs), particularly for voltage regulation due to unpredictable charging behaviour and the intermittent nature of distributed energy resources (DERs). This study focuses on formulating an...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/18/13/3494 |
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| Summary: | Electric vehicles (EVs) have introduced new operational challenges for distribution network service providers (DNSPs), particularly for voltage regulation due to unpredictable charging behaviour and the intermittent nature of distributed energy resources (DERs). This study focuses on formulating an empirical EV load model that characterises charging behaviour over a broad spectrum of supply voltage magnitudes to enable more accurate representation of EV demand under varying grid conditions. The empirical model is informed by laboratory evaluation of one Level 1 and two Level 2 chargers, along with five EV models. The testing revealed that all the chargers operated in a constant current (CC) mode across the applied voltage range, except for certain Level 2 chargers, which transitioned to constant power (CP) operation at voltages above 230 V. A model of a typical low voltage network has been developed using the OpenDSS software package (version 10.2.0.1) to evaluate the performance of the proposed empirical load model against traditional CP load modelling. In addition, a 24 h case study is presented to provide insights into the practical implications of increasing EV charging load. The results demonstrate that the CP model consistently overestimated network demand and voltage drops and failed to capture the voltage-dependent behaviour of EV charging in response to source voltage change. In contrast, the empirical model provided a more realistic reflection of network response, offering DNSPs improved accuracy for system planning. |
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| ISSN: | 1996-1073 |