Adapted Stochastic PV Hosting Capacity Approach for Electric Vehicle Charging Considering Undervoltage
This paper presents a stochastic approach to single-phase and three-phase EV charge hosting capacity for distribution networks. The method includes the two types of uncertainties, aleatory and epistemic, and is developed from an equivalent method that was applied to solar PV hosting capacity estimat...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-09-01
|
| Series: | Electricity |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4826/2/3/23 |
| _version_ | 1797519540705296384 |
|---|---|
| author | Enock Mulenga Math H. J. Bollen Nicholas Etherden |
| author_facet | Enock Mulenga Math H. J. Bollen Nicholas Etherden |
| author_sort | Enock Mulenga |
| collection | DOAJ |
| description | This paper presents a stochastic approach to single-phase and three-phase EV charge hosting capacity for distribution networks. The method includes the two types of uncertainties, aleatory and epistemic, and is developed from an equivalent method that was applied to solar PV hosting capacity estimation. The method is applied to two existing low-voltage networks in Northern Sweden, with six and 83 customers. The lowest background voltage and highest consumption per customer are obtained from measurements. It is shown that both have a big impact on the hosting capacity. The hosting capacity also depends strongly on the charging size, within the range of charging size expected in the near future. The large range in hosting capacity found from this study—between 0% and 100% of customers can simultaneously charge their EV car—means that such hosting capacity studies are needed for each individual distribution network. The highest hosting capacity for the illustrative distribution networks was obtained for the 3.7 kW single-phase and 11 kW three-phase EV charging power. |
| first_indexed | 2024-03-10T07:44:14Z |
| format | Article |
| id | doaj.art-23ea59006b814fd482ac1029f0f1eb6b |
| institution | Directory Open Access Journal |
| issn | 2673-4826 |
| language | English |
| last_indexed | 2024-03-10T07:44:14Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electricity |
| spelling | doaj.art-23ea59006b814fd482ac1029f0f1eb6b2023-11-22T12:46:48ZengMDPI AGElectricity2673-48262021-09-012338740210.3390/electricity2030023Adapted Stochastic PV Hosting Capacity Approach for Electric Vehicle Charging Considering UndervoltageEnock Mulenga0Math H. J. Bollen1Nicholas Etherden2Department of Engineering Sciences and Mathematics, Luleå University of Technology, 93187 Skellefteå, SwedenDepartment of Engineering Sciences and Mathematics, Luleå University of Technology, 93187 Skellefteå, SwedenDepartment of Engineering Sciences and Mathematics, Luleå University of Technology, 93187 Skellefteå, SwedenThis paper presents a stochastic approach to single-phase and three-phase EV charge hosting capacity for distribution networks. The method includes the two types of uncertainties, aleatory and epistemic, and is developed from an equivalent method that was applied to solar PV hosting capacity estimation. The method is applied to two existing low-voltage networks in Northern Sweden, with six and 83 customers. The lowest background voltage and highest consumption per customer are obtained from measurements. It is shown that both have a big impact on the hosting capacity. The hosting capacity also depends strongly on the charging size, within the range of charging size expected in the near future. The large range in hosting capacity found from this study—between 0% and 100% of customers can simultaneously charge their EV car—means that such hosting capacity studies are needed for each individual distribution network. The highest hosting capacity for the illustrative distribution networks was obtained for the 3.7 kW single-phase and 11 kW three-phase EV charging power.https://www.mdpi.com/2673-4826/2/3/23hosting capacityMonte Carlo methodsstochasticuncertaintyundervoltageelectric vehicle |
| spellingShingle | Enock Mulenga Math H. J. Bollen Nicholas Etherden Adapted Stochastic PV Hosting Capacity Approach for Electric Vehicle Charging Considering Undervoltage Electricity hosting capacity Monte Carlo methods stochastic uncertainty undervoltage electric vehicle |
| title | Adapted Stochastic PV Hosting Capacity Approach for Electric Vehicle Charging Considering Undervoltage |
| title_full | Adapted Stochastic PV Hosting Capacity Approach for Electric Vehicle Charging Considering Undervoltage |
| title_fullStr | Adapted Stochastic PV Hosting Capacity Approach for Electric Vehicle Charging Considering Undervoltage |
| title_full_unstemmed | Adapted Stochastic PV Hosting Capacity Approach for Electric Vehicle Charging Considering Undervoltage |
| title_short | Adapted Stochastic PV Hosting Capacity Approach for Electric Vehicle Charging Considering Undervoltage |
| title_sort | adapted stochastic pv hosting capacity approach for electric vehicle charging considering undervoltage |
| topic | hosting capacity Monte Carlo methods stochastic uncertainty undervoltage electric vehicle |
| url | https://www.mdpi.com/2673-4826/2/3/23 |
| work_keys_str_mv | AT enockmulenga adaptedstochasticpvhostingcapacityapproachforelectricvehiclechargingconsideringundervoltage AT mathhjbollen adaptedstochasticpvhostingcapacityapproachforelectricvehiclechargingconsideringundervoltage AT nicholasetherden adaptedstochasticpvhostingcapacityapproachforelectricvehiclechargingconsideringundervoltage |