Calculating Operational Patterns for Electric Vehicle Charging on a Real Distribution Network Based on Renewables’ Production
Open accessAbstract
The connection of electric vehicles to distribution networks has been an emerging issue of paramount importance for power systems. On one hand, it provides new opportunities for climate change mitigation, if electric energy used for charging is produced from zero emission sources. On the other hand, it stresses networks that are now required to accommodate, in addition to the loads and production from distributed generation they are initially designed for, loads from electric vehicles charging. In order to achieve maximum use of the grid without substantially affecting its performance, these issues have to be addressed in a coordinated manner, which requires adequate knowledge of the system under consideration. It is advantageous that electric vehicle charging can be controlled to a certain degree. This research provides better understanding of real distribution networks’ operation, proposing specific operational points through minimizing electric vehicle charging effects. The probabilistic Monte Carlo method on high performance computers is used for the calculations.
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Model-based real grids can study the impact of low carbon technologies on a specific area or neighborhood, but this approach limits the representative character of the case studies.
“These grids can be used to study the impact of low carbon technologies on a specific area or neighborhood, however this approach limits the representative character of the case studies.”
From Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids (2019) · cites this paper as [17]
The Introduction describes modelling electric-vehicle charging on a real distribution network, and Section 5 says the resulting patterns are unique to each line. This supports studying a specific grid, but the paper does not say that using real grids limits how representative case studies are. Section 2 instead calls its network a representative rural distribution network; page numbers were not available in our copy. (LLM, conf=0.82)
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- Authors
- Lazarou, S., Vita, V., Christodoulou, C., & Ekonomou, L.
- Affiliations
- School of Pedagogical and Technological Education (GR)
- Corresponding author
- Ekonomou, Lambros
- Venue
- Energies
- Publisher
- MDPI AG
- Published
- 2018-09-11
- Volume
- 11
- Issue
- 9
- Pages
- 2400
- ISSN
- 1996-1073 (ISSN-L)
- OpenAlex
- W2891542143
- Cited by
- 25
- References
- 24
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 4 · 2022: 3 · 2021: 6 · 2020: 2 · 2019: 4 · 2018: 2
- FWCI
- 1.34
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Energies (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- ASPETE-School of Pedagogical and Technological Education (DECA)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Keywords
- electric vehicle charging, distribution networks, renewable energy generation, charging scheduling, grid impact of EV charging, distributed generation
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