CoChat
Sign Up
Cited by 52Electric Vehicles and InfrastructureSmart Grid Energy ManagementOptimal Power Flow Distribution

Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids

Open access
Spitzer, Martin, Schlund, Jonas, Apostolaki-Iosifidou, Elpiniki, Pruckner, Marco·2019·Energies
DOI 10.3390/en12214059
Open this paper in CoChat — free accountOpen PDF

Abstract

All over the world the reduction of greenhouse gas (GHG) emissions, especially in the transportation sector, becomes more and more important. Electric vehicles will be one of the key factors to mitigate GHG emissions due to their higher efficiency in contrast to internal combustion engine vehicles. On the other hand, uncoordinated charging will put more strain on electrical distribution grids and possible congestions in the grid become more likely. In this paper, we analyze the impact of uncoordinated charging, as well as optimization-based coordination strategies on the voltage stability and phase unbalances of a representative European semi-urban low voltage grid. Therefore, we model the low voltage grid as a three-phase system and take realistic arrival and departure times of the electric vehicle fleet into account. Subsequently, we compare different coordinated charging strategies with regard to their optimization objectives, e.g., cost reduction or GHG emissions reduction. Results show that possible congestion problems can be solved by coordinated charging. Additionally, depending on the objective, the costs can be reduced by more than 50% and the GHG emissions by around 40%.

AI snapshot

Written from the paper’s full text.

TL;DR

This paper models a representative European semi-urban low-voltage grid as a three-phase system and compares uncoordinated EV charging with cost-, valley-filling-, and GHG-optimized coordinated charging. It finds coordinated charging can resolve congestion, with cost optimization cutting weekly charging cost by 51.13% and GHG optimization cutting emissions by about 40% relative to uncoordinated charging.

Key findings

  • Uncoordinated charging at 30% EV penetration caused no voltage violations but current-limit exceedances of 15 and 120 min for light and heavy load, respectively; at 70% EV penetration in the heavy-load case, voltage violations occurred for 990 min and current-limit violations for 2400 min.
  • Phase imbalance matters: with evenly distributed EV connections the voltage unbalance factor stayed around 1%, but massing 70% of single-phase connections on phase R produced a peak VUF of 2.5%, exceeding the German 2% limit; worst-case phase R current reached up to 820 A versus a 420 A cable thermal rating.
  • Cost-optimized charging reduced weekly energy cost from 125.99 € to 60.05 €, a saving of 62.83 € or 51.13%, and lowered GHG emissions from 924.54 to 548.89 kg CO2eq, but current limits were still exceeded because EV charging remained phase-unbalanced.
  • Valley filling achieved the lowest average distribution losses, 0.636 kVA versus 1.332 kVA for uncoordinated charging, but had higher cost and GHG emissions (89.05 € and 890.85 kg CO2eq); GHG-optimized charging reached 517.50 kg CO2eq and 76.39 €, with ADL 1.105 kVA.

Methods

  • The study uses DSOO European semi-urban low-voltage grid #13: one transformer, 115 buses, and 108 consumers at 230 V, modeled as a three-phase quasi-steady system in MATLAB Simscape at 50 Hz. Scenarios are baseline (0% EV, 13% PV), 2030 (30% EV, 20% PV), and 2050 (70% EV, 33% PV); heavy load uses 78 single-family and 30 duplex homes, light load uses 108 single-family homes, and simulations cover one summer and one winter week at 15-min resolution.
  • EV data include manufacturer battery/charging specifications, a fleet proportional to German EV sales since 2010, SOC based on ADAC energy consumption including HVAC, and stochastic arrival/departure availability from Schlund et al.; household loads are synthesized, PV feed-in is generated for Erlangen, and electricity prices/generation come from SMARD.
  • Three coordinated charging strategies are optimized with perfect one-week foresight: cost minimization, valley filling via variance minimization, and GHG minimization. Constraints require full charging between arrival and departure, no charging when away, maximum charging rate, nonnegative charging, and for cost/GHG strategies a transformer limit; analysis criteria include ±10% voltage deviation, 420 A cable thermal rating, 2% VUF, PV self-consumption, and average distribution losses.

Limitations

  • The paper states that all charging strategies assume perfect foresight over a one-week horizon, EV usage data are sparse and based on a conventional-traffic survey, the ADL formula is only applicable to this specific case, and the transformer apparent power rating was omitted because cyclical loading allows short overloads.
  • The paper also notes that real-world systems cannot control which phase an EV connects to, and that GHG-minimal charging was economically infeasible in the studied week because low-carbon generation coincided with high electricity prices.
  • Evident from the text: results rely on one representative grid and selected summer/winter weeks, so broader generalizability is limited; the phase-unbalance and current-limit violations depend strongly on assumed phase distribution and EV placement.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.3390/en12214059

Cites

33 of 33 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

7 of 30 cited sources checked · 2 supported · 1 flagged · accuracy not yet measured

  • Premisecitation

    Many previous studies model the grid as a perfectly balanced three-phase system.

    “Many previous studies, such as [5,9,10], model the grid as a perfectly balanced three phase system.”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites [5] Lopes, 2011, Integration of electric vehicles in the electric power system, Proc. IEEE source
    • cites [9] Flammini, M.G., Prettico, G., Fulli, G., Bompard, E., and Chicco, G. (2017, January 15–16). Interaction of consumers, photovoltaic systems and electric vehicle energy demand in a Reference Network Model. Proceedings of the 2017 International Conference of Electrical and MISC Technologies for Automotive, Torino, Italy. source
    • cites [10] Richardson, P., Flynn, D., and Keane, A. (2010, January 25–29). Impact assessment of varying penetrations of electric vehicles on low voltage distribution systems. Proceedings of the IEEE PES General Meeting, Providence, RI, USA. source

      The cited paper does not model its grid as perfectly balanced. In Section IV (Results), it explicitly says it carries out unbalanced load-flow analyses and examines single-phase voltages because distribution networks typically have phase imbalance. (LLM, conf=0.92)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured
  • Premisecitation

    IEEE test feeder models are less suitable for EV impact studies because their design and data were published for specific issues.

    “These models are less suitable for EV impact studies as the overall design and data available were published for specific issues [14].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [14] Postigo Marcos, F., Mateo Domingo, C., Gomez San Roman, T., Palmintier, B., Hodge, B.M., Krishnan, V., de Cuadra García, F., and Mather, B. (2017). A review of power distribution test feeders in the United States and the need for synthetic representative networks. Energies, 10. source

      The paper’s limitations discussion (page unavailable) says some test feeders were designed for a single issue and can be unsuitable for other applications because relevant information is missing. It does not apply that limitation to IEEE test feeders as a group or specifically conclude that they are less suitable for EV impact studies; its example is a feeder for DG protection analysis. (LLM, conf=0.85)

      Experimental — accuracy not yet measured
  • Premisecitation

    The size of the network should be considered for reliable results because small-scale networks miss heterogeneity.

    “The size of the network should be considered in order to have reliable results because small-scale networks miss heterogeneity [14].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [14] Postigo Marcos, F., Mateo Domingo, C., Gomez San Roman, T., Palmintier, B., Hodge, B.M., Krishnan, V., de Cuadra García, F., and Mather, B. (2017). A review of power distribution test feeders in the United States and the need for synthetic representative networks. Energies, 10. source
  • Premisecitation

    Balanced three-phase approaches often omit voltage unbalances that occur between power lines in real-world systems, resulting in lack of representativeness.

    “These approaches often omit the voltage unbalances which occur between the power lines in real-world systems resulting in lack of representativeness.”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites [5] Lopes, 2011, Integration of electric vehicles in the electric power system, Proc. IEEE source
    • cites [9] Flammini, M.G., Prettico, G., Fulli, G., Bompard, E., and Chicco, G. (2017, January 15–16). Interaction of consumers, photovoltaic systems and electric vehicle energy demand in a Reference Network Model. Proceedings of the 2017 International Conference of Electrical and MISC Technologies for Automotive, Torino, Italy. source
    • cites [10] Richardson, P., Flynn, D., and Keane, A. (2010, January 25–29). Impact assessment of varying penetrations of electric vehicles on low voltage distribution systems. Proceedings of the IEEE PES General Meeting, Providence, RI, USA. source

      Section B, “Impact on Single-Phase Voltage Levels” (page unavailable), says phase voltages can differ substantially and that monitoring only at the three-phase supply level can miss a household-level voltage limit. This supports the concern about overlooking real phase unbalance, but the paper does not establish that balanced three-phase approaches often omit it or generally lack representativeness. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
  • Premisecitation

    Uncoordinated EV charging can cause considerable congestion in electrical networks, especially in residential areas.

    “Since drivers tend to change in times when electrical grids are already highly loaded, for example after going back home from work, EVs can cause considerable congestion in electrical networks [4,5], especially in residential areas.”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [4] Mu, 2014, A spatial–temporal model for grid impact analysis of plug-in electric vehicles, Appl. Energy source
    • cites [5] Lopes, 2011, Integration of electric vehicles in the electric power system, Proc. IEEE source
  • May combine two claims. 31
  • Classified as probably not a substantial claim. 9
  • The quote only partly states this claim. 1

  • May combine two claims.

    Premisecitation

    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.”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites [15] Richardson, 2012, Optimal charging of electric vehicles in low-voltage distribution systems, IEEE Trans. Power Syst. source

      The Distribution Network section describes a model based on a residential feeder in suburban Dublin, supporting the use of a real-area grid to study EV charging. The paper does not say that this approach limits how representative case studies are; the Residential Customer Load Modelling section instead checks whether its test network compares favourably with similar networks. Page numbers are unavailable in our copy. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [16] de Hoog, J., Thomas, D.A., Muenzel, V., Jayasuriya, D.C., Alpcan, T., Brazil, M., and Mareels, I. (2013, January 21–25). Electric vehicle charging and grid constraints: Comparing distributed and centralized approaches. Proceedings of the 2013 Power & Energy Society General Meeting, Vancouver, BC, Canada. source
    • cites [17] Lazarou, S., Vita, V., Christodoulou, C., and Ekonomou, L. (2018). Calculating Operational Patterns for Electric Vehicle Charging on a Real Distribution Network Based on Renewables Production. Energies, 11. source

      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)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Findingown data

    In the heavy load scenario with a 70% EV penetration rate, voltage violations occur for 990 minutes and current limit violations for 2400 minutes.

    “As for the heavy load scenario with a 70% EV penetration rate, voltage violations occur for 990 min and current limit violations for 2400 min.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: All consumers are either single-family homes or a mixture between single-family homes and duplex homes based on the evaluated scenario.
    • The authors state this as an assumption: The charging of the EV in the residential setting is only limited by the maximum charging rate of the vehicle.
    • The authors state this as an assumption: The grid has a tap changing transformer and the full voltage bandwidth can be used in the low voltage part of the network.

  • May combine two claims.

    Findingown data

    With an EV penetration rate of 30%, the current carrying capacity of the cable is exceeded for 15 minutes in the light load case and 120 minutes in the heavy load case.

    “The current carrying capacity of the cable is exceeded for 15, 120 min, respectively.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: All consumers are either single-family homes or a mixture between single-family homes and duplex homes based on the evaluated scenario.
    • The authors state this as an assumption: The charging of the EV in the residential setting is only limited by the maximum charging rate of the vehicle.
    • The authors state this as an assumption: The grid has a tap changing transformer and the full voltage bandwidth can be used in the low voltage part of the network.

  • May combine two claims.

    Findingreasoning

    SC is low for both cost and GHG optimizations.

    “The SC is low for both optimizations as the EV are mainly charged at night, and SC levels are in general low in winter.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: SC levels are in general low in winter.

  • May combine two claims.

    Findingown data

    The overall saving between UC and cost-optimized charging is 62.83 e or 51.13%.

    “The overall saving between UC and cost-optimized charging is 62.83 e or 51.13%.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In GHG-optimized charging, phase voltages exhibit nearly the same median value of around 0.96 pu, with almost equal inter-quartile ranges.

    “The phase voltages are exhibiting nearly the same median value of around 0.96 pu, furthermore are the inter-quartile ranges almost equal.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The medians of the phase currents lie at 226 A, and the whiskers are crossing the current-carrying limit.

    “The medians of the phase currents lie at 226 A, and the whiskers are crossing the current-carrying limit.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    SC is comparably low with 1.13% for the heavy load winter scenario, as the EVs are scheduled to charge predominantly at night.

    “SC is comparably low with 1.13% for the heavy load winter scenario, as the EVs are scheduled to charge predominantly at night.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Under GHG-optimized charging, 75% of all currents are below 300 A, but the 25% quantile reaches maxima of 469 A, 535 A, and 567.7 A for phases R, S, and T, respectively.

    “Moreover, 75% of all currents are below 300 A, but measurement 25% quantile reach a maximum of 469 A, 535 A, and 567.7 A, for phase R, S, and T, respectively.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingnone given

    VF provides the lowest ADL but results in comparatively high energy costs and GHG emissions.

    “VF provides the lowest ADL but results in comparatively high energy costs and GHG emissions.”
    • Also stated in: § 5. Outlook and Future Work · plain
      “The VF approach proved to be the best way to minimize network losses but has the disadvantage of comparably high GHG emissions and electricity costs.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The voltage limit is not exceeded with a median of 0.956 pu and whiskers reaching from 0.986 pu to 0.902 pu.

    “The voltage limit is not exceeded with a median of 0.956 pu and the whiskers reaching from 0.986 pu to 0.902 pu.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingreasoning

    Cost-optimized charging offers a 30% reduction in ADL, while GHG optimization offers only a 17% reduction in comparison to the UC scenario.

    “The cost-optimized charging offers a reduction of 30%, while GHG optimization only offers a 17% reduction in comparison to the UC scenario.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingnone given

    GHG emissions and electricity costs for EV charging are 890.85 kg CO2 eq and 89.05 e, respectively.

    “GHG emissions and electricity costs for EV charging are 890.85kg CO 2 eq and 89.05 e, respectively.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    In both cases, a balanced distribution of the households loads can be observed.

    “In both cases, a balanced distribution of the households loads can be observed.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingreasoning

    Due to a high coincidence between low GHG emissions and low energy prices, carbon emissions are almost halved, dropping from 924.54 to 548.89 kg CO2 eq.

    “Due to a high coincidence between low GHG emissions and low energy prices, the carbon emissions are almost halved, dropping from 924.54 to 548.89 kg CO 2 eq.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    GHG-optimized charging offers only a 5.6% reduction of emissions, at a cost increase of 26.29% in contrast to the cost optimized scenario.

    “The GHG-optimized charging offers only a 5.6% reduction of emissions, at a cost increase of 26.29% in contrast to the cost optimized scenario.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    For phase R, 75% of all voltage values lie above 0.945 pu, while for phases S and T the figures are slightly higher than 0.95 pu.

    “For phase R, 75% of all values lie above 0.945 pu, while for the phases S and T the figures are slightly higher than 0.95 pu.”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Findingown data

    In the case where 70% of single-phase installations are connected to phase R, the accumulation of connections to a single-phase leads to a violation of the limit for voltage unbalance.

    “In the second case, the accumulation of connections to a single-phase leads to a violation of the limit for voltage unbalance.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Some EVs are charging forenoon so that the small load valley between breakfast and noon is filled, but the majority of EVs are charging between 8:00 p.m. and 8:00 a.m. the next day.

    “Some EVs are charging forenoon so that the small load valley between breakfast and noon is filled, but the majority of EVs are charging between 8:00 p.m. and 8:00 a.m. the next day.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In a worst-case scenario (winter week, heavy load, 70% EV penetration), the rated power limit at the transformer is only exceeded for short periods and never reaches 130% of the rated power limit.

    “It shows that even in a worst-case scenario (winter's week, heavy load, and 70% EV penetration), the rated power limit is only exceeded for short periods and never reaches 130% of the rated power limit.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The cost-optimized strategy does not work as intended because EV charging is inherently unbalanced and the accumulation of EV charging on a single-phase leads to violation of the current-carrying limit, even when the apparent power limit is adhered.

    “As shown in the right box plot of Figure 9, this does not work as intended as EV charging is inherently unbalanced and the accumulation of EV charging on a single-phase leads to violation of the current-carrying limit, even when the apparent power limit is adhered.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: EV charging is inherently unbalanced.

  • May combine two claims.

    Findingown data

    Similar to the UC case, some current values violate the limits, and the distribution is wider, indicated by taller boxes and longer whiskers.

    “Similar to the behavior of the phase voltages in the UC case, some current values violate the limits, and the distribution is wider, indicated by taller boxes and longer whiskers.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The minimum voltage values for phase R lie at 0.875 pu with a number of outliers between 0.875 and 0.85 pu.

    “The minimum values lie at 0.875 pu with a number of outliers between 0.875 and 0.85 pu.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Cost optimization lowers energy cost by more than half and provides the lowest overall energy cost among the other optimizations.

    “The cost optimization lowers the energy cost by more than half and provides the user with the lowest overall energy cost among the other optimizations.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The cost optimized strategy is able to minimize the costs for electricity but leads to critical grid situations even with a constraint on the apparent power flow in place.

    “The cost optimized strategy is able to minimize the costs for electricity but leads to critical grid situations even with a constraint on the apparent power flow in place.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Uncontrolled EV charging load may be added to pre-existing peak load, overloading grid components such as transformers or causing poor power quality.

    “EV charging load when uncontrolled may be added to pre-existing peak load overloading grid components such us transformers or causing poor power quality [6].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [6] Apostolaki-Iosifidou, E., Woo, S., and Lipman, T. (2019, January 13–17). Challenges and Opportunities for Electric Vehicle Charging Detection Using Utility Energy Consumption Data. Proceedings of the Transportation Research Board Annual Meeting, Washington, DC, USA. No. 19-05695.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    EV owners tend to have an affinity for renewables and a high interest in using their residential PV installations to charge their EVs.

    “As mentioned above, EV owners tend to have an affinity for renewables and a high interest in using their residential PV installations in order to charge their EVs.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [32] Frenzel, I., Jarass, J., Trommer, S., and Lenz, B. (2019, October 22). Erstnutzer von Elektrofahrzeugen in Deutschland. Nutzerprofile, Anschaffung, Fahrzeugnutzung; Technical Report. Available online: https://elib.dlr.de/96491/.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The number of EVs worldwide could exceed 130 million by 2030 under the assumption that government policies continue supporting the expansion of electromobility.

    “According to the Global EV Outlook [3], the number of EVs worldwide could exceed 130 million by 2030 under the assumption that government policies continue supporting the expansion of electromobility.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [3] Bunsen, T., Cazzola, P., Gorner, M., Paoli, L., Scheffer, S., Schuitmaker, R., Tattini, J., and Teter, J. (2018). Global EV Outlook 2018: Towards Cross-Modal Electrification, International Energy Agency.

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    The most commonly used grid models are IEEE test feeders, which were originally designed to stress load flow algorithms.

    “Additionally, the most commonly used grid models (e.g., [11]) are test feeders provided by the Institute of Electrical and Electronics Engineers (IEEE) [12], which were originally designed to stress load flow algorithms [12,13].”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [11] Rivera Acevedo, J.A. (2017). Distributed Optimization for Electric Vehicle Charging Control. [Ph.D. Thesis, Technische Universität München].
    • cites [12] Mateo, 2018, European representative electricity distribution networks, Int. J. Electr. Power Energy Syst. source
    • cites [13] IEEE PES (2019, January 15). IEEE PES AMPS DSAS Test Feeder Working Group. Available online: http://sites.ieee.org/pes-testfeeders/resources/.

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Charging scheduling strategies or grid services from parked idle EVs can mitigate the consequences of EV integration.

    “One way to mitigate these consequences is charging scheduling strategies or grid services (voltage regulation, frequency regulation, reserves, etc.) from parked idle EVs [7,8].”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [7] Codani, 2017, Measurement of power loss during electric vehicle charging and discharging, Energy source
    • cites [8] Kempton, 2005, Vehicle-to-grid power fundamentals: Calculating capacity and net revenue, Power Sources source

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Study design and conductnone given

    The availability model of EVs is validated together with domain experts.

    “The availability mode of EVs is validated together with domain experts.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    EV buyers and users are predominately middle-aged people in a technical profession, with high socioeconomic status, living in a suburban or rural multi-person household with high-income.

    “EV buyers and users are predominately middle-aged people in a technical profession, with high socioeconomic status, who are living in a suburban or rural multi-person household with high-income [26].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [26] Schneider, 2014, Who will buy electric vehicles? Identifying early adopters in Germany, Transp. Res. Part A Policy Pract. source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The formula for average network losses is only applicable for this specific case because the EV charging demand is assumed to be only real power.

    “Please note, that the formula is only applicable for this specific case, as we assumed that the EV charging demand is only real power.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: The EV charging demand is only real power.

  • May combine two claims.

    Interpretationreasoning

    The limited emission reduction and cost increase of GHG-optimized charging is due to low carbon emission technologies being deployed during a time of high demand and therefore high electricity prices.

    “This is due to low carbon emission technologies being deployed during a time of high demand and therefore, high electricity prices.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    The above analysis and results include a representative topology and realistic methodology to measure the EV impact on low voltage grids.

    “The above analysis and results include a representative topology and realistic methodology to measure the EV impact on low voltage grids.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Interpretationnone given

    VF is most suitable from a grid perspective and thus a potential strategy for DSOs.

    “As VF is most suitable from a grid perspective and thus a potential strategy for DSOs, our results emphasize the conflict of interest that could occur between operators and aggregators.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    The low SC for both optimizations is because EVs are mainly charged at night and SC levels are generally low in winter.

    “The SC is low for both optimizations as the EV are mainly charged at night, and SC levels are in general low in winter.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: SC levels are in general low in winter.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Study design and conductreasoning

    This study provides a practical and representative basis for future analysis.

    “This study provides a practical and representative basis for future analysis.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationown data

    From the results, conflicts between different approaches are observed.

    “From the results, it is observed that there are conflicts between different approaches.”
    Quote in the paperNot a substantial claim
39 of 39

  • The authors state this as an assumption.

    All consumers are either single-family homes or a mixture between single-family homes and duplex homes based on the evaluated scenario.

    “As we are modeling a semi-urban low voltage grid, we assume all consumers to be either single-family homes or a mixture between single-family homes and duplex homes based on the evaluated scenario.”

  • The authors state this as an assumption.

    The charging of the EV in the residential setting is only limited by the maximum charging rate of the vehicle.

    “We assume that the charging of the EV in the residential setting is only limited by the maximum charging rate of the vehicle.”

  • The authors state this as an assumption.

    The grid has a tap changing transformer and the full voltage bandwidth can be used in the low voltage part of the network.

    “We assume that the grid has a tap changing transformer and the full voltage bandwidth can be used in the low voltage part of the network.”

  • The authors state this as an assumption.

    The EV charging demand is only real power.

    “Please note, that the formula is only applicable for this specific case, as we assumed that the EV charging demand is only real power.”

  • The paper relies on this without support.

    The further the EVs are connected from the transformer, the higher the voltage drops.

    “The further the EVs are connected from the transformer, the higher the voltage drops.”

  • The paper relies on this without support.

    EV charging is inherently unbalanced.

    “EV charging is inherently unbalanced”

  • The paper relies on this without support.

    In the specific network, the current rating of the cable is exceeded before the apparent power rating of the transformer (250 kVA).

    “as in our specific network the current rating of the cable is exceeded before the apparent power rating of the transformer (250 kVA).”

  • The paper relies on this without support.

    EVs are generally available at home during the night and can be ideally scheduled.

    “Additionally, EVs are generally available at home during this time and can be ideally scheduled.”

  • The paper relies on this without support.

    In real-world systems it is impossible to control at which phase an EV will be connected.

    “Nevertheless, in real-world systems it is impossible to control at which phase an EV will be connected to.”

  • The paper relies on this without support.

    Network losses are mainly a quadratic function of current.

    “As network losses are mainly a quadratic function of current, this underlines the fact, that EVs were scheduled to charge during a time of high load.”

  • The paper relies on this without support.

    SC levels are in general low in winter.

    “The SC is low for both optimizations as the EV are mainly charged at night, and SC levels are in general low in winter.”
11 of 11

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Line/transformer loadings have not been covered in Spitzer et al. [18].

    “but line/transformer loadings have not been covered.”

    From Maximum Tolerated Number of Simultaneous BEV Charging Events in a Typical Low-Voltage Grid for Urban Residential Area (2023) · cites this paper as [18]

    Section 4.1 (Uncoordinated Charging) examines transformer apparent power against its rated limit in Figure 5, even though the authors exclude it as a formal analysis criterion. Section 4.2.1 (Cost Optimized Strategy) also discusses cable current-limit violations and a transformer constraint. Thus, the paper covers both line and transformer loading. (LLM, conf=0.90)

    Checked by a reasoning model — may be wrong.

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • PV self-consumption figures conflict with Table 3

    Major

    The text gives self-consumption rates of 4.04% before GHG optimization and 0.18% afterward. Table 3 gives 2.64% and 0.06% for those same winter-week scenarios.

  • PV feed-in source does not match reference 33

    Minor

    The text identifies reference 33 as the source for photovoltaic geographical data, but reference 33 is a SMARD electricity-market data entry.

  • Scenario-study citation does not match reference 40

    Minor

    The text cites reference 40 as an energy-market study by Hecking and coauthors. Reference 40 instead lists a Bavarian vehicle-registration publication; the Hecking study appears as reference 39.

  • SMARD citation points to a MathWorks script

    Minor

    The cited reference 34 is a MathWorks feeder-model script, not the SMARD database named in the text.

4 of 4

Cites

Flagged first, then by citations

Research works printed but not linked: 2

  1. IEEE PES (2019, January 15). IEEE PES AMPS DSAS Test Feeder Working Group. Available online: http://sites.ieee.org/pes-testfeeders/resources/.
  2. Dudgeon, G. (2019, October 05). IEEE 906 Bus European LV Test Feeder in Simscape Power Systems. Available online: https://www.mathworks.com/matlabcentral/fileexchange/66991-ieee-906-bus-european-lv-test-feeder-in-simscape-power-systems.

Cited by

Sorted by citations

Related

Authors
Spitzer, M., Schlund, J., Apostolaki-Iosifidou, E., & Pruckner, M.
Affiliations
  • Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
  • SLAC National Accelerator Laboratory (US)
Corresponding author
Pruckner, Marco
ORCID
Venue
Energies
Publisher
MDPI AG
Published
2019-10-25
Volume
12
Issue
21
Pages
4059
ISSN
1996-1073 (ISSN-L)
DOI
10.3390/en12214059
OpenAlex
W2981805322
Cited by
52
References
32
Citations by year
2025: 5 · 2024: 4 · 2023: 10 · 2022: 10 · 2021: 13 · 2020: 10
FWCI
2.97
Type
journal article
Language
en
Open access
Licence
Locations
  • Energies (publishedVersion, cc-by)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • OPUS Repository (Kooperativer Bibliotheksverbund Berlin-Brandenburg) (submittedVersion, cc-by)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
Keywords
electric vehicles, coordinated charging, low-voltage distribution networks, voltage stability, phase imbalance, grid congestion, greenhouse gas emissions reduction, charging cost reduction

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-28.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-28.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review