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Cited by 9Optimal Power Flow DistributionElectric Vehicles and InfrastructureSmart Grid Energy Management

Enhancing voltage optimization in distribution networks through flexible operation of EV parking lots

Open access
De Santis, Michele, Harighi, Tohid, Di Fazio, Anna Rita, Borghetti, Alberto, Russo, Mario·2025·Sustainable Energy, Grids and Networks
DOI 10.1016/j.segan.2024.101601
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Abstract

This study focuses on the use of consumption flexibility provided by a parking lot (PL) equipped with charging stations for electric vehicles to improve the voltage control in distribution networks. A methodology is presented in which PL offers both upward and downward flexibility of power consumption, provided that energy recovery is guaranteed in subsequent time intervals. To define the flexibility offered by the PL, the proposed approach uses a stochastic optimization model that computes the day-ahead absorption profiles and the maximum allowable flexibility for each 15-minute interval, expressed in terms of the power adjustment capability of the PL in response to the distribution system operator (DSO) request. The DSO then optimizes the voltage profile of the distribution network using the power flexibility offered by the PLs, as well as by other distributed energy resources (DERs). A multiperiod horizon is used in the voltage optimization problem to account for the effects of energy recovery in subsequent intervals. The results are presented for simulations of 24-hour operation of the IEEE 123-node test feeder with four flexible PLs and 15 DERs, whose reactive powers can be varied. The results for two days show an improvement of approximately 70% in terms of voltage profiles in comparison with the case without any voltage optimization, with 30% of the specific contribution of PLs compared to only DERs optimization. The full recovery in terms of the energy provided by each PL is verified, and a cost analysis from the DSO perspective is presented.

AI snapshot

Written from the paper’s full text.

TL;DR

The paper proposes a stochastic optimization for EV parking-lot flexibility and a multiperiod DSO voltage optimization that uses that flexibility together with other DERs. In IEEE 123-node simulations with four parking lots and 15 PV DERs, using parking-lot flexibility improved voltage profiles by about 70%–75% versus no voltage optimization and by about 34%–35% versus DER-only optimization, while fully recovering the scheduled parking-lot energy.

Key findings

  • In Case A, the voltage deviation index (VDI) was 0.335 with no VOP, 0.154 with VOP DERs, and 0.101 with VOP DERs and PLs; in Case B, it was 0.359, 0.141, and 0.091, respectively. The paper reports approximately 70% and 75% VDI improvement versus no VOP for Cases A and B, and approximately 34% and 35% improvement versus VOP DERs.
  • Total daily energy consumed by each parking lot was identical between the scheduled program and the multi-period VOP: EVPL 1 = 3.6501 MWh, EVPL 2 = 6.2028 MWh, EVPL 3 = 8.5602 MWh, and EVPL 4 = 3.6501 MWh, verifying full energy recovery.
  • Maximum downward/upward flexibility for a single 15-min interval was, for PL A, 2.8/2.2 MW; PL B, 1.7/1.4 MW; and PL C, 1.3/1.3 MW. Average values were lower, e.g., PL A down 0.7 MW and up 0.6 MW.
  • With a DSO budget of 50 €/h, the total daily cost of the PL flexibility service was 99.7 €/day in Case A and 105.5 €/day in Case B; reducing the budget increased VDI and decreased total daily cost.

Methods

  • The parking-lot aggregator uses a 4-stage stochastic linear optimization with 15-min periods, a k-medoid scenario tree built from 60 daily scenarios, and recovery interval n_rec = 3 to compute reference consumption profiles and maximum upward/downward flexibility margins; implemented in AIMMS and solved with Gurobi.
  • The DSO voltage optimization is a multiperiod quadratic program using a linearized power-flow model based on voltage sensitivity matrices and voltage control zones/pilot nodes; it is applied every 15 min over a 24-h horizon to the balanced IEEE 123-node test feeder with four EV parking lots and 15 PV DERs.
  • Case A uses 200 kW rated PV per system and rated load; Case B uses 300 kW PV per system and load reduced to 30% of Case A. The VOP is solved in MATLAB R2022a with fmincon, with base power flow by MatPower, and compared across no VOP, VOP DERs, and VOP DERs and PLs.

Limitations

  • The paper states that further work is needed for a more accurate representation of unbalanced operating conditions, extension to uncertainties from other flexibility sources, consideration of additional DSO services such as congestion management, and decomposition approaches for very large test cases.
  • The text makes evident that the model assumes balanced operation, does not allow power injection from the parking lot to the grid (V2G is excluded), and neglects uncertainties in uncontrolled loads and DER RES production in the short-horizon VOP.
  • The case studies do not address scenarios where the parking lot cannot meet some EV charge requests, and the cost analysis relies on fixed tariff and budget assumptions.

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

Integrity signals

Registry

Crossref · 10.1016/j.segan.2024.101601

Cites

41 of 41 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

4 of 6 cited sources checked · 2 supported · 0 flagged · accuracy not yet measured

  • Premisecitation
    § 3.1. PL model for VOP · p. 7

    In each virtual voltage control zone, a pilot node is identified whose voltage adequately represents the voltage amplitudes of all nodes in that zone, as described in [38].

    “In each VCZ, a pilot node (PN) is identified, whose voltage adequately represents the voltage amplitudes of all nodes in that VCZ, as described in [38].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [38] Di Fazio, 2019, Zoning evaluation for voltage optimization in distribution networks with distributed energy resources, Energies source
  • Premisecitation
    § 3.1. PL model for VOP · p. 8

    The square amplitudes of the nodal voltages are linearly related to the variations of the active and reactive powers injected in each node with respect to their base-case values.

    “The square amplitudes of the nodal voltages (22) are linearly related to the variations of the active and reactive powers injected in each node with respect to their values in the base case, represented by superscript 0, as follows”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [32] Di Fazio, 2018, Linear method for steady-state analysis of radial distribution systems, Int. J. Electr. Power Energy Syst. source

      The indexed copy contains an IRIS repository page, not the paper’s technical text; the passage labeled “Abstract > 1.1 Articolo in rivista” lists a PDF restricted to authorized users. Searches for squared nodal-voltage amplitudes and for a linear relationship with active and reactive power variations returned no relevant passage. The claim cannot be checked against our copy. (LLM, conf=0.78)

      Experimental — accuracy not yet measured
  • Premisecitation
    § 3.1. PL model for VOP · p. 8

    The constrained Jacobian method proposed in [32] takes advantage of the radial configuration of the network.

    “To avoid such drawbacks, the constrained Jacobian method proposed in [32] is used, which takes advantage of the radial configuration of the network.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [32] Di Fazio, 2018, Linear method for steady-state analysis of radial distribution systems, Int. J. Electr. Power Energy Syst. source

      The indexed copy contains an IRIS repository listing, not the paper’s methods text. Its title mentions radial distribution systems, but searches for “constrained Jacobian” and “Jacobian radial distribution systems” found no passage establishing that the paper proposes that method or uses the network’s radial configuration in it. The listing identifies the PDF as restricted to authorized users (Abstract > 1.1 Articolo in rivista; no page number). (LLM, conf=0.76)

      Experimental — accuracy not yet measured
  • Findingnone given
    § A B S T R A C T · p. 1

    Full recovery of the energy provided by each PL was verified.

    “The full recovery in terms of the energy provided by each PL is verified”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The overall energy absorption is constant.
    • The authors state this as an assumption: The EV charging service is guaranteed by timely energy recovery.
  • Findingown data
    § A B S T R A C T · p. 1

    In those simulations, the specific contribution of PLs to the voltage profile improvement was 30% compared with only DERs optimization.

    “with 30% of the specific contribution of PLs compared to only DERs optimization”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: Uncertainties associated with load consumption and DER production are negligible in the DSO's short optimization horizon.
  • May combine two claims. 18
  • The quote only partly states this claim. 1
  • Classified as probably not a substantial claim. 14

  • May combine two claims.

    Study design and conductcitation
    § 2. EV parking lot model and flexibility optimization · p. 5

    The k-medoid clustering procedure provides the medoid and probability value for each cluster and stage, ensuring an integer number of entering, exiting, and parked cars and preserving feasibility of the scenarios.

    “For each cluster and each stage, this procedure provides the medoid (i.e., one of the original scenarios that minimizes the dissimilarity measure with respect to the other scenarios in the cluster) and the corresponding probability value 𝜋 𝜔 , ensuring an integer number of entering, exiting, and parked cars, thus preserving the feasibility of the scenarios.”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [36] Orozco, 2021, Day-ahead multistage stochastic optimization of a group of electric vehicle charging stations source
    • cites [37] Harighi, 2024, Flexibility modeling for parking lots with multiple EV charging stations, Electr. Power Syst. Res. source

  • The quote only partly states this claim.

    Findingown data
    § A B S T R A C T · p. 1

    In simulations of 24-hour operation of the IEEE 123-node test feeder with four flexible PLs and 15 DERs, the proposed voltage optimization improved voltage profiles by approximately 70% compared with the case without any voltage optimization.

    “The results for two days show an improvement of approximately 70% in terms of voltage profiles in comparison with the case without any voltage optimization”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: Uncertainties associated with load consumption and DER production are negligible in the DSO's short optimization horizon.

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

    Findingnone given
    § 4.1. Parking lots · p. 9

    The scenario for PL A includes 195 EVs with an average stay time of 10 periods.

    “The scenario for PL A includes 195 EVs with an average stay time of 10 periods, the scenario of PL B includes 327 EVs with an average stay time of 9.4 periods, and the scenario for PL C includes 121 EVs with average stay time of 7.4 periods.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § 5. Conclusion · p. 14

    The VOP DERs and PLs algorithm improves the voltage deviation index by approximately 70% in Case A and 75% in Case B compared with the no-VOP algorithm.

    “the solution of the VOP DERs and PLs algorithm improves the voltage deviation index by approximately 70% and 75% for Cases A and B, respectively, compared with that of the no VOP algorithm”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § 4.2.1. Case A · p. 11

    For EVPL2 between 11:30 and 11:45 the actual absorption exceeds the scheduled one by approximately 0.27 MW, and in the following three periods (11:45 to 12:30) the actual absorption falls below the scheduled level by approximately 0.09 MW.

    “the actual absorption, indicated by the blue curve, exceeds the scheduled one by approximately 0.27 MW); in the following three periods (between 11:45 and 12:30), the actual absorption falls below the scheduled level by approximately 0.09 MW.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § 4.1. Parking lots · p. 9

    The values of the objective function (21) for the stochastic optimization case without flexibility are 438 for PL A, 568 for PL B, and 242 for PL C.

    “The values of the objective function (21) for the stochastic optimization case without flexibility are e 438 for PL A, e 568 for PL B, e 242 for PL C.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § 4.2.1. Case A · p. 12

    The total daily energy absorbed by each parking lot is the same for the scheduled program and for the multi-period VOP, so complete energy recovery for the EV charging service over the 24 h is achieved.

    “Table 7 shows that the energy values for the scheduled program, that is, the energy absorbed by each PL without any flexibility, and for the multi-period VOP, that is, the actual energy absorbed according to the results of the proposed algorithm, are the same.”
    • Also stated in: § 5. Conclusion · p. 15 · plain
      “this procedure guarantees complete energy recovery for the EV charging service during 24 h of the day”
    Quote in the paperSubstantial claim

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

    Findingown data
    § 4.1. Parking lots · p. 9

    The scenario for PL C includes 121 EVs with an average stay time of 7.4 periods.

    “The scenario for PL A includes 195 EVs with an average stay time of 10 periods, the scenario of PL B includes 327 EVs with an average stay time of 9.4 periods, and the scenario for PL C includes 121 EVs with average stay time of 7.4 periods.”
    Quote in the paperNot a substantial claim

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

    Findingown data
    § 4.1. Parking lots · p. 9

    The scenario for PL B includes 327 EVs with an average stay time of 9.4 periods.

    “The scenario for PL A includes 195 EVs with an average stay time of 10 periods, the scenario of PL B includes 327 EVs with an average stay time of 9.4 periods, and the scenario for PL C includes 121 EVs with average stay time of 7.4 periods.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § 4.2.2. Case B · p. 13

    Compared to Case A, in Case B there are more periods in which the flexibility of the parking lots is exploited with an absorption increase, followed by a decrease during the following three recovery periods.

    “Compared to Case A, in Case B, there are more periods when the flexibility of the PLs is exploited with an absorption increase (and consequent decrease during the following three recovery periods).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § 4.2.3. Cost analysis · p. 14

    As the DSO budget limit decreases, the VDI increases and the TDC decreases.

    “As expected, VDI increased and TDC decreased as the budget limit decreased.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § 4.2.3. Cost analysis · p. 13

    Under the assumed unitary flexibility price of 25 €/MWh and DSO budget of 50 €/h, the Total Daily Cost of the PL flexibility service used by the DSO was 99.7 €/day in Case A and 105.5 €/day in Case B.

    “the Total Daily Cost (TDC) of the PL flexibility service used by the DSO was 99.7 € /day in Case A and 105.5 € /day in Case B.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § 4.2.1. Case A · p. 11

    The VDI values are 0.335 (no VOP), 0.154 (VOP DERs) and 0.101 (VOP DERs and PLs) in Case A, and 0.359, 0.141 and 0.091 respectively in Case B.

    “| A 0.335 | 0.154 | 0.101 |”
    • Also stated in: § 4.2.1. Case A · p. 11 · plain
      “| B 0.359 | 0.141 | 0.091 |”
    Quote in the paperSubstantial claim

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

    Findingown data
    § 4.2. Multi-period VOP · p. 11

    For the case study and operating conditions considered, each execution of the VOP algorithm takes on average 0.25 s on an AMD Ryzen 7 4800H, 2.9 GHz CPU with 16 GB of RAM.

    “For each execution, the VOP algorithm takes on average 0.25 s with an AMD Ryzen 7 4800H, 2.9 GHz CPU and 16 GB of RAM.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § 4.1. Parking lots · p. 9

    The PL C results are the lowest, confirming low flexibility.

    “The PL C results are the lowest confirming the low flexibility.”
    Quote in the paperNot a substantial claim

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

    Interpretationnone given
    § 2.1. Reference consumption profiles · p. 6

    V2V exchanges are allowed by bidirectional charging stations and help ensure that EVs depart with the maximum charge allowed by the parking duration by using energy stored in EVs expected to have longer parking times.

    “V2V exchanges are allowed by bidirectional charging stations and help to ensure that EVs depart with the maximum charge allowed by the parking duration, 𝐸 𝜔,𝑡 S, by using the energy stored in EVs that are expected to have longer parking times.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationnone given
    § 3. Multi-period voltage optimization · p. 7

    The proposed voltage optimization considers subsequent time intervals to account for energy recovery by PLs after flexibility has been used, which is a significant improvement over the approach presented in [34].

    “As shown in Fig. 2, the voltage optimization is a dispatching activity performed on a short time horizon, f.i. every quarter of hour, but considering also the subsequent time intervals to account for the energy recovery by PLs after flexibility has been used. This represents a significant improvement with respect to the approach presented in [34].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [34] Harighi, 2023, Flexible operation of an EV parking lot for voltage control of a distribution network source

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given
    § 2.1. Reference consumption profiles · p. 6

    In the presence of V2V energy exchanges, some EVs receive more energy from the grid than needed for their final charge gain during parking.

    “The evaluation of non-negative 𝐸 𝜔,𝑡 V2V is based on the observation that in the presence of V2V energy exchanges, some EVs receive more energy from the grid than needed for their final charge gain during parking.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationreasoning
    § 3. Multi-period voltage optimization · p. 7

    Due to the short time horizon, uncertainties associated with variations of uncontrolled loads and DERs exploiting RESs can be neglected.

    “Due to the short time horizon, the uncertainties associated with variations of uncontrolled loads and to DERs exploiting RESs can be neglected.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationreasoning
    § Table 1 · p. 4

    The parking lot aggregator considers decisions based on shorter time horizons infeasible because they do not sufficiently consider future arrivals and departures.

    “The parking lot aggregator considers decisions based on shorter time horizons infeasible because they do not sufficiently consider future arrivals and departures.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given
    § Table 1 · p. 4

    The uncertainty in forecasting EV arrivals and departures justifies the stochastic approach.

    “The uncertainty in forecasting EV arrivals and departures justifies the stochastic approach.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning
    § 3.1. PL model for VOP · p. 7

    The need to recover flexibility once it has been used introduces another relationship between the VOPs solved at time t and those to be solved in the following n_rec time periods, so a multi-period approach must be adopted.

    “The need to recover the flexibility once it has been used introduces another relationship between the VOPs solved at time 𝑡 and those to be solved in the following 𝑛 rec time periods. Then, a multi-period approach must be adopted,”
    Quote in the paperSubstantial claim

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

    Study design and conductnone given
    § 2.2. Maximum power flexibility · p. 6

    All models are supplemented with non-anticipativity constraints to ensure that decisions made at various stages are based solely on currently available information, regardless of future outcomes or information.

    “All models are supplemented with non-anticipativity constraints, which are common in stochastic optimization, to ensure that decisions made at various stages are based solely on currently available information, regardless of future outcomes or information.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given
    § 3.1. PL model for VOP · p. 8

    In large distribution networks, the power flow equations represent a significant number of non-linear equations.

    “In large distribution networks, the power flow equations represent a significant number of non linear equations.”
    Quote in the paperNot a substantial claim

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

    Interpretationnone given
    § 2. EV parking lot model and flexibility optimization · p. 5

    Aggregation includes the possibility that energy can be shared among vehicles connected to the charging stations.

    “Aggregation includes the possibility that energy can be shared among the vehicles connected to the charging stations.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given
    § 3.1. PL model for VOP · p. 7

    Monitoring all node voltages in a large distribution system is not feasible.

    “Monitoring all node voltages in a large distribution system is not feasible; to address this issue, the distribution network is partitioned into 𝑁𝑣𝑐 𝑧 virtual voltage control zones (VCZs).”
    Quote in the paperNot a substantial claim

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

    Interpretationreasoning
    § 3.5. VOP formulation · p. 8

    A classical sequential QP algorithm can be used to solve the VOP by solving a series of QP problems obtained by assuming only one of the two variables P_flex_up or P_flex_down.

    “Then, to solve the VOP, a classical sequential QP algorithm can be used, solving a series of QP problems obtained by assuming only one of the two variables, that is either 𝑃 𝑡 flex up ,𝑘 or 𝑃 𝑡 flex down ,𝑘 .”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning
    § 4.1. Parking lots · p. 9

    The results of PL A and PL B are closer, with PL A showing improved flexibility, due to the greater importance of stay time duration with respect to the number of EVs.

    “The results of PL A and PL B are closer, with PL A showing improved flexibility, due to the greater importance of stay time duration with respect to the number of EVs.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning
    § 3.1. PL model for VOP · p. 8

    Repeating the power flow equations n_rec+1 times for multiple time periods leads to a considerable increase in computational burden and a risk of convergence problems in the VOP numerical solution.

    “In addition, since multiple time periods are considered in (21), the power flow equations need to be repeated 𝑛 𝑟𝑒𝑐 + 1 times. This repetition leads to a considerable increase in computational burden and a risk of convergence problems in the VOP numerical solution.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning
    § 3.5. VOP formulation · p. 8

    The VOP (31)-(35) is a quadratic programming problem with linear constraints, except for constraint (34), which ensures that at least one of the two variables P_flex_up and P_flex_down is null.

    “The VOP (31)-(35) is a quadratic programming (QP) problem with linear constraints, except for (34), which ensures that at least one the two variables 𝑃 𝑡 flex up ,𝑘 and 𝑃 𝑡 flex down ,𝑘 is null.”
    Quote in the paperNot a substantial claim
30 of 30

  • The authors state this as an assumption.

    The PL operator and the DSO have a mutual understanding allowing the PL operator to adjust power within a predetermined recovery interval after flexibility provision.

    “To guarantee adequate charging service, the proposed procedure assumes a mutual understanding between the PL operators and the DSO, allowing the PL operator to adjust power within a predetermined recovery interval after the flexibility provision.”

  • The authors state this as an assumption.

    The overall energy absorption is constant.

    “assuming that the overall energy absorption is constant”

  • The authors state this as an assumption.

    The EV charging service is guaranteed by timely energy recovery.

    “the EV charging service is guaranteed by timely energy recovery”

  • The authors state this as an assumption.

    Uncertainties associated with load consumption and DER production are negligible in the DSO's short optimization horizon.

    “with a short optimization horizon for which the uncertainties associated with load consumption and DER production were considered negligible in this study.”

  • The authors state this as an assumption.

    Power injection from the parking lot to the grid is not allowed.

    “It is assumed that power injection from the parking lot to the grid is not allowed.”

  • The authors state this as an assumption.

    Forecasts of the number of EVs entering and exiting the parking lot in each period of the next day are available.

    “The scenario generation procedure assumes that forecasts of the number of EVs entering and exiting the PL in each period of the next day are available.”

  • The paper relies on this without support.

    Departing vehicles are either fully charged or charged to the maximum level compatible with the charging station's rated power and parking time.

    “Departing vehicles are either fully charged or charged to the maximum level compatible with the charging station's rated power and parking time.”

  • The authors state this as an assumption.

    The DSO request is limited to a single 15-min period t_flex.

    “The model calculates flexibility margins assuming the DSO request is limited to a single 15-min period 𝑡 flex .”

  • The paper relies on this without support.

    The agreement between the PL operator and the DSO allows the PL to recover the power change during a specified period n_rec after the flexibility interval; the recovery is proportional to the requested change and follows a uniform pattern, with no further changes requested during n_rec.

    “The agreement between the PL operator and the DSO allows the PL to recover the power change during a specified period 𝑛 rec after the flexibility interval. The recovery is proportional to the change in the reference profile requested by the DSO and follows a uniform pattern, with no further changes requested during 𝑛 rec .”

  • The paper relies on this without support.

    V2V exchanges involve losses in converters that must be accounted for.

    “However, vehicle-to-vehicle (V2V) exchanges involve losses in the converters that must be accounted for.”

  • The paper relies on this without support.

    V2V exchanges may cause some stress on the battery that should be compensated or limited.

    “In addition, V2V exchanges may cause some stress on the battery that should be compensated or limited.”

  • The authors state this as an assumption.

    Charging and V2V efficiencies are constant; dependence on power exchanged, state of charge, and state of health of the batteries is neglected.

    “Both 𝜂 ch and 𝜂 V2V are constant (i.e., the dependence of the efficiencies on the power exchanged, the state of charge, and the state of health of the batteries involved is neglected).”

  • The authors state this as an assumption.

    Long-term efficiency degradation due to aging is not considered.

    “Long-term efficiency degradation due to aging is not considered.”

  • The authors state this as an assumption.

    Balanced operation is assumed for the supplying MV distribution system.

    “Due to the high power typically absorbed by PLs, balanced operation is assumed for the supplying MV distribution system.”

  • The authors state this as an assumption.

    For simplicity but without loss of generality, n+flex=0 and n_rec is the same for all PLs.

    “Concerning the PLs, for the sake of simplicity but without loss of generality, it is assumed 𝑛 + flex = 0 and that 𝑛 rec is the same for all the PLs.”

  • The authors state this as an assumption.

    The scenarios in Fig. 4 are assumed to correspond more closely to the actual number of parked EVs.

    “The results of Fig. 4 refer to the scenarios that are assumed to correspond more closely to the actual number of parked EVs.”

  • The authors state this as an assumption.

    The reactive power provided by a PV system can be varied only when its generated active power is larger than 10% of its rated value.

    “The reactive power provided by the PV system can be varied only when the generated active power is larger than 10% of the rated value;”

  • The authors state this as an assumption.

    The active power generated by the PV systems tracks the maximum power point according to the solar radiation variations and cannot be curtailed.

    “The generated active powers track the maximum power point according to the variations of the solar radiation during the day and cannot be curtailed.”
18 of 18

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.

  • Euro-denominated costs are attributed to a voltage-deviation objective

    Minor

    Section 4.1 calls the euro amounts values of objective function (21), but the paper defines (21) as a sum of squared voltage deviations, not the parking-lot cost objective.

  • Funding statement contradicts the paper's grant acknowledgment

    Minor

    The funding section says the work received no funding, while the paper's opening note says the research activities producing its results were funded through named grants.

  • PL C is not lowest for every flexibility result

    Minor

    The text says PL C's results are the lowest, but Table 3 gives PL C a maximum upward flexibility of 0.7 MW for n + f l ex = 2, exceeding PL B's 0.5 MW.

3 of 3

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. IEEE Distribution System Subcommittee, 1992

Cited by

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Related

Authors
De Santis, M., Harighi, T., Di Fazio, A. R., Borghetti, A., & Russo, M.
ORCID
Venue
Sustainable Energy, Grids and Networks
Publisher
Elsevier BV
Published
2025-03
Volume
41
Pages
101601
ISSN
2352-4677 (ISSN-L)
DOI
10.1016/j.segan.2024.101601
OpenAlex
W4406080289
Cited by
9
References
40
Citations by year
2026: 4 · 2025: 5
FWCI
2.03
Type
journal article
Language
en
Open access
Licence
Locations
  • Sustainable Energy Grids and Networks (publishedVersion, cc-by)
  • Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion, cc-by)
  • Archivio Istituzionale della Ricerca - Università degli Studi della Campania "Luigi Vanvitelli" (submittedVersion)
  • Archivio Istituzionale della Ricerca - Università degli Studi di Cassino (submittedVersion)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
Keywords
voltage optimization, distribution networks, electric vehicle parking lots, electric vehicle charging stations, voltage regulation, distributed energy resources, stochastic optimization, energy recovery, reactive power, distribution system operators, IEEE 123-node test feeder, cost analysis

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 ›

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