Optimal Planning of Distributed Energy Resources in a Distribution Network with Electric Vehicle Dynamic Wireless Power Charging Loads

Dynamic Wireless Power Transfer (DWPT) has emerged as a potential solution for Electric Vehicle (EV) charging applications in recent years, enabling continuous charging while EVs are in motion. However, large-scale adoption of DWPT introduces variable and high-power charging demands that can impose severe stress on distribution networks. This paper investigates the impacts of EV-DWPT charging on a distribution grid and proposes an optimization framework to mitigate these effects. The optimization framework first combines a Finite-Element State-Space (FE-SS) DWPT pad model with a traffic flow model to construct 24 h aggregated EV-DWPT charging load profiles at the node level of a distribution system. Then, a mixed-integer nonlinear multi-objective optimization model is developed to optimize the placement and sizing of Distributed Energy Resources (DERs) in the presence of the added EV-DWPT charging load. The optimization objectives include minimizing the DER investment and operational cost, active power losses, voltage deviations, and EV-DWPT load curtailment. Two solution strategies are evaluated: a cost-based aggregate (CB) method and a Chebyshev goal programming (GP) method. The CB method emphasizes economic efficiency by aggregating various objectives into a single cost measure, while the GP approach offers a compromise between the technical and economic objectives by minimizing the deviation from individual objective targets. The comparative analysis provides evidence that CB can be used for investment cost minimization as the primary planning criterion, whereas GP is preferable when a balanced solution with improved voltage performance and reduced DWPT curtailment is desired. The proposed optimization methodology is applied to the IEEE 33-bus test system under multiple EV-DWPT load penetration levels and a planning scenario assumption. The results show that coordinated planning of DERs can mitigate the negative effects of EV-DWPT integration on the performance of the voltage while minimizing network losses and guaranteeing reliable charging operation. These findings demonstrate that strategic DER deployment can enable large-scale roadway electrification while maintaining distribution grid operational performance and feasibility.

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Publication Details

Journal
Electricity
Published
2026-10-08
DOI
https://doi.org/10.3390/electricity7040115
Primary Topic
Optimal Power Flow Distribution
Type
article
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article

Optimal Planning of Distributed Energy Resources in a Distribution Network with Electric Vehicle Dynamic Wireless Power Charging Loads

Rakan Almazmomi, Abd A. Arkadan
Electricity
Optimal Power Flow Distribution
article

Optimal Planning of Distributed Energy Resources in a Distribution Network with Electric Vehicle Dynamic Wireless Power Charging Loads

Rakan Almazmomi, Abd A. Arkadan
article en

Abstract

Dynamic Wireless Power Transfer (DWPT) has emerged as a potential solution for Electric Vehicle (EV) charging applications in recent years, enabling continuous charging while EVs are in motion. However, large-scale adoption of DWPT introduces variable and high-power charging demands that can impose severe stress on distribution networks. This paper investigates the impacts of EV-DWPT charging on a distribution grid and proposes an optimization framework to mitigate these effects. The optimization framework first combines a Finite-Element State-Space (FE-SS) DWPT pad model with a traffic flow model to construct 24 h aggregated EV-DWPT charging load profiles at the node level of a distribution system. Then, a mixed-integer nonlinear multi-objective optimization model is developed to optimize the placement and sizing of Distributed Energy Resources (DERs) in the presence of the added EV-DWPT charging load. The optimization objectives include minimizing the DER investment and operational cost, active power losses, voltage deviations, and EV-DWPT load curtailment. Two solution strategies are evaluated: a cost-based aggregate (CB) method and a Chebyshev goal programming (GP) method. The CB method emphasizes economic efficiency by aggregating various objectives into a single cost measure, while the GP approach offers a compromise between the technical and economic objectives by minimizing the deviation from individual objective targets. The comparative analysis provides evidence that CB can be used for investment cost minimization as the primary planning criterion, whereas GP is preferable when a balanced solution with improved voltage performance and reduced DWPT curtailment is desired. The proposed optimization methodology is applied to the IEEE 33-bus test system under multiple EV-DWPT load penetration levels and a planning scenario assumption. The results show that coordinated planning of DERs can mitigate the negative effects of EV-DWPT integration on the performance of the voltage while minimizing network losses and guaranteeing reliable charging operation. These findings demonstrate that strategic DER deployment can enable large-scale roadway electrification while maintaining distribution grid operational performance and feasibility.

ElectricityVol. 7(4)
Colorado School of Mines (US), King Abdulaziz University (SA)
Openalex Percentile: Top 22%
Optimal Power Flow Distribution
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