Impact analysis of electric vehicle charging station integration with distributed generators on power systems

Aggarwal, Surbhi; Singh, Amit Kumar

doi:10.1002/cta.2974

Cited by 25 publications

(17 citation statements)

References 26 publications

(42 reference statements)

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“…This issue is also presented in Reference 24. On the contrary, the authors in References 25,26 address the problem of optimal sitting and sizing of charging stations preventing voltage violations and considering line ratings.…”

Section: Scope Of Workmentioning

confidence: 99%

Distribution network energy loss reduction under EV charging schedule

Bouhouras

Kothona

Gkaidatzis

et al. 2022

Intl J of Energy Research

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Summary This article deals with the problem of energy losses in distribution networks (DNs) under electric vehicle (EV) penetration. The problem of charging overlaps causing severe power losses and voltage drops is faced under appropriate EV charging. An optimized EV charging schedule is proposed under EV time‐of‐arrival consideration. The solution algorithm is based on a particle swarm optimization (PSO) variant, and both grid‐to‐vehicle (G2V) and vehicle‐to‐grid (V2G) schemes are included regarding the power interactions of the EVs with the grid. The goal is to optimally allocate the charging and/or discharging time periods of the EVs in order to minimize energy losses while delivering fully charges EVs to the owners. New departures after the first EVs' arrival are also handled. The results indicate that with the proposed scheduling, daily energy loss reduction could be reached up to 25% under an improved voltage profile that indicates more uniform loading for the DN.

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Section: Scope Of Workmentioning

confidence: 99%

Distribution network energy loss reduction under EV charging schedule

Bouhouras

Kothona

Gkaidatzis

et al. 2022

Intl J of Energy Research

View full text Add to dashboard Cite

show abstract

“…Through the utilization of inverse Jacobian matrix, performed the sensitivity analysis of the system. Aggarwal and A. Kumar [22] have studied the installation of a fast-charging station in the IEEE 24-bus testing system. The major aim of the transportation sector was the achievement of low-carbon, green transportation, and sustainable development.…”

Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

“….As described by the equations above, the apparent power flow in each line does not exceed the maximum transmission capacity. System voltage balance is described by (22),…”

Section: Modeling Of Distribution Systemmentioning

confidence: 99%

Location Determination of Electric Vehicles Parking Lot With Distribution System by Mexican AXOLOTL Optimization and Wild Horse Optimizer

et al. 2022

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In this manuscript proposes a hybrid approach for locating and sizing Electric vehicle charging stations (EVCSs) optimally and managing the vehicle charging process. The proposed hybrid approach is to work in conjunction with Mexican Axolotl optimization (MAO) and Wild Horse Optimizer (WHO) hence it is named as MAOWHO approach. The major purposes of the proposed approach are to site and size of the electric vehicle parking lot (EVPL) and to improve the benefit of EVPL for the participation of the reserve market. In addition, power loss and voltage fluctuations occur due to the stochastic nature of renewable energy sources (RES) and electric vehicles (EV) demand load, which is reduced by the proposed approach. To optimally determine the size of the parking lot, the MAOWHO approach is adopted. The integration of the EV and PV systems, especially in parking lots, enhances the reliability and flexibility of the electrical system at critical moments. Multiple objective optimization problems are calculated to achieve objective variables to reduce power losses, voltage fluctuations, charging and supply costs, and EV costs. The location and capacity of the RES and EV charging stations in this optimization problem are objective variables. The MAOWHO approach enhances Solar Powered Electric Vehicle Parking Lot (EVSPL) participation in various energy and ancillary service markets that includes the effects of capacity payments. Besides, the implementation of MAOWHO approach is done by the MATLAB/Simulink platform and the performance of the MAOWHO approach is compared to the existing approaches. From the simulation outcome, it concludes that the proposed approach based performance provides a profit of 880 € compared to other approaches like SMO, CGO, SBLA.

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“…The expected technology effectiveness was tested on a custom IEEE 34-bus distribution network. Surbhi Aggarwal and Amit Kumar Singh [22] studied the installation of rapid charging stations, a case study on a 24-bus system. This work demonstrates the location of charging stations through dissimilar nominal powers of 5, 25, 50, and 100 MW in different systems of test cases on the load bus line, taking into account the violation of the voltage amplitude limits (0.95 < V < 1.05) ratings.…”

Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

A Hybrid AOSAOA Scheme Based on the Optimal Location for Electric Vehicle Parking Lots and Capacitors in a Grid to Care of Voltage Profile and Power Loss

et al. 2022

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In this manuscript, a hybrid system depending on the optimal location of electric vehicle parking lots (PL) and capacitors under voltage profile care and power loss is proposed. The proposed hybrid scheme is the joint execution of both the atomic orbital search (AOS) and arithmetic optimization algorithm (AOA). Commonly it is called the A OSAOA technique. In the paper, the allocation of the parking lot and capacitor is introduced to congestion management with reactive power compensation. To optimally regulate that parking lot size, the AOSAOA technique is adopted. Furthermore, parking lot and capacitor allocation are introduced to congestion management and reactive power compensation. With this proper control, the perfect sitting of capacitor and EV parking lots under the grid, including the deterioration of real and reactive power loss and voltage profiles are optimally chosen. Furthermore, the implementation of the proposed AOSAOA model is developed by the MATLAB/Simulink platform, and the efficiency of the proposed model is likened to other techniques.

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Impact analysis of electric vehicle charging station integration with distributed generators on power systems

Cited by 25 publications

References 26 publications

Distribution network energy loss reduction under EV charging schedule

Distribution network energy loss reduction under EV charging schedule

Location Determination of Electric Vehicles Parking Lot With Distribution System by Mexican AXOLOTL Optimization and Wild Horse Optimizer

A Hybrid AOSAOA Scheme Based on the Optimal Location for Electric Vehicle Parking Lots and Capacitors in a Grid to Care of Voltage Profile and Power Loss

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