Skip to main content
placeholder image

Multiobjective Optimization Technique for Mitigating Unbalance and Improving Voltage Considering Higher Penetration of Electric Vehicles and Distributed Generation

Journal Article


Abstract


  • The increasing penetration of distributed generations (DGs) and electric vehicles (EVs) offers not only several opportunities but also introduces many challenges for the distribution system operators (DSOs) regarding power quality. This article investigates the network performances due to uncoordinated DG and EV distribution. It also considers power quality-related performances such as the neutral current, energy loss, voltage imbalance, and bus voltage as a multiobjective optimization problem. The differential evolution optimization algorithm is employed to solve the multiobjective optimization problem to coordinate EV and DG in a distribution grid. This article proposed a method to coordinate EV and DG distribution. The proposed method allows DSOs to jointly optimize the phase sequence and optimal dispatch of DGs to improve the network's performance. If the network requires further improvement, the EV charging or discharging rate is coordinated for a particular location. The efficacy of the proposed method is tested in an Australian low-voltage distribution grid considering the amount of imbalance due to higher penetration of DG and EV. It is observed that the proposed method reduces voltage unbalance factor by up to 98.24%, neutral current up to 94%, and energy loss by 59.45%, and improve bus voltage by 10.42%.

Publication Date


  • 2020

Citation


  • Islam, M. R., Lu, H., Hossain, J., & Li, L. (2020). Multiobjective Optimization Technique for Mitigating Unbalance and Improving Voltage Considering Higher Penetration of Electric Vehicles and Distributed Generation. IEEE Systems Journal, 14(3), 3676-3686. doi:10.1109/JSYST.2020.2967752

Scopus Eid


  • 2-s2.0-85088218685

Start Page


  • 3676

End Page


  • 3686

Volume


  • 14

Issue


  • 3

Abstract


  • The increasing penetration of distributed generations (DGs) and electric vehicles (EVs) offers not only several opportunities but also introduces many challenges for the distribution system operators (DSOs) regarding power quality. This article investigates the network performances due to uncoordinated DG and EV distribution. It also considers power quality-related performances such as the neutral current, energy loss, voltage imbalance, and bus voltage as a multiobjective optimization problem. The differential evolution optimization algorithm is employed to solve the multiobjective optimization problem to coordinate EV and DG in a distribution grid. This article proposed a method to coordinate EV and DG distribution. The proposed method allows DSOs to jointly optimize the phase sequence and optimal dispatch of DGs to improve the network's performance. If the network requires further improvement, the EV charging or discharging rate is coordinated for a particular location. The efficacy of the proposed method is tested in an Australian low-voltage distribution grid considering the amount of imbalance due to higher penetration of DG and EV. It is observed that the proposed method reduces voltage unbalance factor by up to 98.24%, neutral current up to 94%, and energy loss by 59.45%, and improve bus voltage by 10.42%.

Publication Date


  • 2020

Citation


  • Islam, M. R., Lu, H., Hossain, J., & Li, L. (2020). Multiobjective Optimization Technique for Mitigating Unbalance and Improving Voltage Considering Higher Penetration of Electric Vehicles and Distributed Generation. IEEE Systems Journal, 14(3), 3676-3686. doi:10.1109/JSYST.2020.2967752

Scopus Eid


  • 2-s2.0-85088218685

Start Page


  • 3676

End Page


  • 3686

Volume


  • 14

Issue


  • 3