A novel charging and discharging algorithm of plug-in hybrid electric vehicles considering vehicle-to-grid and photovoltaic generation

Ahmed Aljanad, Azah Mohamed, Tamer Khatib, Afida Ayob, Hussain Shareef

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Considering, the high penetration of plug-in electric vehicles (PHEVs), the charging and discharging of PHEVs may lead to technical problems on electricity distribution networks. Therefore, the management of PHEV charging and discharging needs to be addressed to coordinate the time of PHEVs so as to be charged or discharged. This paper presents a management control method called the charging and discharging control algorithm (CDCA) to determine when and which of the PHEVs can be activated to consume power from the grid or supply power back to grid through the vehicle-to-grid technology. The proposed control algorithm considers fast charging scenario and photovoltaic generation during peak load to mitigate the impact of the vehicles. One of the important parameters considered in the CDCA is the PHEV battery state of charge (SOC). To predict the PHEV battery SOC, a particle swarm optimization-based artificial neural network is developed. Results show that the proposed CDCA gives better performance as compared to the uncoordinated charging method of vehicles in terms of maintaining the bus voltage profile during fast charging.

Original languageEnglish
Article number61
JournalWorld Electric Vehicle Journal
Volume10
Issue number4
DOIs
Publication statusPublished - Dec 1 2019

Keywords

  • Artificial neural network
  • Charging and discharging control algorithm
  • Particle swarm optimization
  • Plug-in hybrid electric vehicle
  • State of charge

ASJC Scopus subject areas

  • Automotive Engineering

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