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Design of a Smart Distribution Strategy for a Residential Electric Vehicle Charging System Fully Powered by Photovoltaics Under Intermittent Conditions

  • Department of Electrical Engineering
  • Institut Teknologi Sepuluh Nopember

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

Electric Vehicle (EV) charging systems are commonly powered by grid systems. This paper presents a smart distribution strategy for EV charging system fully powered by photovoltaic (PV) energy, aiming to advance green technology. However, the system faces challenges such as limited energy availability from intermittent PV generation, varying State-of-Charge (SoC) levels, and random plug-in time. A smart distribution strategy has proposed a smart charging with the ultimate goal of balancing energy between the PV source and load while maintaining approximately equal EV SoC levels. The novelty lies in the comprehensive utilization of PV systems, incorporating intermittency as a key factor in the strategy. A 303 kWp PV source for 100 charging units, solar irradiation has been forecasted using Artificial Neural Network in order to obtain daily available energy. EV demand has been modelled using a Monte Carlo simulation in order to obtain the plug-in time and the daily travel distance. The simulation results show that the average PV utilization reaches 95.08% with Genetic Algorithm (GA) and 96.63% with Particle Swarm Optimization (PSO). The fairness index, reflecting EV SoC equity, increases to 64.44% with GA and 66.67% with PSO, compared to without the proposed strategy. This study offers a sustainable and equitable charging solution for EV owners.

Original languageEnglish
Pages (from-to)69-79
Number of pages11
JournalInternational Review of Electrical Engineering
Volume20
Issue number1
DOIs
Publication statusPublished - 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Electric Vehicle Charging
  • Energy Balancing
  • Genetic Algorithm
  • Green Energy
  • Particle Swarm Optimization

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