Scholarlink

The management of power flow in renewable energy-based charging stations is a critical challenge due to the variability in energy sources such as solar and wind, as well as the fluctuating demand from electric vehicles (EVs). In this paper, charging station having solar-based renewable energy system is being implemented, which is fed by the constant input irradiation level of 1000 W/m2. The artificial intelligence-based algorithms for power flow distribution are designed feeding EV battery load. Each algorithm brings unique capabilities, from the simplicity and fast convergence of PC_GWO to the exploratory strength of PC_MFO and the predictive and adaptive power of LRC_MFANN. The assessment is carried out by studying the behavior of the DC link voltage, power delivered at the EV load terminals and station battery. As inferred from the results, superior stability in the DC link voltage, LRC_MFANN is found to be the most effective algorithm for ensuring consistent and reliable power delivery to the station’s battery, minimizing fluctuations and enhancing overall performance.

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Sustainable Energy Solution for Solar Charging Station Using Optimization Algorithms for Power Flow Management

  • 会议论文

  • 发表日期：

    2026年

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  • Pankaj Badgaiyan,
  • Sunil Kumar Gupta,
  • Mukesh Pandey

摘要

The management of power flow in renewable energy-based charging stations is a critical challenge due to the variability in energy sources such as solar and wind, as well as the fluctuating demand from electric vehicles (EVs). In this paper, charging station having solar-based renewable energy system is being implemented, which is fed by the constant input irradiation level of 1000 W/m2. The artificial intelligence-based algorithms for power flow distribution are designed feeding EV battery load. Each algorithm brings unique capabilities, from the simplicity and fast convergence of PC_GWO to the exploratory strength of PC_MFO and the predictive and adaptive power of LRC_MFANN. The assessment is carried out by studying the behavior of the DC link voltage, power delivered at the EV load terminals and station battery. As inferred from the results, superior stability in the DC link voltage, LRC_MFANN is found to be the most effective algorithm for ensuring consistent and reliable power delivery to the station’s battery, minimizing fluctuations and enhancing overall performance.