IET Generation, Transmission & Distribution (Sep 2024)

Revolutionizing photovoltaic consumption and electric vehicle charging: A novel approach for residential distribution systems

  • Qinglin Meng,
  • Xinyu Tong,
  • Sheharyar Hussain,
  • Fengzhang Luo,
  • Fei Zhou,
  • Lei Liu,
  • Ying He,
  • Xiaolong Jin,
  • Botong Li

DOI
https://doi.org/10.1049/gtd2.13232
Journal volume & issue
Vol. 18, no. 17
pp. 2822 – 2833

Abstract

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Abstract Electric vehicles (EVs) and small photovoltaic (PV) installations advance residential power grids by lowering charging costs and fostering eco‐friendly operations. Yet, the variable nature of EV charging presents challenges to grid reliability. This research introduces a Monte Carlo‐based simulation for predicting EV charging loads and a systematic charging method that integrates a ‘green electricity’ pricing scheme with a joint optimization model for PV and EV management. By applying an improved ant lion optimizer (IALO) algorithm enriched with differential evolution features, an optimization strategy that markedly enhances grid performance is devised. In a park scenario, this ‘green electricity’ model reduced the mean square error of EV charging load by 11.82%, smoothed the power load curve, and improved grid stability. When compared with particle swarm optimization (PSO) and grey wolf optimizer (GWO) algorithms, the IALO algorithm boosted overall revenue by 16.8% and 12.8%, increased PV utilization by 162.3% and 37.1%, and significantly cut carbon emissions by 159.6% and 31.6%, respectively. These outcomes affirm the financial, environmental, and functional benefits of our proposed approach.

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