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Tri-level demand and pricing management of renewable integrated PEV charging stations in power market environment

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  • Choudhary, Durgesh
  • Mahanty, Rabindra Nath
  • Kumar, Niranjan

Abstract

The increasing concern for the environment has increased the adaption of PEVs. The power demand for charging PEVs is growing in a random manner. This has increased the concern of the grid for meeting the demand in real-time. A novel tri-level demand and pricing management strategy is proposed in the study to address this issue. The proposed strategy participates in the day-ahead market and real time market to purchase power from the grid. A long short-term memory network is used to estimate the PEV demand. Weather forecasting is used to estimate the renewable generation. The strategy analyzes the demand-supply and their economics to generate the real-time power price for PEV operations. Deep reinforcement learning is employed to coordinate the PEV operations in real-time. The charging coordination manages the demand with existing power, optimizing the charging station and PEV's profit. The study incorporates infrastructural limitations and grid constraints. The battery degradation and random PEV behaviour are included in the strategy. The case study results show that the proposed strategy has increased the power utilization factor by 48.65 %, PEV's profit by 15.36 %, and charging station profit by 7.39 %.

Suggested Citation

  • Choudhary, Durgesh & Mahanty, Rabindra Nath & Kumar, Niranjan, 2025. "Tri-level demand and pricing management of renewable integrated PEV charging stations in power market environment," Renewable Energy, Elsevier, vol. 253(C).
    • Handle: RePEc:eee:renene:v:253:y:2025:i:c:s0960148125012583
    DOI: 10.1016/j.renene.2025.123596
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    References listed on IDEAS

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