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Optimized operation strategy for energy storage charging piles based on multi-strategy hybrid improved Harris hawk

Bo Tang1,2, Cui Shiting3,2, Xin Wang4

  • 1Electric Engineering College, Tibet Agriculture and Husbandry College, Nyingchi, 860000, China.

Heliyon
|May 31, 2024
PubMed
Summary

This study introduces an optimized scheduling strategy for electric vehicle charging stations, significantly reducing electricity costs for users and increasing revenue for charging providers by managing charging and discharging effectively. The approach enhances grid stability by lowering peak load demands.

Keywords:
Electric vehicleEnergy storageHarris hawk optimizationMulti-strategy hybrid improved Harris hawk algorithmOrderly charge and dischargePeak shaving and valley filling

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Area of Science:

  • Electrical Engineering
  • Optimization Theory
  • Smart Grids

Background:

  • Disordered charging and discharging of electric vehicle (EV) energy storage charging piles create grid instability.
  • Dynamic characteristics of EVs further complicate energy management.
  • Time-of-use electricity prices present an opportunity for cost optimization.

Purpose of the Study:

  • To develop an ordered charging and discharging optimization scheduling strategy for EV energy storage charging piles.
  • To minimize EV charging and discharging costs while maximizing charging pile revenue.
  • To address multivariable, multi-objective, and high-dimensional optimization challenges.

Main Methods:

  • Developed a mathematical model for EV charging and discharging scheduling.
  • Proposed a Multi-strategy Hybrid Improved Harris Hawk Algorithm (MHIHHO) for optimization.
  • Validated MHIHHO performance using CEC benchmark test functions.
  • Conducted simulations considering power constraints and discharge loads.

Main Results:

  • Reduced the peak-to-valley load ratio by 52.8% compared to the original algorithm.
  • Effectively allocated charging piles for off-peak energy storage.
  • Reduced user charging costs by 16.83%–26.3%.
  • Increased charging pile revenue.

Conclusions:

  • The proposed MHIHHO-based scheduling strategy effectively optimizes EV charging and discharging operations.
  • The strategy leads to significant cost savings for EV users and increased revenue for charging infrastructure.
  • This approach contributes to improved grid stability and efficient energy resource allocation.