When an extreme event shock occurs and the microgrid is disconnected from the main grid, it is necessary to quickly restore the normal electricity consumption within the microgrid to minimize the disturbance caused by power outages to residential customers. In this paper, we propose an emergency cross-domain energy dispatching strategy based on improved differential evolutionary algorithm to restore the stable operation of the microgrid by reformulating the charging and discharging management scheme of electric vehicles and energy storage devices. First, an emergency cross-domain energy transfer strategy for electric vehicles is developed and an emergency energy management scheme for energy storage devices is established to construct an optimization problem with the objectives of minimizing power supply gap and power cost; second, an improved differential evolutionary algorithm is used to solve the optimization problem; finally, a Python-based simulation experiment platform is built to verify the effectiveness of the strategy proposed in this paper in reducing residential power supply gap, average Finally, a Python-based simulation platform is built to verify the effectiveness of the proposed strategy in reducing residential power supply gap, average power outage time and power cost.

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Emergency Cross-Domain Energy Scheduling Strategy for Micro-grids Based on Improved Differential Evolutionary Algorithm

  • Chongyang Li,
  • Yi Li

摘要

When an extreme event shock occurs and the microgrid is disconnected from the main grid, it is necessary to quickly restore the normal electricity consumption within the microgrid to minimize the disturbance caused by power outages to residential customers. In this paper, we propose an emergency cross-domain energy dispatching strategy based on improved differential evolutionary algorithm to restore the stable operation of the microgrid by reformulating the charging and discharging management scheme of electric vehicles and energy storage devices. First, an emergency cross-domain energy transfer strategy for electric vehicles is developed and an emergency energy management scheme for energy storage devices is established to construct an optimization problem with the objectives of minimizing power supply gap and power cost; second, an improved differential evolutionary algorithm is used to solve the optimization problem; finally, a Python-based simulation experiment platform is built to verify the effectiveness of the strategy proposed in this paper in reducing residential power supply gap, average Finally, a Python-based simulation platform is built to verify the effectiveness of the proposed strategy in reducing residential power supply gap, average power outage time and power cost.