Cloud-Edge Collaborative Optimal Scheduling Method for Power Grid in Edge Computing Environment
Conventional methods for power grid collaborative optimization scheduling mainly rely on model prediction,without considering the impact of dynamic characteristics on power grid scheduling,which reduces the economic efficiency of power grid optimization scheduling.Therefore,a cloud-edge collaborative optimal scheduling method for power grid in edge computing environment is designed:Extract the load characteristics of cloud edge collaborative operation in the power grid,and determine the energy exchange power of the power grid based on the internal power consumption load and generation output feature vectors;Based on edge computing,a grid cloud edge collaborative optimal dispatching model is constructed to configure interruptible load and reserve capacity in grid operation,and provide economic compensation for the power grid cut off,so as to meet the demand for stable grid operation;Based on the characteristics and actual needs of the power grid,determine the appropriate scheduling period,and consider historical and real-time data to adjust the periodic power grid scheduling balance constraints,in order to meet the scheduling optimization needs.By conducting comparative experiments,it was verified that the scheduling effect of this method is better and can be applied in practical life.
万方数据
维普
