Load prediction-based airport charging pile load management method and system, and medium

Abstract

The invention relates to the technical field of deep learning, in particular to an airport charging pile load management method and system based on load prediction and a medium. Acquiring a current load data set in the airport power grid; inputting the current load data into an improved particle swarm algorithm-long short-term memory neural network model, and predicting predicted load data in a future preset time period, the improved particle swarm algorithm including an adaptive Cauchy variation mechanism; determining a plurality of charging pile load management strategies of the airport according to the predicted load data; on the basis of an improved raccoon optimization algorithm, an optimal charging pile load management strategy in the multiple charging pile load management strategies is determined, and the improved raccoon optimization algorithm comprises a first-time improved search strategy; and carrying out load regulation and control on each charging pile in the airport based on the optimal charging pile load management strategy. The objective of the invention is to solve the problems of how to predict load changes of different power utilization systems in an airport in advance and how to optimize and adjust the load state of an electric vehicle charging pile system in a transformer substation.