The invention discloses an
electric vehicle charging
pile charging control
strategy analysis method and
system, and the method comprises the steps: constructing a
hypergraph structure fusing the charging
pile space topology, demand association and power constraint, coding node features, and building hyperedge connection;
feature learning is carried out by introducing an improved
hypergraph neural network of a dynamic attention mechanism and combining real-time charging parameters; a three-dimensional feature
tensor is constructed by fusing a charging
pile multi-dimensional
sequential control model with spatio-temporal data, and a charging parameter dependency relationship is mined to generate a prediction sequence and a matrix; an optimization objective function is constructed based on
power grid, equipment and user conditions to generate a preliminary strategy, an actual charging data feedback
fine tuning model is utilized, and an
optimal control strategy is obtained through multiple rounds of iteration. The
system is correspondingly provided with seven functional units including
hypergraph construction,
feature learning and the like to realize the process. The method can accurately predict the charging parameters, optimizes the charging strategy, and achieves the balance of the charging efficiency, the
power grid load and the user cost.