A microgrid alternating current-direct current section convertor PID parameter optimization method based on a gray wolf algorithm comprises: setting the number of wolves in a wolf pack, the maximum number of Iterations, question dimensions and a PID parameter variable value range, and initialing a wolf pack position; calculating a setting model target function value corresponding to a position where each wolf is located, namely the target function value of a PID control effect; according to the setting model target function value, dividing the wolf pack into [Alpha] wolf taken as a wolf with an optimal PID effect, [Beta] wolf taken as a wolf with a suboptimal PID effect, [Delta] wolf taken as a third-best PID effect and [Omega] wolf taken as the rest of the wolves; calculating a check model target function value corresponding to the position where the [Alpha] wolf is located; determining whether the PID control effect of the check model has no improvement for continuous V times or not; updating the wolf pack position representing the PID parameters; determining whether the number of current iterations reaches the setting maximum number of the iterations or not; and outputting the location where the [Alpha] wolf is located, namely the global optimal PID parameter value of the microgrid alternating current-direct current section convertor. The microgrid alternating current-direct current section convertor PID parameter optimization method based on the gray wolf algorithm allow the PID controller parameters to be set to the optimal value of a given target.