The power grid expansion and increasing topological complexity have led to the failure of selectivity coordination in existing relay protection configurations

which in turn may cause systematic miscoordination and threaten power system security. Although manual setting offers strong generalization capability

it is difficult to achieve globally optimal selection of starting points and suffers from low efficiency. Existing optimization methods have improved solution speed and alleviated local optimum issues; however

they may still face the risk of local convergence in high-dimensional and complex grid scenarios and their integration with engineering constraints remains insufficient. To address these issues

an intelligent starting point selection and relay protection setting method based on a quantum inspired-adaptive genetic algorithm (QI-AGA) is proposed. First

an evaluation framework for the importance of protection coordination relationships is established based on steady-state power flow and miscoordination consequence analysis. Second

a model for starting point selection and setting calculation in ring networks is developed

aiming to minimize both the importance of miscoordination and the number of protection adjustments

thereby improving coordination reliability while reducing adjustment effort. Then

a solution method based on QI-AGA is proposed to optimize the selection of starting points and complete the setting calculation according to coordination principles

enhancing both efficiency and reliability of intelligent setting. Finally

case studies based on multiple real 220 kV power grid configurations demonstrate that the proposed method can effectively select starting points and improve setting efficiency.