A transmission grid planning method based on the α-Q(λ) algorithm

In this paper, multi-step backtracking in reinforcement learning is introduced into the traditional transmission grid planning, and the α-Q(λ) algorithm based on multi-step backtracking is proposed for solving grid planning. The basic concept of the α-Q(λ) algorithm is introduced and the specific application ideas and processes of the algorithm in grid planning are designed. Finally, the validation of the proposed method in the Garve-6 system verifies the validity and practicability of the proposed method and comparatively analyzes the performance difference between the method and the traditional method, highlighting its advantages in planning efficiency and economy.