摘要: By applying the artificial intelligence to the traditional transmission expansion planning, a transmission expansion planning method using α-Q(λ) algorithm with adaptive learning factor is proposed based on reinforcement learning. With the help of the prepared database and the Monte Carlo method, the transmission expansion planning model is constructed by considering the reliability cost in the optimal object function. Combining the characteristics of the transmission network, the multi-step backtracking α-Q(λ) algorithm with adaptive learning factor is designed. Then the mixed integer planning model is transformed into the agent and environment of in the α-Q(λ) algorithm to simulate the planning process of a power grid. The validity of the proposed method is verified by Garver-6 and IEEE 24-RTS system, and the comparison with other intelligent algorithms is shown.