To meet the need for a ultra-reliable and low-latency service transmission of large-scale equipment access in substations, we propose a multi-frequency heterogeneous wireless communication network access selection algorithm for substation services. Considering the reliability and effectiveness requirements of these services, we firstly construct a substation scenario model under heterogeneous wireless network coverage. Secondly, to effectively improve the freshness of the information received, we utilize the Average Age of Information (AAoI) as the optimization target function of wireless network access selection and propose the optimization problem of substation service access selection based on the age of information. Finally, we implement the Deep Q-Learning (DQN) method to obtain the best access selection scheme. It can be seen from the analysis of the application examples and the test data that the proposed access selection optimization theory and algorithm can reduce the average age of information during service transmission and improve the freshness of data.