With the increasing penetration of distributed photovoltaic (PV) generation in distribution grids, PV access locations significantly affect voltage stability and network losses. In this paper, we proposed a critical node identification and PV access planning method based on fuzzy cognitive maps (FCMs). An FCM-based distribution grid model was established by incorporating time-varying load characteristics and PV output fluctuations, and the weight matrix was learned from historical operating data using a data-driven optimization approach. A node importance index derived from out-degree centrality was then proposed to identify critical nodes in the distribution grid. Simulation studies on the IEEE 33-node and 118-node standard test systems under different PV penetration levels demonstrated that connecting PV to non-critical nodes effectively mitigates voltage fluctuations and reduces system power losses compared with critical-node-based access strategies. The proposed method provides an interpretable and effective decision-support tool for distributed PV integration in distribution grids.