Planning strategies for distributed photovoltaic based on fuzzy cognitive maps

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.