@article{Sha2026, 
author = {Jiancheng Sha and Shaojun Bian and Lingfang Sun and Mengchao Xu and Guoliang Feng},
title = {Planning strategies for distributed photovoltaic based on fuzzy cognitive maps},
year = {2026},
journal = {AIMS Electronics and Electrical Engineering},
volume = {10},
number = {2},
pages = {180-204},
keywords = {fuzzy cognitive maps, intelligent computing, distribution grid, photovoltaic, energy loss},
url = {https://www.sciopen.com/article/10.3934/electreng.2026008},
doi = {10.3934/electreng.2026008},
abstract = {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.}
}