Planning strategies for distributed photovoltaic based on fuzzy cognitive maps

Jiancheng Sha; Shaojun Bian; Lingfang Sun; Mengchao Xu; Guoliang Feng; Jiancheng Sha; Shaojun Bian; Lingfang Sun; Mengchao Xu; Guoliang Feng

doi:10.3934/electreng.2026008

AIMS Electronics and Electrical Engineering

2026, Volume 10, Issue 2: 180-204. doi: 10.3934/electreng.2026008

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Planning strategies for distributed photovoltaic based on fuzzy cognitive maps

1.
School of Automation Engineering, Northeast Electric Power University, Jilin City, China
2.
School of Creative and Digital Industries, Buckinghamshire New University, High Wycombe HP11 2JZ, UK
3.
School of Control and Computer Engineering, North China Electric Power University, Beijing, China

Received: 16 October 2025 Revised: 08 January 2026 Accepted: 26 January 2026 Published: 02 March 2026

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.
- fuzzy cognitive maps,
- intelligent computing,
- distribution grid,
- photovoltaic,
- energy loss
Citation: Jiancheng Sha, Shaojun Bian, Lingfang Sun, Mengchao Xu, Guoliang Feng. Planning strategies for distributed photovoltaic based on fuzzy cognitive maps[J]. AIMS Electronics and Electrical Engineering, 2026, 10(2): 180-204. doi: 10.3934/electreng.2026008

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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.

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