<p>This paper addresses the challenges of multi-attribute group decision-making (MAGDM) in planning active distribution networks (ADNs) with high renewable energy penetration and proposes a comprehensive decision-making framework. First, Pythagorean fuzzy sets (PFSs) are employed to simultaneously quantify membership and non-membership degrees, thereby effectively handling the uncertainty, fuzziness, and contradictions in expert evaluations. Second, a structural hole–behavioral similarity weighting method is developed to determine expert weights by considering both network structural positions and behavioral similarities, assigning higher weights to experts located in bridging positions. Finally, the combined compromise solution (CoCoSo) method is adopted to integrate evaluations and rank alternatives based on the derived weights. The proposed framework is applied to the microgrid optimization management of an industrial park in Taiyuan within an active distribution network. Sensitivity and comparative analyses are conducted to verify the robustness, feasibility, and effectiveness of the approach. The results demonstrate that the proposed framework not only produces reliable and interpretable rankings but also provides valuable insights for experts in planning and managing active distribution networks with high renewable energy integration.</p>