Sustainability is vital in balancing human needs with environmental preservation, with solar energy playing a key role. The variety of solar panels available can cause hesitancy in selecting the best option. To address this, Pythagorean fuzzy sets ( \(\textrm{PFS}\) s) with similarity measures ( \(\textrm{SMs}\) ) offer a promising solution by extending fuzzy and intuitionistic fuzzy sets. However, measuring similarity between \(\textrm{PFS}\) s accurately remains challenging, with existing \(\textrm{SMs}\) often producing counterintuitive results. We propose a novel 3D similarity measure incorporating hesitancy degrees for \(\textrm{PFS}\) s and validate it through comprehensive comparative analysis and graphical representation, demonstrating its superior efficacy. Additionally, we introduce an innovative hybrid multiple criteria decision-making ( \(\textrm{MCDM}\) ) methodology within a Pythagorean fuzzy environment. This integrates subjective weight assessments via stepwise weight assessment ratio analysis (SWARA) and ranks solar panels using the technique for order of preference by similarity to the ideal solution ( \(\textrm{TOPSIS}\) ). A thorough comparative analysis highlights the practicality and efficiency of our proposed model compared to existing techniques.