Utilities have recently shown a considerable interest in extracting powerlines from laser scanning data for periodic utility monitoring. However, if the powerline runs through a forest, extraction is more difficult. A robust and exact power line model is crucial for adequate clearance and detecting potential hazards. Thus, this study establishes and automated method for reconstructing high-voltage bundle conductors. The powerline bundles at various heights are first recovered and divided into segments. The fitted residuals of each segment are used to estimate the number of sub-conductors. The point distance formula and 3D line fitting are used to extract individual sub-conductors. Each part is separated according to its positive and negative distance values. Finally, the sub-conductor segments are reassembled using a random sample consensus (RANSAC) technique. On five datasets, the proposed technique extracts and reconstructs individual sub-conductors with great precision.