Abstract: Utilizing electricity consumption data from the Beijing-Tianjin-Hebei urban agglomeration, this study constructs a synergistic network for the transition from old to new growth drivers and delineates its spatial network structure. The research aims to explain the mechanisms through which the synergy network achieves enhanced connectivity, increased synergy intensity, and cross-regional diffusion. The analytical framework progresses sequentially from characterizing the phenomenon and interpreting the structure to identifying the underlying mechanisms. First, at the network level, the results indicate that synergistic linkages expanded overall over the sample period, and that overall connectivity is strong. However, network density remains relatively low, and structural concentration is high, suggesting that the formation and strengthening of synergistic ties rely heavily on a few key nodes. Structurally, analyses based on centrality and block models reveal a distinct role differentiation into core, hub, and peripheral cities, as well as a sectoral division characterized by the coexistence of net-spillover, net-beneficiary, and bidirectional-interaction blocks. Beijing and Tianjin play pivotal leading and core agglomeration roles, while the hub functions of cities like Tangshan are rising. In contrast, participation from some peripheral cities remains limited, which explains the structural constraints on increasing network density. At the mechanism level, the QAP regression results show that innovation proximity—that is, similarity in R&D investment—and geographical proximity significantly promote the formation and strengthening of synergistic linkages. Based on these findings, this paper proposes an incentive mechanism for joint R&D and joint demonstration oriented toward cross-city co-production and a hub-city-based mechanism for sharing and diffusing outcomes. In addition, given that the estimated coefficient on structural isomorphism in energy-intensive sectors is negative but statistically insignificant across all sample years, it recommends optimizing rules for differentiated specialization and factor mobility to guard against the risk of homogeneous competition. These measures aim to enhance the quality of regional synergistic relationships and advance the coordinated development of the transition from old to new growth drivers.