Clean energy technology innovation is an important support for China to achieve green energy transformation, and policy intervention can provide necessary support and incentives for technological innovation. By applying social network analysis, we construct an interprovincial clean energy enterprise technological innovation spatial correlation network in China, dividing different sectors of technological innovation distribution. Furthermore, we employ the index random graph model to empirically examine the effects of demand-driven, environment-driven, and supply-driven policies on the formation mechanism of clean energy enterprise technological innovation networks. The study finds that the clean energy technology innovation network in China shows a trend of closeness and robustness, with regions demonstrating a " The strong get stronger" characteristic in the network. Demand-driven and environment-driven policies significantly influence the emission and reception relationships of technological innovation, while supply-driven policies only promote the reception relationships of technological innovation significantly in the early stage of industrial development. Therefore, it is essential to focus on the relationship between innovative sectors, collaboratively formulate industrial innovation policies, and drive the integration of innovation networks.