Massive heterogeneous flexibility resources are connected to the grid on a large scale, and there are differences between transmission and distribution network flexibility resources in terms of time, space, capacity, and responsiveness. To cope with the challenge of how to efficiently tap the regulation capability of such resources, a cooperative scheduling strategy for transmission and distribution networks considering partitional clustering of massive resources is proposed. First, considering the differentiated characteristics of the flexibility resources of the transmission and distribution network, a model for regulating high energy-carrying loads and civil loads is established. Next, based on the concept of digital-analog fusion, an assessment method and index of adjustable potential of partitional clustering for massive heterogeneous resources are proposed. Then, a day-ahead-intraday multi-timescale transmission and distribution network demand response strategy model is developed, taking into account transmission and distribution resource regulation model differentiation as well as the new energy prediction bias. Finally, simulation verification is carried out on the improved transmission and distribution system, and the results show that the proposed strategy can coordinate the massive heterogeneous resources of the transmission and distribution network to participate in the demand response, and effectively improve the system operational economy, with the peak shaving rate reaching 38.3%, and the wind and light abandonment rate reduced by 11.39%.