This paper proposes a demand-side resource digital twin building method of multiple temporal-spatial scales based on physical model and digital model dynamic connascence. With the innovative mechanism and data complementation by dynamic connascence model, the physical properties and real-status status of the demand-side resources (such as energy storage, electric vehicle, flexible load) can be accurately mapped in virtual space to realize the virtual mapping of physical model and digital model, support the building of the demand-side adjustable resource digital twin, improve the response success rate and verify the effectiveness of the model.