There is a global effort to incorporate pervasive sensors, actuators and data networks into national power grids. This Smart Grid offers deep monitoring and controls, but needs advanced analytics over millions of data streams for efficient and reliable operational decisions. This article focuses on Cloud technologies used in a scalable software platform for the Smart Grid Cyber-Physical System. Dynamic Demand Response (D2R) is a challenge application that we target on the USC campus microgrid to perform intelligent demand-side management and relieve peak load. Our platform offers an adaptive information integration pipeline to ingest dynamic data; a secure repository for researchers to share knowledge; scalable machine-learning models trained over massive datasets for agile demand forecasting; and a portal to visualize consumption patterns. Our design incorporates hybrid Clouds, including IaaS, PaaS, public and private, which suit the unique component needs for on-demand provisioning, massive scaling, and manageability, and helps us expand from the microgrid to the Los Angeles power grid.