With the increasing demand for environmental conservation and the rapid development of new energy sources, the integration of renewable energy into local energy systems has become a highly promising direction for development. This chapter begins by summarizing the challenges faced in the integration of renewable energy in areas such as power forecasting, stability analysis and computation, digital technology in power systems, and flexible interaction techniques. The digital technologies for renewable energy forecasting and prediction method based on an improved Temporal Convolutional Network (TCN) network, as well as feature modeling, are then proposed. Finally, the concept of a virtual power plant and its role in decentralized energy generation are discussed, and an artificial intelligence-empowered optimization model for peer-to-peer energy transactions between virtual power plants, based on the Deep Deterministic Policy Gradient (DDPG) algorithm, is presented. The effectiveness of the proposed method is verified with a test case study.