Virtual Power Plant Transaction Technology and Mechanism Based on Artificial Intelligence and Blockchain

How to improve the transaction efficiency and security of VPP in the power market and how to improve the responsiveness of VPP through technical means are an urgent problem to be solved. This study explores the virtual power plant (VPP) transaction technology and mechanism based on convolutional neural network (CNN) and blockchain technology to solve the transaction efficiency and security problems of VPP in the power market and improve its responsiveness. The study first uses CNN to intelligently match multiple users with different needs in VPP, then introduces the energy blockchain network, and proposes an improved VPP operation scheduling model. On this basis, smart contracts are developed to realize the automated transaction and settlement of VPP, and a new type of peer-to-peer (P2P) energy trading solution is proposed. In addition, a virtual power plant power trading model and a certificate trading model are constructed, and the frequency aggregation response characteristics of VPP are refined from the three dimensions of time, space, and cost. Finally, it is explored how blockchain technology can assist VPP to achieve more refined management. The research in this paper provides new ideas and methods for the further combination of VPP and blockchain technology to optimize the power market structure. The experiment found that the VPP transaction mechanism integrating CNN and blockchain technology has improved transaction efficiency, transaction security and responsiveness, and the average failure rate has been reduced from 0.282% of the traditional mechanism to 0.191%. The minimum response delay and maximum response delay are better than the traditional mechanism, reaching 139ms and 245ms respectively. This study provides a safe, efficient and transparent transaction and operation scheduling mechanism for VPP to adapt to the market mechanism and improve the market competitiveness of VPP.