Intelligent Planning of Power Transmission and Transformation Projects Based on AI and Multi-source Heterogeneous Data Integration

The acceleration of smart grid construction imposes higher demands on the intelligent planning of power transmission and transformation projects. To address the inefficiencies and high costs in existing planning methods, this paper proposes an intelligent planning approach based on multi-source heterogeneous data integration and artificial intelligence. By integrating multi-source heterogeneous data to analyze on-site information, and utilizing Bayesian networks and Convolutional Neural Networks with Attention Mechanisms (CNNAM), the planning and construction processes of power transmission and transformation projects are optimized. This approach significantly improves the accuracy and reliability of cost estimation, providing strong data support and technical assurance for the intelligent planning of power transmission and transformation projects, thereby making the planning process more effective and practical.