Low-Carbon Power Grid Economic Assessment Model Based on CNN and LSTM

In the context of a complex power grid environment, it is crucial to analyze and optimize power system planning and operational strategies to enhance energy efficiency and reduce the carbon emissions intensity of the system. Given the multitude of indicators and external factors affecting grid planning and development, accurately assessing and rating the development status of the grid can help in understanding developmental patterns. Therefore, this paper employs a combined CNN and LSTM model to predict grid benefits. Subsequently, based on the prediction results, it utilizes fuzzy comprehensive evaluation to conduct an economic assessment, providing planning regulators with insights into the economic feasibility and associated risks of grid projects. The proposed methodology is applied to actual grid data through case analysis, demonstrating that the rating results align with reality. Consequently, this assessment model exhibits a high level of accuracy and superiority.