Research on the construction of power grid electricity consumption data management system driven by artificial intelligence

With the deep development of the power system, the power grid's electricity consumption data exhibits the characteristics of high frequency, high dimension, and multisource heterogeneity. Traditional data management methods are unable to meet the requirements of intelligent dispatching and real-time monitoring. This paper proposes an electricity consumption data management system driven by artificial intelligence, which includes aspects such as data collection, preprocessing, modeling analysis, and dispatch feedback. It establishes a hierarchical structure and multimodel integration architecture. By using deep learning and data fusion technologies, the accuracy of data processing, the precision of prediction results, and the timeliness of system response are improved. The experimental results prove that this system has good feasibility and adaptability.