Abstract: With the widespread application of smart meters in the power system, accurate collection and real-time monitoring of load data have become important components of smart grid construction. However, existing smart meters are often affected by environmental factors, hardware failures, communication interruptions, and other factors during data collection, resulting in missing or inaccurate load data, which in turn affects the operational efficiency and management decisions of the power system. Therefore, the method of supplementing load data has become a key technical issue in the field of smart meters. This article proposes a load data supplementation method based on intelligent algorithms. Firstly, this article analyzes the supplementary demand and challenges of smart meter load data, and summarizes the advantages and disadvantages of existing technologies; then, a load data supplementation algorithm was designed, which can efficiently supplement data based on historical data and changes in power load patterns; subsequently, a complete smart meter load data supplementation system architecture was proposed, and the effectiveness and feasibility of the method were verified through experiments.