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Nowadays, there are more and more electric appliances constituting power load in the power grid system. Among them, the proportion of load affected by weather, such as air conditioning, keeps increasing. Therefore, the influence of meteorological factors (temperature, humidity, rainfall, etc.) on the power grid is more and more prominent. Considering meteorological factors becomes one of the main means for the dispatching center to further improve the load forecasting accuracy. According to the load data of a certain area for six years, the Kalman filter model can give the accurate and efficient prediction results. Then, the meteorological factors are taken into account in the adaptive Kalman filter model, and the load prediction results with meteorological factors taken into account are more accurate through constant modification of the state estimation. Through the MATLAB simulation, it shows that the algorithm is more accurate than traditional Kalman filter, and the modified algorithm provides a new way for short-term load forecasting.