Abstract
The rapid development of big data and artificial intelligence technology provides a good way to analyze the factors of power demand changes. In this paper, the meteorological factors that affect power demand are studied in depth, and a meteorological factor index system for power demand change is established. Based on the identification method of dominant meteorological factors, the coupling relationship between meteorological factors and power loads is quantitatively evaluated; The sensitivity of load changes in commercial, residential and industrial industries under typical scenarios is analyzed, and the relationship between dominant meteorological factors and quantification affecting the load changes in summer and winter is studied. Finally, the validity of this model is verified by the sensitivity analysis and prediction of power load characteristics to meteorological information based on the data of Nanjing power network.
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