Open AccessSensitivity Analysis and Forecast of Power Load Characteristics Based on Meteorological Feature Information
Author(s) -
Li Hu,
Jian Tan,
Jun Han,
Yi Ge,
Dehua Guo
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/558/5/052060
Subject(s) - sensitivity (control systems) , identification (biology) , environmental science , power (physics) , index (typography) , meteorology , electric power system , computer science , engineering , geography , electronic engineering , botany , physics , quantum mechanics , world wide web , biology
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.