Open AccessCorrelation Analysis and Forecast of Power Demand Based on Economic and Meteorological Factors
Author(s) -
Junyi Yang,
Yi Ge,
Zhiwei Xie,
Junhui Huang,
Li Hu,
Hui Zhou
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1650/3/032185
Subject(s) - upstream (networking) , downstream (manufacturing) , upstream and downstream (dna) , index (typography) , economic indicator , power grid , environmental science , power (physics) , environmental economics , econometrics , economy , economics , computer science , operations management , macroeconomics , telecommunications , physics , quantum mechanics , world wide web
Because the economic and meteorological factors are closely related to the level of power demand, this paper establishes an index system for the upstream and downstream industrial chains of important economic and leading industries. The XGBoost algorithm is used to study the quantitative indicators of economic and meteorological factors, and to analyse the time-difference relationship between the economy of the typical city Nanjing, the upstream and downstream industry chain indicators of the leading industry and the power indicators. Through the relevant data of the Nanjing Power Grid, this paper establishes and quantifies a model of the relationship between the economic and industrial chain information and power systems in Nanjing, and predicts the load in the future.