Open AccessResearch on distributed photovoltaic power generation prediction based on grey model for energy Internet of city
Author(s) -
Hao Li,
Chang Liu,
Wen Li,
Chao Liu,
Bin Li
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/440/3/032011
Subject(s) - photovoltaic system , renewable energy , beijing , reliability engineering , computer science , power (physics) , electric power system , distributed generation , electricity generation , energy (signal processing) , automotive engineering , real time computing , engineering , electrical engineering , statistics , mathematics , china , political science , law , physics , quantum mechanics
Power load forecasting is one of the basic tasks of power system dispatching coordination and rational arrangement of energy production. Reasonable power load forecasting can ensure safe, continuous and stable energy supply, and provide reasonable guarantee for the safe and economic operation of power system. Based on Beijing’s new energy and renewable energy online monitoring system, this paper collects power generation data, environmental data and equipment working condition data, and uses gray model prediction method to predict the load of photovoltaic power station, and obtain more accurate power load data, which is complex fluctuation. The photovoltaic power generation project provides the basis for post-generation planning.