Open AccessOverview of the Application of Energy Consumption Forecast Models in Energy Efficiency Optimization
Author(s) -
Ren Liu,
Zhonghang Wang,
Haihong Chen,
Jie Yang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/831/1/012012
Subject(s) - energy consumption , computer science , consumption (sociology) , efficient energy use , energy (signal processing) , energy accounting , perspective (graphical) , energy conservation , industrial engineering , artificial intelligence , engineering , mathematics , social science , statistics , sociology , electrical engineering
Energy consumption analysis, and energy demand forecasting and energy conservation effect evaluation based on such analysis are important bases for energy efficiency management. The wide application of AI machine learning methods in energy consumption forecasting not only expands the research route of energy consumption forecasting, but also provides a new perspective for energy efficiency optimization. The purpose of this article is to summarize the important applications of AI machine learning methods in the research of energy consumption forecasting-data-driven models and traditional forward models, and the comparison and application of the two types of models, and conclude the common application scenarios and technical routes of forecast models in the research of energy efficiency optimization so as to provide comprehensive model methods, application scenarios, forecast conditions and other multi-dimensional bases for energy consumption forecasting researchers. On this basis, the research questions and development needs in the research of energy consumption forecasting at the application and basic levels are raised herein.