摘要
建筑用电能耗预测是建筑能源管理的重要组成部分,准确预测建筑用电能耗可以帮助管理者制定有效的能源策略,提高能源利用效率。本文介绍了建筑用电能耗预测的特性及分类,将建筑用电能耗预测研究分为工程方法、统计方法、机器学习方法、深度学习方法及组合方法进行阐述,总结这些方法的优缺点,并展望建筑用电能耗预测的未来发展方向。
Building electricity consumption prediction is an important part of building energy management.Accurate prediction of building electricity consumption can help managers formulate effective energy strategies and improve energy efficiency.This paper introduces the characteristics and classification of building electricity consumption prediction,and divides the research of building electricity consumption prediction into engineering method,statistical method,machine learning method,deep learning method and combined method.The advantages and disadvantages of these methods are the future development direction of building electricity consumption prediction are discussed.
作者
常依婷
张素莉
尤光昊
CHANG Yiting;ZHANG Suli;YOU Guanghao(School of Energy and Power Engineering,Changchun Institute of Technology,Changchun 130103;School of Computer Technology and Engineering,Changchun Institute of Technology,Changchun 130103)
出处
《中国建材科技》
CAS
2024年第3期88-93,共6页
China Building Materials Science & Technology
基金
吉林省科技厅项目(20210203103SF)。
关键词
建筑能耗
工程方法
统计法
机器学习法
深度学习法
组合方法
building energy consumption
engineering method
statistical method
machine learning method
deep learning method
combined method
作者简介
通讯作者:张素莉(1974-),博士,教授,主要从事智能信息处理的研究。
