电力需求侧管理2025，Vol.27Issue(6)：78-84,7.DOI:10.3969/j.issn.1009-1831.2025.06.012
基于AOBP的空调能耗特征标签模型与预测方法
Feature labeling model and prediction method for air conditioning energy consumption based on AOBP
摘要
Abstract
Against the backdrop of the escalating global energy and environmental crisis,accurate prediction of air conditioning energy consumption is crucial for formulating effective energy-saving policies,optimizing energy utilization,reducing energy pressure,and reduc-ing carbon emissions,as air conditioning energy consumption accounts for a large proportion of the entire building energy consumption.A data-driven air conditioning energy consumption prediction method is proposed based on a probability model of air-conditioning occupant behavior.Firstly,based on the analysis of the relationship between air conditioning energy consumption and factors such as air-condition-ing occupant behavior,environmental parameters,time,and building,a feature label system for building air conditioning energy efficiency analysis is further constructed,covering multiple dimensions such as air conditioning occupant behavior,environment,time,and building characteristics.Secondly,the air-conditioning occupant behavior probability(AOBP)model is introduced as a factor to reflect the real-time interaction between the building environment,air conditioning occupants,and energy systems.This model considers the effects of strategy,time,events,and external stimuli,thus providing a more comprehensive estimation of air conditioning usage.Finally,particle swarm optimization algorithm is utilized to optimize the long short term memory network(LSTM)and to predict energy consumption across various building types and air conditioning systems.The simulation experiment results show that the proposed data-driven air condi-tioning energy consumption prediction method has made significant progress in improving prediction performance,but the calculation time has also correspondingly increased.关键词
空调能耗预测/空调使用行为概率/数据驱动/改进长短时记忆网络Key words
air-conditioning energy consumption prediction/air-conditioning occupant behavior probability/data driven/improving long short-term memory network分类
管理科学引用本文复制引用
任禹丞,王雨薇,郑杨,杨子跃,刘京易..基于AOBP的空调能耗特征标签模型与预测方法[J].电力需求侧管理,2025,27(6):78-84,7.基金项目
国网江苏省电力有限公司科技项目(J2023176) （J2023176）
