摘要
利用STL(Seasonal-Trend decomposition using Loess,时间序列分解算法)模型对工业园区运行阶段的建筑碳排放进行预测分析,介绍电碳模型构建技术路线、模型构建的STL和线性回归,给出某高新园区2021年到2022年碳排放量的预测结果。可为园区规划双碳路径、制定减排计划、开展节能减排手段提供数据支撑,辅助园区实现绿色低碳发展目标。
STL(Seasonal-Trend decomposition using Loess)model is employed to predict and analyze the carbon emission of buildings in the operation stage in the industrical park,the technical route for electrical carbon model,STL model building and linear regression are introduced,and the prediction results of carbon emission in a high-tech industrial park from 2021 to 2022 are given.This paper can provide data support for the industrial park to plan the dual-carbon path,prepare emission reductionplanandcarryout energy conservation and emission reduction,and help the industrial park realize green and low-carbon development goals.
作者
汪海良
WANG Hailiang(Arcplus Institute of Shanghai Architectural Design&Research(Co.,Ld.),Shanghai 200041,China)
出处
《建筑电气》
2024年第7期3-6,共4页
Building Electricity
关键词
工业园区
建筑碳排放
碳排放预测模型
冷却度日
STL
线性回归
算法
拟合
industrial park
buildingcarbon emission
predictionmodel forcarbon 1emission
cooling degree days
STL
linear regression
algorithm
fitting
