报告详情
Research on Monthly Carbon Emission Monitoring Methods and Carbon Reduction Pathways in Industrial Parks
编号：56
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更新：2025-10-11 22:35:48 浏览：2次
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摘要
Accurate monitoring of carbon emissions in industrial parks is essential for achieving China’s “dual carbon” goals. Traditional methods, however, are limited by data lag and static emission factors, failing to support dynamic carbon management. This study integrates 52 months of multi-dimensional data—including electricity consumption, meteorological conditions, and production indicators—from a zero-carbon industrial park in Yunnan Province from 2021 to 2025. This Paper construct a feature engineering system incorporating temporal, lagged, and interaction terms. Using time-series cross-validation and the LightGBM algorithm, and establish a dynamic “electricity-energy-carbon” monitoring framework. This enables real-time carbon tracking through adaptive factor calibration and quantifies emission reduction benefits via a multi-objective optimization model. Our approach reveals synergies between production optimization and energy transition, offering a reusable, standardized monitoring process to support low-carbon transformation in industrial parks.
关键词
Industrial parks,Emission reduction pathways,LightGBM model,Carbon emission monitoring,Carbon emission management
报告人
永丽 阮
高级工程师 云南电网有限责任公司昆明供电局稿件作者
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重要日期
-
会议日期
11月07日
2025
至11月09日
2025
-
10月12日 2025
初稿截稿日期
-
10月20日 2025
注册截止日期
主办单位
IEEE西南交通大学IAS学生分会
承办单位
西南交通大学电气工程学院
SPACI车网关系研究室
四川大学电力系统稳定与高压直流输电研究团队
SPACI车网关系研究室
四川大学电力系统稳定与高压直流输电研究团队
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