Carbon Emission Analysis of Low-Carbon Technology Coupled with a Regional Integrated Energy System Considering Carbon-Peaking Targets

Analyzing the carbon emission behavior of a regional integrated energy system (RIES) is crucial for aligning with carbon-peaking development strategies and ensuring compliance with carbon-peaking implementation pathways. This study focuses on a building cluster area in Shanghai, China, aiming to provide a comprehensive analysis from both macro and micro perspectives. From a macro viewpoint, an extended STIRPAT model, incorporating the environmental Kuznets curve, is proposed to predict the carbon-peaking trajectory in Shanghai. This approach yields carbon-peaking implementation pathways for three scenarios: rapid development, stable development, and green development, spanning the period of 2020–2040. At a micro scale, three distinct RIES system configurations—fossil, hybrid, and clean—are formulated based on the renewable energy penetration level. Utilizing a multi-objective optimization model, this study explores the carbon emission behavior of a RIES while adhering to carbon-peaking constraints. Four scenarios of carbon emission reduction policies are implemented, leveraging green certificates and carbon-trading mechanisms. Performance indicators, including carbon emissions, carbon intensity, and marginal emission reduction cost, are employed to scrutinize the carbon emission behavior of the cross-regional integrated energy system within the confines of carbon peaking.

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Publication Details

Journal
Applied Sciences
Published
2024-09-13
DOI
https://doi.org/10.3390/app14188277
Citations
2
Primary Topic
Environmental Impact and Sustainability
Type
article
Field-Weighted Citation Impact
0.41

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article

Carbon Emission Analysis of Low-Carbon Technology Coupled with a Regional Integrated Energy System Considering Carbon-Peaking Targets

Yipu Zeng, Ting Yin, Yiming Shu, Yiru Dai
2 citations
Applied Sciences
Environmental Impact and Sustainability
0.41
article

Carbon Emission Analysis of Low-Carbon Technology Coupled with a Regional Integrated Energy System Considering Carbon-Peaking Targets

Yipu Zeng, Ting Yin, Yiming Shu, Yiru Dai
article en
2 citations

Abstract

Analyzing the carbon emission behavior of a regional integrated energy system (RIES) is crucial for aligning with carbon-peaking development strategies and ensuring compliance with carbon-peaking implementation pathways. This study focuses on a building cluster area in Shanghai, China, aiming to provide a comprehensive analysis from both macro and micro perspectives. From a macro viewpoint, an extended STIRPAT model, incorporating the environmental Kuznets curve, is proposed to predict the carbon-peaking trajectory in Shanghai. This approach yields carbon-peaking implementation pathways for three scenarios: rapid development, stable development, and green development, spanning the period of 2020–2040. At a micro scale, three distinct RIES system configurations—fossil, hybrid, and clean—are formulated based on the renewable energy penetration level. Utilizing a multi-objective optimization model, this study explores the carbon emission behavior of a RIES while adhering to carbon-peaking constraints. Four scenarios of carbon emission reduction policies are implemented, leveraging green certificates and carbon-trading mechanisms. Performance indicators, including carbon emissions, carbon intensity, and marginal emission reduction cost, are employed to scrutinize the carbon emission behavior of the cross-regional integrated energy system within the confines of carbon peaking.

Applied SciencesVol. 14(18)
Tongji University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Industry, innovation and infrastructure
Openalex Percentile: Top 42%
Environmental Impact and Sustainability
0.41
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Carbon Emission Analysis of Low-Carbon Technology Coupled with a Regional Integrated Energy System Considering Carbon-Peaking Targets — Yipu Zeng, Ting Yin, et al. · Applied Sciences (2024) | TGRS Research Map | TGRS