Hanbing Zhang, Jichao Ye, Xinwei Hu, et al. Bidirectional carbon emission flow analysis for the high-penetration renewable energy systems with distributed energy resources[J]. Energy Conversion and Economics, 2025, 6(4).
DOI:
Hanbing Zhang, Jichao Ye, Xinwei Hu, et al. Bidirectional carbon emission flow analysis for the high-penetration renewable energy systems with distributed energy resources[J]. Energy Conversion and Economics, 2025, 6(4). DOI: 10.1049/enc2.70019.
Bidirectional carbon emission flow analysis for the high-penetration renewable energy systems with distributed energy resources
摘要
Abstract
High-penetration renewable energy systems (HPRES) are characterized by the extensive deployment of distributed energy resources (DERs)
such as the grid-side independent storage
consumer-side distributed storage
and the combination of consumer-side distributed storage with distributed photovoltaics and wind turbines. Additionally
numerous DERs interacting with the grid significantly vary the operating characteristics of the grid. These changes introduce significant complexity in the analysis of carbon emissions
thereby necessitating advanced methodologies to accurately capture and manage the impact of these DERs on the overall carbon footprint of the power system. This study presents a novel methodology for accurately quantifying the distribution of carbon emissions in power systems comprising DERs. To the underlying concept of this approach is the quantification of the carbon emission characteristics
which is achieved by analysing the carbon emission intensity specific to various DERs. We further analyse the impact of these entities on the flow of electricity carbon emissions. To comprehensively address these dynamics
we develop a bidirectional electricity carbon emission flow model corresponding to the unique attributes of the emerging HPRES. To demonstrate the viability and effectiveness of the proposed approach
we perform a simulation based on the modified IEEE 39-bus system
along with a comparison with the original carbon-emission flow model. The findings of this study contribute significantly to research on the demand response