{"title":"Bidirectional carbon emission flow analysis for the high-penetration renewable energy systems with distributed energy resources","authors":"Hanbing Zhang, Jichao Ye, Xinwei Hu, Hui Huang, Xinhua Wu, Yonghai Xu, Yuxie Zhou","doi":"10.1049/enc2.70019","DOIUrl":null,"url":null,"abstract":"<p>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, power grid planning, and low-carbon operations.</p>","PeriodicalId":100467,"journal":{"name":"Energy Conversion and Economics","volume":"6 4","pages":"213-224"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/enc2.70019","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Conversion and Economics","FirstCategoryId":"1085","ListUrlMain":"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/enc2.70019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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, power grid planning, and low-carbon operations.