Directed graph based carbon flow tracing for demand side carbon obligation allocation

Tao Sun; Donghan Feng; Teng Ding; Lixia Chen; Shi You

doi:10.1109/PESGM.2016.7741580

Directed graph based carbon flow tracing for demand side carbon obligation allocation

Tao Sun
, Donghan Feng
, Teng Ding
, Lixia Chen
, Shi You

Shanghai Jiao Tong University

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

In order to achieve carbon emission abatement, some researchers and policy makers have cast their focus on demand side carbon abatement potentials. This paper addresses the problem of carbon flow calculation in power systems and carbon obligation allocation at demand side. A directed graph based method for tracing carbon flow is proposed. In a lossy network, matrices such as carbon losses, net carbon intensity (NCI) and footprint carbon intensity (FCI) are obtained with the proposed method and used to allocate carbon obligation at demand side. Case studies based on realistic distribution and transmission systems are provided to demonstrate the effectiveness of the proposed method.

Original language	English
Title of host publication	Proceedings of 2016 IEEE Power and Energy Society General Meeting
Number of pages	5
Publisher	IEEE
Publication date	2016
ISBN (Print)	978-1-5090-4168-8
DOIs	https://doi.org/10.1109/PESGM.2016.7741580
Publication status	Published - 2016
Event	2016 IEEE Power Engineering Society General Meeting - Boston, United States Duration: 17 Jul 2016 → 21 Jul 2016 https://ieeexplore.ieee.org/xpl/conhome/7593872/proceeding

Conference

Conference	2016 IEEE Power Engineering Society General Meeting
Country/Territory	United States
City	Boston
Period	17/07/2016 → 21/07/2016
Internet address	https://ieeexplore.ieee.org/xpl/conhome/7593872/proceeding

Series	IEEE Power and Energy Society General Meeting
ISSN	1944-9933

Keywords

Carbon dioxide
Carbon
Load flow
Generators
Nickel
Resource management
low-carbon electricity
carbon flow
carbon obligation
demand response
graph theory

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10.1109/PESGM.2016.7741580

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@inproceedings{22614e76a93a4e638575358069c5d5ab,

title = "Directed graph based carbon flow tracing for demand side carbon obligation allocation",

abstract = "In order to achieve carbon emission abatement, some researchers and policy makers have cast their focus on demand side carbon abatement potentials. This paper addresses the problem of carbon flow calculation in power systems and carbon obligation allocation at demand side. A directed graph based method for tracing carbon flow is proposed. In a lossy network, matrices such as carbon losses, net carbon intensity (NCI) and footprint carbon intensity (FCI) are obtained with the proposed method and used to allocate carbon obligation at demand side. Case studies based on realistic distribution and transmission systems are provided to demonstrate the effectiveness of the proposed method.",

keywords = "Carbon dioxide, Carbon, Load flow, Generators, Nickel, Resource management, low-carbon electricity, carbon flow, carbon obligation, demand response, graph theory",

author = "Tao Sun and Donghan Feng and Teng Ding and Lixia Chen and Shi You",

year = "2016",

doi = "10.1109/PESGM.2016.7741580",

language = "English",

isbn = "978-1-5090-4168-8",

series = "IEEE Power and Energy Society General Meeting",

publisher = "IEEE",

booktitle = "Proceedings of 2016 IEEE Power and Energy Society General Meeting",

address = "United States",

note = "2016 IEEE Power Engineering Society General Meeting, PESGM 2016 ; Conference date: 17-07-2016 Through 21-07-2016",

url = "https://ieeexplore.ieee.org/xpl/conhome/7593872/proceeding",

}

Sun, T, Feng, D, Ding, T, Chen, L & You, S 2016, Directed graph based carbon flow tracing for demand side carbon obligation allocation. in Proceedings of 2016 IEEE Power and Energy Society General Meeting. IEEE, IEEE Power and Energy Society General Meeting, 2016 IEEE Power Engineering Society General Meeting, Boston, Massachusetts, United States, 17/07/2016. https://doi.org/10.1109/PESGM.2016.7741580

Directed graph based carbon flow tracing for demand side carbon obligation allocation. / Sun, Tao; Feng, Donghan; Ding, Teng et al.
Proceedings of 2016 IEEE Power and Energy Society General Meeting. IEEE, 2016. (IEEE Power and Energy Society General Meeting).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Directed graph based carbon flow tracing for demand side carbon obligation allocation

AU - Sun, Tao

AU - Feng, Donghan

AU - Ding, Teng

AU - Chen, Lixia

AU - You, Shi

PY - 2016

Y1 - 2016

N2 - In order to achieve carbon emission abatement, some researchers and policy makers have cast their focus on demand side carbon abatement potentials. This paper addresses the problem of carbon flow calculation in power systems and carbon obligation allocation at demand side. A directed graph based method for tracing carbon flow is proposed. In a lossy network, matrices such as carbon losses, net carbon intensity (NCI) and footprint carbon intensity (FCI) are obtained with the proposed method and used to allocate carbon obligation at demand side. Case studies based on realistic distribution and transmission systems are provided to demonstrate the effectiveness of the proposed method.

AB - In order to achieve carbon emission abatement, some researchers and policy makers have cast their focus on demand side carbon abatement potentials. This paper addresses the problem of carbon flow calculation in power systems and carbon obligation allocation at demand side. A directed graph based method for tracing carbon flow is proposed. In a lossy network, matrices such as carbon losses, net carbon intensity (NCI) and footprint carbon intensity (FCI) are obtained with the proposed method and used to allocate carbon obligation at demand side. Case studies based on realistic distribution and transmission systems are provided to demonstrate the effectiveness of the proposed method.

KW - Carbon dioxide

KW - Carbon

KW - Load flow

KW - Generators

KW - Nickel

KW - Resource management

KW - low-carbon electricity

KW - carbon flow

KW - carbon obligation

KW - demand response

KW - graph theory

U2 - 10.1109/PESGM.2016.7741580

DO - 10.1109/PESGM.2016.7741580

M3 - Article in proceedings

SN - 978-1-5090-4168-8

T3 - IEEE Power and Energy Society General Meeting

BT - Proceedings of 2016 IEEE Power and Energy Society General Meeting

PB - IEEE

T2 - 2016 IEEE Power Engineering Society General Meeting

Y2 - 17 July 2016 through 21 July 2016

ER -

Directed graph based carbon flow tracing for demand side carbon obligation allocation

Abstract

Conference

Keywords

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