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Assessment of spatial and temporal modelling on greenhouse gas emissions from electricity generation

Lookup NU author(s): Professor Sara Walker

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

AuthorThis paper highlights the importance of precise assessments of greenhouse gas (GHG) emissions associated with power generation for effective policy making in environmental sustainability. The current assessment approaches based on historical data or estimated generation using energy models may not accurately reflect the reality of future power systems due to the impact of spatial-temporal and techno-economic characteristics of generation mix and load demands. To address this, the paper presents a comprehensive methodology for accurately quantifying the geographical and temporal variations in GHG emissions associated with generating units’ operation, startup, and shutdown at an hourly resolution. The methodology is based on a detailed electricity model that considers various sources of generation, techno-economic, and spatial-temporal characteristics of system components. The study demonstrates the effectiveness of the methodology in quantifying GHG emissions in the IEEE RTS-GLMC system, with a focus on CO2, N2O, and CH4. The analysis reveals significant variations in GHG emissions among different generation buses and hours of the year, attributed to the high proportion of renewable energy in the generation mix. The paper emphasizes the inadequacy of examining marginal environmental impacts based on GHG emission intensity alone and suggests a more thorough analysis based on total GHG emissions generation. Finally, the paper emphasizes the crucial role of time-varying and marginal assessment techniques in identifying effective strategies for reducing GHG emissions in the electricity sector, including optimizing the operation and capacity of generation units, energy storage systems, and electric vehicles, including their locations.


Publication metadata

Author(s): Sarhan A, Ramachandaramurthy VK, Sin TC, Walker S, Salman B, Padmanaban S

Publication type: Article

Publication status: Published

Journal: IEEE Access

Year: 2023

Volume: 11

Pages: 97478-97492

Online publication date: 17/03/2023

Acceptance date: 02/04/2022

Date deposited: 27/04/2023

ISSN (electronic): 2169-3536

Publisher: Institute of Electrical and Electronics Engineers Inc.

URL: https://doi.org/10.1109/ACCESS.2023.3258923

DOI: 10.1109/ACCESS.2023.3258923


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Funding

Funder referenceFunder name
10.13039/501100008561
BOLDREFRESH2025–Centre of Excellence Grant
J510050002/2021169
Universiti Tenaga Nasional, Malaysia, for providing the BOLD Research Grant 2/2021

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