Publication:
Assessment of Spatial and Temporal Modeling on Greenhouse Gas Emissions From Electricity Generation

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dc.citedby0
dc.contributor.authorSarhan A.en_US
dc.contributor.authorRamachandaramurthy V.K.en_US
dc.contributor.authorSin T.C.en_US
dc.contributor.authorWalker S.L.en_US
dc.contributor.authorSalman B.en_US
dc.contributor.authorPadmanaban S.en_US
dc.contributor.authorid57203979904en_US
dc.contributor.authorid6602912020en_US
dc.contributor.authorid57212007867en_US
dc.contributor.authorid37105142200en_US
dc.contributor.authorid57195282152en_US
dc.contributor.authorid18134802000en_US
dc.date.accessioned2024-10-14T03:21:27Z
dc.date.available2024-10-14T03:21:27Z
dc.date.issued2023
dc.description.abstractThis 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. � 2013 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ACCESS.2023.3258923
dc.identifier.epage97492
dc.identifier.scopus2-s2.0-85151556917
dc.identifier.spage97478
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85151556917&doi=10.1109%2fACCESS.2023.3258923&partnerID=40&md5=4ca2b8acd3dd0a709c46035561d7f5c0
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/34653
dc.identifier.volume11
dc.pagecount14
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofAll Open Access
dc.relation.ispartofGold Open Access
dc.relation.ispartofGreen Open Access
dc.sourceScopus
dc.sourcetitleIEEE Access
dc.subjectelectric vehicle
dc.subjectEnergy
dc.subjectenergy storage
dc.subjectGHG emissions
dc.subjectrenewable generation
dc.subjectDigital storage
dc.subjectElectric energy storage
dc.subjectElectric loads
dc.subjectFossil fuels
dc.subjectFuel storage
dc.subjectGas emissions
dc.subjectGreenhouse effect
dc.subjectGreenhouse gases
dc.subjectRenewable energy resources
dc.subjectSustainable development
dc.subjectElectricity-generation
dc.subjectEnergy
dc.subjectGeneration mix
dc.subjectGreenhouse gas emissions
dc.subjectLoad modeling
dc.subjectPower- generations
dc.subjectRenewable energy source
dc.subjectRenewable generation
dc.subjectSpatial and temporal modeling
dc.subjectTechno-economics
dc.subjectElectric vehicles
dc.titleAssessment of Spatial and Temporal Modeling on Greenhouse Gas Emissions From Electricity Generationen_US
dc.typeArticleen_US
dspace.entity.typePublication
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