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

被引:0
|
作者
Sarhan, Ameen [1 ]
Ramachandaramurthy, Vigna K. [1 ]
Sin, Tan Ching [1 ]
Walker, Sara L. [2 ]
Salman, Bello [3 ]
Padmanaban, Sanjeevikumar [4 ]
机构
[1] Univ Tenaga Nas, Inst Power Engn, Coll Engn, Dept Elect & Elect Engn, Jalan Ikram Uniten, Kajang 43000, Malaysia
[2] Newcastle Univ, EPSRC Natl Ctr Energy Syst Integrat, Sch Engn, Newcastle Upon Tyne NE1 7RU, England
[3] Kaduna State Univ, Ctr Energy & Environm Strategy Res, Tafawa Balewa Way,PMB 2339, Kaduna, Nigeria
[4] Univ South Eastern Norway, Dept Elect Engn IT & Cybernet, N-3918 Porsgrunn, Norway
来源
IEEE ACCESS | 2023年 / 11卷
关键词
Renewable energy sources; Load modeling; Power generation; Greenhouse effect; Data models; Fossil fuels; Energy storage; Energy; GHG emissions; renewable generation; energy storage; electric vehicle; LIFE-CYCLE ASSESSMENT; RENEWABLE ENERGY-SOURCES; POWER-GENERATION; CO2; EMISSIONS; SYSTEMS; LCA;
D O I
10.1109/ACCESS.2023.3258923
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This 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.
引用
收藏
页码:97478 / 97492
页数:15
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