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A green electrical matrix-based model for the energy transition: Maine, USA case example.

Authors :
Gil-García, Isabel C.
Fernández-Guillamón, Ana
García-Cascales, M. Socorro
Molina-García, Angel
Dagher, Habib
Source :
Energy. Mar2024, Vol. 290, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Nowadays, climate change is a major global societal challenge that significantly increases environmental stress. Most international organizations and policies have promoted initiatives to minimize emissions, reduce fossil fuel dependence and increase renewable energy resource integration into different sectors. An energy transformation towards more renewable systems is thus a priority. Under this scenario, the present paper describes and evaluates an alternative energy conversion matrix-based model to combine sector electrification, power generation units from renewables, and new clean technologies. The proposed green matrix-based model allows analyzing future scenarios, including electricity participation in end-use consumption and electric power generated by renewables – potentially integrated into different sectors –. The proposed model is evaluated in the state of Maine (United States). This case study is focused on decarbonizing both residential heating and transport sector through the integration of large offshore wind power plant. Results and discussion is also included in the paper, providing expected energy demand reductions and decreasing emissions through the integration of renewables. This energy transition integration case study is proposed in three road-maps with different penetration rates and time scales. The proposed green matrix-based model can be also applied to other areas and energy resources, as an alternative way to analyze and estimate renewable integration into different sectors. • Green Electrical Matrix to link electricity supply and end-use for energy transition. • Assesses renewable potential and electrification tech for end uses, e.g., transport. • Applies model to Maine, USA to show reductions in fossil fuels and emissions. • GIS and MCDM for optimal offshore wind location, maximizing electricity generation. • Short, medium, and long-term projections of renewable integration into energy system. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03605442
Volume :
290
Database :
Academic Search Index
Journal :
Energy
Publication Type :
Academic Journal
Accession number :
175030410
Full Text :
https://doi.org/10.1016/j.energy.2024.130246