Proposed Extension of the U.S.–Caribbean Super Grid to South America for Resilience during Hurricanes

Rodney Itiki (), Madhav Manjrekar and Silvio Giuseppe Di Santo
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Rodney Itiki: Department of Electrical and Computer Engineering, University of North Carolina at Charlotte, Charlotte, NC 28223-0001, USA
Madhav Manjrekar: Department of Electrical and Computer Engineering, University of North Carolina at Charlotte, Charlotte, NC 28223-0001, USA
Silvio Giuseppe Di Santo: Department of Energy and Automation, University of Sao Paulo—USP, Sao Paulo 05508-010, Brazil

Energies, 2024, vol. 17, issue 1, 1-19

Abstract: Climate change mitigation, adaptation to intensifying hurricanes, and decarbonization challenges in developing countries emphasize the urgent need for resilient high-voltage grids to facilitate the expansion of renewables. This research explores the technical feasibility of extending the U.S.–Caribbean Super Grid to include the Virgin Islands, Guadeloupe, Martinique, Trinidad and Tobago, Guyana, Suriname, French Guyana, and the northeastern part of Brazil in South America. This proposed extension aims to capitalize on the recent introduction of a new generation of wind turbines certified for operation under strong hurricane forces. The research utilizes modeling and simulation techniques to evaluate the performance of the proposed extension. A method for modeling and estimating spatiotemporal wind power profiles is applied, and the results demonstrate a reduction in maximum wind power variability within the U.S.–Caribbean Super Grid. Depending on the hurricane trajectory, the variability is reduced from 56.6% to less than 43.2%. This reduction takes effect by distributing peak surplus wind power alongside the proposed U.S.–Caribbean–South America Super Grid (UCASG). The research concludes by acknowledging the merits and limitations of the study and discussing potential directions for future research in this field.

Keywords: assessment; hurricane-proof turbines; interconnection of power grids; spatiotemporal wind power profile; super grid; wind power variability; wind power forecasting (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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