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Design optimization model for the integration of renewable and nuclear energy in the United Arab Emirates’ power system

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  • Almansoori, Ali
  • Betancourt-Torcat, Alberto

Abstract

A Mixed Integer Linear Programming (MILP) formulation is presented for the optimal design of the United Arab Emirates’ (UAE) power system. The model was formulated in the General Algebraic Modeling System (GAMS), which is a mathematical modeling language for programming and optimization. Previous studies have either focused on the estimation of the UAE’s energy demands or the simulation of the operation of power technologies to plan future electricity supply. However, these studies have used international simulation tools such as “MARKAL” and “MESSAGE”; whereas the present work presents an optimization model. The proposed design optimization model can be used to estimate the most suitable combination of power plants under CO2 emission and alternative energy targets, carbon tax, and social benefits of air emissions avoidance. Although the proposed model was used to estimate the future power infrastructure in the UAE, the model includes several standard power technologies; thus, it can be extended to other countries. The proposed optimization model was verified using historical data of the UAE power sector operation in the year 2011. Likewise, the proposed model was used to study the 2020 UAE power sector operations under three scenarios: domestic vs. international natural gas prices (considering different carbon tax levels), social benefits of using low emission power technologies (e.g., renewable and nuclear), and CO2 emission constraints. The results show that the optimization model is a practical tool for designing the UAE power infrastructure, evaluating future production technologies and scenarios, and identifying key parameters affecting the UAE power sector.

Suggested Citation

  • Almansoori, Ali & Betancourt-Torcat, Alberto, 2015. "Design optimization model for the integration of renewable and nuclear energy in the United Arab Emirates’ power system," Applied Energy, Elsevier, vol. 148(C), pages 234-251.
    • Handle: RePEc:eee:appene:v:148:y:2015:i:c:p:234-251
    DOI: 10.1016/j.apenergy.2015.03.068
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    6. Batoul Modarress & Alexander Ansari & Al Ansari, 2020. "Sustainable Development and Ecological Deficit in the United Arab Emirates," Sustainability, MDPI, vol. 12(15), pages 1-19, July.
    7. Guo, Zheng & Cheng, Rui & Xu, Zhaofeng & Liu, Pei & Wang, Zhe & Li, Zheng & Jones, Ian & Sun, Yong, 2017. "A multi-region load dispatch model for the long-term optimum planning of China’s electricity sector," Applied Energy, Elsevier, vol. 185(P1), pages 556-572.
    8. Jui-Yuan Lee & Han-Fu Lin, 2019. "Multi-Footprint Constrained Energy Sector Planning," Energies, MDPI, vol. 12(12), pages 1-18, June.
    9. Zheng, Xuyue & Wu, Guoce & Qiu, Yuwei & Zhan, Xiangyan & Shah, Nilay & Li, Ning & Zhao, Yingru, 2018. "A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China," Applied Energy, Elsevier, vol. 210(C), pages 1126-1140.
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