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Robustness methodology to aid multiobjective decision making in the electricity generation capacity expansion problem to minimize cost and water withdrawal

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  • Jornada, Daniel
  • Leon, V. Jorge

Abstract

This paper deals with the electricity generation capacity expansion problem to minimize cost and water withdrawal. Each solution prescribes locations and technologies for new power plants, and their designed capacities. A two-stage methodology is proposed to aid decision making by identifying the few alternatives from the many efficient solutions that are robust to uncertainties. The first stage finds solutions that are efficient in view of cost and water withdrawal objectives. The second stage finds the subset of first-stage solutions that are robust when the designed capacities of power plants are subjected to uncertainties at the time of their construction. The methodology is applied in a case study for the electrical grid in Texas, USA. The trade-off among technologies and locations, and the effect of uncertainty are considered to answer strategic questions for expansion planning. Experimental results suggest that the methodology prescribes locations, capacities and type of technologies for new power plants in Texas that tend to maintain their prescribed values of cost and water withdrawal when facing unforeseen implementation conditions, while satisfying the required generation capacity.

Suggested Citation

  • Jornada, Daniel & Leon, V. Jorge, 2016. "Robustness methodology to aid multiobjective decision making in the electricity generation capacity expansion problem to minimize cost and water withdrawal," Applied Energy, Elsevier, vol. 162(C), pages 1089-1108.
    • Handle: RePEc:eee:appene:v:162:y:2016:i:c:p:1089-1108
    DOI: 10.1016/j.apenergy.2015.10.157
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    1. Fitiwi, Desta & Lynch, Muireann Á. & Bertsch, Valentin, 2019. "Optimal development of electricity generation mix considering fossil fuel phase-out and strategic multi-area interconnection," Papers WP616, Economic and Social Research Institute (ESRI).
    2. Tong Koecklin, Manuel & Fitiwi, Desta & de Carolis, Joseph F. & Curtis, John, 2020. "Renewable electricity generation and transmission network developments in light of public opposition: Insights from Ireland," Papers WP653, Economic and Social Research Institute (ESRI).
    3. Ji, Ling & Zhang, Bei-Bei & Huang, Guo-He & Xie, Yu-Lei & Niu, Dong-Xiao, 2018. "GHG-mitigation oriented and coal-consumption constrained inexact robust model for regional energy structure adjustment – A case study for Jiangsu Province, China," Renewable Energy, Elsevier, vol. 123(C), pages 549-562.
    4. Fitiwi, Desta Z. & Lynch, Muireann & Bertsch, Valentin, 2020. "Enhanced network effects and stochastic modelling in generation expansion planning: Insights from an insular power system," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    5. Lubega, William Naggaga & Stillwell, Ashlynn S., 2018. "Maintaining electric grid reliability under hydrologic drought and heat wave conditions," Applied Energy, Elsevier, vol. 210(C), pages 538-549.
    6. Lei, Shunbo & Pozo, David & Wang, Ming-Hao & Li, Qifeng & Li, Yupeng & Peng, Chaoyi, 2022. "Power economic dispatch against extreme weather conditions: The price of resilience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    7. Parkinson, Simon C. & Makowski, Marek & Krey, Volker & Sedraoui, Khaled & Almasoud, Abdulrahman H. & Djilali, Ned, 2018. "A multi-criteria model analysis framework for assessing integrated water-energy system transformation pathways," Applied Energy, Elsevier, vol. 210(C), pages 477-486.

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