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Generation expansion planning considering health and societal damages – A simulation-based optimization approach

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  • Rodgers, Mark D.
  • Coit, David W.
  • Felder, Frank A.
  • Carlton, Annmarie

Abstract

Electricity generation expansion planning models determine the optimal technology-capacity-investment strategy that minimizes market costs including investment costs, and fixed and variable operating & maintenance costs over a long-term planning horizon. From a market cost perspective, fossil fuels are among the most economical sources of electricity, and thus are the primary sources of energy for electricity. However, these energy sources create by-products that have harmful health effects upon exposure. In this paper, a simulation-based, metamodeling approach is leveraged to quantify health damages associated with power grid expansion decisions by linking the outputs of generation expansion planning simulations with a screening tool that quantifies the human health damages from the electricity sector. Using this as a surrogate function for health damages, these costs are included in the objective function of a generation expansion planning model, in addition to market costs and the social damages of carbon emissions and methane leakage to minimize societal damages. Applying an improvement algorithm, candidate data points are selected to enhance metamodel prediction capability. Finally, using an updated metamodel, a new expansion plan is found. This framework enables researchers to better understand the health implications of long-term capacity expansion decisions.

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  • Rodgers, Mark D. & Coit, David W. & Felder, Frank A. & Carlton, Annmarie, 2018. "Generation expansion planning considering health and societal damages – A simulation-based optimization approach," Energy, Elsevier, vol. 164(C), pages 951-963.
  • Handle: RePEc:eee:energy:v:164:y:2018:i:c:p:951-963
    DOI: 10.1016/j.energy.2018.09.004
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    6. 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).
    7. Xiangyu Kong & Jingtao Yao & Zhijun E & Xin Wang, 2019. "Generation Expansion Planning Based on Dynamic Bayesian Network Considering the Uncertainty of Renewable Energy Resources," Energies, MDPI, vol. 12(13), pages 1-20, June.
    8. Carlos Roberto de Sousa Costa & Paula Ferreira, 2023. "A Review on the Internalization of Externalities in Electricity Generation Expansion Planning," Energies, MDPI, vol. 16(4), pages 1-19, February.
    9. Khan, Hafiz Anwar Ullah & Ünel, Burçin & Dvorkin, Yury, 2023. "Electricity Tariff Design via Lens of Energy Justice," Omega, Elsevier, vol. 117(C).
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    11. 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).
    12. Mark D. Rodgers & David W. Coit & Frank A. Felder & Annmarie G. Carlton, 2019. "A Metamodeling Framework for Quantifying Health Damages of Power Grid Expansion Plans," IJERPH, MDPI, vol. 16(10), pages 1-21, May.
    13. Fitiwi, Desta Z. & Lynch, Muireann & Bertsch, Valentin, 2020. "Power system impacts of community acceptance policies for renewable energy deployment under storage cost uncertainty," Renewable Energy, Elsevier, vol. 156(C), pages 893-912.

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