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Parametric sensitivity analysis for techno-economic parameters in Indian power sector

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  • Mallah, Subhash
  • Bansal, N.K.

Abstract

Sensitivity analysis is a technique that evaluates the model response to changes in input assumptions. Due to uncertain prices of primary fuels in the world market, Government regulations for sustainability and various other technical parameters there is a need to analyze the techno-economic parameters which play an important role in policy formulations. This paper examines the variations in technical as well as economic parameters that can mostly affect the energy policy of India. MARKAL energy simulation model has been used to analyze the uncertainty in all techno-economic parameters. Various ranges of input parameters are adopted from previous studies. The results show that at lower discount rate coal is the least preferred technology and correspondingly carbon emission reduction. With increased gas and nuclear fuel prices they disappear from the allocations of energy mix.

Suggested Citation

  • Mallah, Subhash & Bansal, N.K., 2011. "Parametric sensitivity analysis for techno-economic parameters in Indian power sector," Applied Energy, Elsevier, vol. 88(3), pages 622-629, March.
    • Handle: RePEc:eee:appene:v:88:y:2011:i:3:p:622-629
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    References listed on IDEAS

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    1. Kannan, R., 2009. "Uncertainties in key low carbon power generation technologies - Implication for UK decarbonisation targets," Applied Energy, Elsevier, vol. 86(10), pages 1873-1886, October.
    2. Chen, W.T. & Li, Y.P. & Huang, G.H. & Chen, X. & Li, Y.F., 2010. "A two-stage inexact-stochastic programming model for planning carbon dioxide emission trading under uncertainty," Applied Energy, Elsevier, vol. 87(3), pages 1033-1047, March.
    3. Mallah, Subhash & Bansal, N.K., 2010. "Allocation of energy resources for power generation in India: Business as usual and energy efficiency," Energy Policy, Elsevier, vol. 38(2), pages 1059-1066, February.
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    Cited by:

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    2. Liu, Xi & Du, Huibin & Brown, Marilyn A. & Zuo, Jian & Zhang, Ning & Rong, Qian & Mao, Guozhu, 2018. "Low-carbon technology diffusion in the decarbonization of the power sector: Policy implications," Energy Policy, Elsevier, vol. 116(C), pages 344-356.
    3. García-Gusano, Diego & Espegren, Kari & Lind, Arne & Kirkengen, Martin, 2016. "The role of the discount rates in energy systems optimisation models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 56-72.
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    8. Yildiz, Yusuf & Korkmaz, Koray & Göksal Özbalta, Türkan & Durmus Arsan, Zeynep, 2012. "An approach for developing sensitive design parameter guidelines to reduce the energy requirements of low-rise apartment buildings," Applied Energy, Elsevier, vol. 93(C), pages 337-347.

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