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Making renewable energy competitive in India: Reducing financing costs via a government-sponsored hedging facility

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  • Farooquee, Arsalan Ali
  • Shrimali, Gireesh

Abstract

In India, a significant barrier to market-competitiveness of renewable energy is a shortage of attractive debt. Domestic debt has high cost, short tenors, and variable interest rates, adding 30% to the cost of renewable energy compared to renewable energy projects elsewhere. Foreign debt is as expensive as domestic debt because it requires costly market-based currency hedging solutions. We investigate a government-sponsored foreign exchange facility as an alternative to reducing hedging costs. Using the geometric Brownian motion (GBM)22Acronyms: contract for differences (CfD), foreign exchange (FX), FX hedging facility (FXHF), geometric Brownian motion (GBM), levelized cost of electricity (LCOE), power purchase agreement (PPA). as a representative stochastic model of the INR–USD foreign exchange rate, we find that the expected cost of providing a currency hedge via this facility is 3.5 percentage points, 50% lower than market. This leads to an up to 9% reduction in the per unit cost of renewable energy. However, this requires the government to manage the risks related to unexpected currency movements appropriately. One option to manage these risks is via a capital buffer; for the facility to obtain India's sovereign rating, the capital buffer would need to be almost 30% of the underlying loan. Our findings have significant policy implications given that the Indian government can use this facility to make renewable energy more competitive and, therefore, hasten its deployment.

Suggested Citation

  • Farooquee, Arsalan Ali & Shrimali, Gireesh, 2016. "Making renewable energy competitive in India: Reducing financing costs via a government-sponsored hedging facility," Energy Policy, Elsevier, vol. 95(C), pages 518-528.
    • Handle: RePEc:eee:enepol:v:95:y:2016:i:c:p:518-528
    DOI: 10.1016/j.enpol.2016.02.005
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    Cited by:

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    2. Shrimali, Gireesh & Konda, Charith & Farooquee, Arsalan Ali, 2016. "Designing renewable energy auctions for India: Managing risks to maximize deployment and cost-effectiveness," Renewable Energy, Elsevier, vol. 97(C), pages 656-670.
    3. Indora, Sunil & Kandpal, Tara C., 2019. "A framework for analyzing impact of potential financial/fiscal incentives for promoting institutional solar cooking in India," Renewable Energy, Elsevier, vol. 143(C), pages 1531-1543.
    4. Suresha Kharvi & T. P. M. Pakkala, 2021. "An optimal inventory policy when purchase price follows geometric Brownian motion process," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 835-851, December.
    5. Zhang, Yao & Zhang, Yuxin & Gong, Chao & Dinçer, Hasan & Yüksel, Serhat, 2022. "An integrated hesitant 2-tuple Pythagorean fuzzy analysis of QFD-based innovation cost and duration for renewable energy projects," Energy, Elsevier, vol. 248(C).
    6. Gireesh Shrimali, 2021. "Financial Instruments to Address Renewable Energy Project Risks in India," Energies, MDPI, vol. 14(19), pages 1-19, October.
    7. Vallecha, Harshit & Bhattacharjee, Debraj & Osiri, John Kalu & Bhola, Prabha, 2021. "Evaluation of barriers and enablers through integrative multicriteria decision mapping: Developing sustainable community energy in Indian context," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    8. Jeslin Drusila Nesamalar, J. & Venkatesh, P. & Charles Raja, S., 2017. "The drive of renewable energy in Tamilnadu: Status, barriers and future prospect," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 115-124.

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