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Economic dynamics and technology diffusion in Indian power sector

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  • B. Sudhakara Reddy

    (Indira Gandhi Institute of Development Research)

Abstract

There is a growing concern among policy makers about how electricity is generated and consumed in the context of energy security and global climate change. In such a scenario, renewable energy sources, especially solar and wind energy, are likely to play a significant role in providing reliable and sustainable electricity to consumers as they are locally available and their carbon foot print is small. The future share of power by renewables will greatly depend on the expected generation cost and the government's support to investments in the sector. Using levelised cost approach, capital cost, operating and fuel costs of major electricity generation technologies are compared. Then, a forecast is made for electricity generation in India, using non-linear Bass diffusion model over 15-year horizon, until 2030 for all major energy technologies, viz., coal, natural gas, hydro, solar, wind, and biomass. The results show how present trends and future forecasts of electricity-generating technologies change the electricity generation mix, and how solar and wind power may increase their share in the total generation. However, fossil fuels will continue to remain competitive relative to renewables due to their cost advantage. The main issue considered here is whether each energy technology has reached its maximum penetration level. This helps set out a path for renewable energy technology diffusion in the Indian power sector.

Suggested Citation

  • B. Sudhakara Reddy, 2016. "Economic dynamics and technology diffusion in Indian power sector," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2016-014, Indira Gandhi Institute of Development Research, Mumbai, India.
  • Handle: RePEc:ind:igiwpp:2016-014
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    References listed on IDEAS

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    Cited by:

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    4. Zhang, Tianyu & Dong, Peiwu & Zeng, Yongchao & Ju, Yanbing, 2022. "Analyzing the diffusion of competitive smart wearable devices: An agent-based multi-dimensional relative agreement model," Journal of Business Research, Elsevier, vol. 139(C), pages 90-105.
    5. Cheng, Shulei & Wu, Yinyin & Chen, Hua & Chen, Jiandong & Song, Malin & Hou, Wenxuan, 2019. "Determinants of changes in electricity generation intensity among different power sectors," Energy Policy, Elsevier, vol. 130(C), pages 389-408.
    6. Prakash, Vrishab & Ghosh, Sajal & Kanjilal, Kakali, 2020. "Costs of avoided carbon emission from thermal and renewable sources of power in India and policy implications," Energy, Elsevier, vol. 200(C).
    7. Zhanwu Wang & Guangyin Xu & Zhenfeng Wang & Zhiping Zhang, 2022. "Sustainability of agricultural waste power generation industry in China: criteria relationship identification and policy design mechanism," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 3371-3395, March.
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    More about this item

    Keywords

    Cost; Diffusion; Power; Renewables; Technology;
    All these keywords.

    JEL classification:

    • P28 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Natural Resources; Environment
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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