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Assessing reliability of electricity grid services from space: the case of Uttar Pradesh, India

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  • Dugoua, Eugenie
  • Kennedy, Ryan
  • Shiran, Myriam
  • Urpelainen, Johannes

Abstract

While most households around the world have access to electricity, the number of hours per day when the grid supplies them with adequate voltage can be low. Improving the reliability of electricity is crucial to make progress on energy poverty but measuring and monitoring it is difficult, especially in lower-income countries where official data is sparse. We develop a transparent method using only easily accessible data to track the reliability of electricity. We train a decision tree model to predict the number of hours with normal electricity in Uttar Pradesh, India, using monthly nighttime luminosity, village characteristics, and voltage data from monitors installed in households. The approach successfully predicts reliability across time and space, and we document that, in Uttar Pradesh, the average number of hours per day with normal electricity has increased by 0.6 h between 2014 and 2019. The predicted number of hours with normal/reliable electricity supply for 2019 remains as low as 8.1 h.

Suggested Citation

  • Dugoua, Eugenie & Kennedy, Ryan & Shiran, Myriam & Urpelainen, Johannes, 2022. "Assessing reliability of electricity grid services from space: the case of Uttar Pradesh, India," LSE Research Online Documents on Economics 115140, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:115140
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    File URL: http://eprints.lse.ac.uk/115140/
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    References listed on IDEAS

    as
    1. Kennedy, Ryan & Mahajan, Aseem & Urpelainen, Johannes, 2020. "Crowdsourcing data on the reliability of electricity service: Evidence from a telephone survey in Uttar Pradesh, India," Energy Policy, Elsevier, vol. 145(C).
    2. Michael Grimm & Luciane Lenz & Jörg Peters & Maximiliane Sievert, 2020. "Demand for Off-Grid Solar Electricity: Experimental Evidence from Rwanda," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 7(3), pages 417-454.
    3. Hunt Allcott & Allan Collard-Wexler & Stephen D. O'Connell, 2016. "How Do Electricity Shortages Affect Industry? Evidence from India," American Economic Review, American Economic Association, vol. 106(3), pages 587-624, March.
    4. Min, Brian & Golden, Miriam, 2014. "Electoral cycles in electricity losses in India," Energy Policy, Elsevier, vol. 65(C), pages 619-625.
    5. Mikul Bhatia & Nicolina Angelou, 2014. "Capturing the Multi-Dimensionality of Energy Access," World Bank Publications - Reports 18677, The World Bank Group.
    6. Baskaran, Thushyanthan & Min, Brian & Uppal, Yogesh, 2015. "Election cycles and electricity provision: Evidence from a quasi-experiment with Indian special elections," Journal of Public Economics, Elsevier, vol. 126(C), pages 64-73.
    7. Michaël Aklin & Chao-yo Cheng & Johannes Urpelainen & Karthik Ganesan & Abhishek Jain, 2016. "Factors affecting household satisfaction with electricity supply in rural India," Nature Energy, Nature, vol. 1(11), pages 1-6, November.
    8. Gibson, John & Olivia, Susan, 2010. "The Effect of Infrastructure Access and Quality on Non-Farm Enterprises in Rural Indonesia," World Development, Elsevier, vol. 38(5), pages 717-726, May.
    9. Kennedy, Ryan & Mahajan, Aseem & Urpelainen, Johannes, 2019. "Quality of service predicts willingness to pay for household electricity connections in rural India," Energy Policy, Elsevier, vol. 129(C), pages 319-326.
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    More about this item

    Keywords

    electricity; reliability; India; nightlights; remote sensing; Nightlights; Electricity; Reliability; Remote sensing;
    All these keywords.

    JEL classification:

    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General

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