Assessing reliability of electricity grid services from space: the case of Uttar Pradesh, India
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...
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Published in | IDEAS Working Paper Series from RePEc |
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Main Authors | , , , |
Format | Paper |
Language | English |
Published |
St. Louis
Federal Reserve Bank of St. Louis
01.01.2022
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Subjects | |
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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. |
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AbstractList | 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. |
Author | Dugoua, Eugenie Kennedy, Ryan Shiran, Myriam Urpelainen, Johannes |
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Title | Assessing reliability of electricity grid services from space: the case of Uttar Pradesh, India |
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