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Modeling of Electric Demand for Sustainable Energy and Management in India Using Spatio-Temporal DMSP-OLS Night-Time Data

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Abstract

Changes in the pattern of electric power consumption in India have influenced energy utilization processes and socio-economic development to greater extent during the last few decades. Assessment of spatial distribution of electricity consumption is, thus, essential for projecting availability of energy resource and planning its infrastructure. This paper makes an attempt to model the future electricity demand for sustainable energy and its management in India. The nighttime light database provides a good approximation of availability of energy. We utilized defense meteorological satellite program-operational line-scan system (DMSP-OLS) nighttime satellite data, electricity consumption (1993–2013), gross domestic product (GDP) and population growth to construct the model. We also attempted to examine the sensitiveness of electricity consumption to GDP and population growth. The results revealed that the calibrated DMSP and model has provided realistic information on the electric demand with respect to GDP and population, with a better accuracy of r 2 = 0.91. The electric demand was found to be more sensitive to GDP (r = 0.96) than population growth (r = 0.76) as envisaged through correlation analysis. Hence, the model proved to be useful tool in predicting electric demand for its sustainable use and management.

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Acknowledgements

The authors gratefully acknowledge the anonymous reviewers and editorial office for their constructive comments and suggestions which helped to improve the overall quality of the present work. Thanks are also due to Dr. P.G. Diwakar, Deputy Director (Remote Sensing Applications) NRSC for his guidance and suggestions.

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Correspondence to Pavan Kumar.

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Tripathy, B.R., Sajjad, H., Elvidge, C.D. et al. Modeling of Electric Demand for Sustainable Energy and Management in India Using Spatio-Temporal DMSP-OLS Night-Time Data. Environmental Management 61, 615–623 (2018). https://doi.org/10.1007/s00267-017-0978-1

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