4.7 Article

Resource potential and variability assessment of solar and wind energy in India

期刊

ENERGY
卷 211, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2020.118993

关键词

Geographical information system; Multi-criteria-assessment; On-shore wind; Solar photovoltaic; Spatial variability; Temporal variability

资金

  1. DST [DST/RCUK/JVCCE/2015/02]

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With the growing concerns over climate change and energy security, the Government of India aims to enhance the share of solar and wind based Renewable Energy (RE) in energy mix. However, current official estimates of RE potential undervalue the actual scale of potential and they also fall way short of meeting the future low-carbon demand. These estimates are generally available at coarse spatial reso-lution of regions/states and do not provide information of RE temporal variability. Considering low resolution values in system planning may result in over/underestimation of other required resources like grid infrastructure and flexibility options. This calls for re-assessing India's RE potential by a thorough examination of land suitability, and quantification of its spatial and temporal variability to support grid integration and system planning activities. In this context, this article performs a Geographical Information System (GIS) based multi-criteria-assessment of ground-mounted solar Photovoltaic (PV) and on-shore wind energy potential in India. Geo-spatial and multi-year hourly meteorological data sets are utilized to estimate geographical and techno-economic RE potential. Calculated supply curve outlines the availability of estimated whole solar energy within the Levelized Cost of Energy (LCOE) range of 51.6 $/MWh to 89 $/MWh. 3102 GW of wind capacity is available below 115 $/MWh LCOE. Variability assessment shows that the western region of the country has highest RE potential with low spatial variability. A complementary relationship between solar and wind energy in various states shows the feasibility of hybrid solar-wind plants to ensure reliable green energy supply. By performing these assessments for 1 degrees by 1 degrees geographical grid cells, this study generates a granular data set paving the path for policymakers to setup feasible policies. (C) 2020 Elsevier Ltd. All rights reserved.

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