2026-09-19T21:57:49Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1112262022-02-01T18:46:37Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Valerie Karplus and Niven Winchester.
Singh, Arun
Technology and Policy Program.
Massachusetts Institute of Technology. Engineering Systems Division
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Technology and Policy Program
a-ii---
2017-09-15T14:20:11Z
2017-09-15T14:20:11Z
2017
2017
http://hdl.handle.net/1721.1/111226
1003283983
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2017.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 78-83).
Sustaining rapid economic growth and satisfying increasing energy demand while limiting greenhouse gas (GHG) emissions is a central challenge in India. Proposed policy solutions should be evaluated according to their impacts on the energy system and the economy to identify efficient policies. I have developed an energy-economic model for India that provides a comprehensive foundation for analyzing energy technologies and policies. This novel model based on a general equilibrium approach simulates the Indian economy, with detailed inter-sectoral linkages, and facilitates an understanding of economy-wide impacts of policies. The model allows for analysis of tradeoffs among different technology and policy choices in terms of their costs and efficiency in GHG emissions reduction. While comprehensive carbon pricing is arguably the most economically efficient measure for emissions reduction, political considerations often favor technology-specific choices. Support for renewable energy factors prominently in India's climate change mitigation strategy. To study the impact of policies that promote renewable energy, the model represents renewable electricity in detail. Impact of incentives and scale factors are also incorporated in projecting renewables expansion. I simulate India's Nationally Determined Contributions (NDCs) to the Paris Agreement and compare their effectiveness, benchmarking them against the theoretical least-cost alternative of broad-based carbon pricing. Specifically, India's NDCs include targets on non-fossil electricity capacity expansion and CO2 emissions intensity of GDP (GoI 2015a). This work provides valuable quantitative insights on the impact of these policy measures, and fills a critical knowledge gap in the design and implementation of effective climate policies in India. My findings suggest that compared to a reference case of no policy constraint, the average cost of reducing a tonne of CO2 is lowest in a scenario with an emissions intensity target implemented via CO2 pricing, and more than 43 times higher in the pure non-fossil electricity target scenario. Further, emissions intensity targets result in a 6.3% drop in total electricity demand, as the cost of fossil fuel based electricity increases. As CO2 emitting electricity sources become more expensive, non-fossil sources - particularly solar and wind - increase in the mix. Enforcing non-fossil electricity capacity targets leads to an additional 15.6% drop in total electricity demand as average electricity prices increase to account for a higher share of costlier non-fossil electricity. Non-fossil electricity capacity targets also result in leakage of emissions to non-electricity energy sectors. The magnitude of differences among these results depends on wind and solar electricity costs. Cheaper costs of wind and solar power lead to lower welfare losses and electricity demand levels that are comparable across scenarios.
by Arun Singh.
S.M. in Technology and Policy
83 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Institute for Data, Systems, and Society.
Engineering Systems Division.
Technology and Policy Program.
Clean development pathways for India : evaluating feasibility and modeling impact of policy options
Thesis
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<Abstract>Sustaining rapid economic growth and satisfying increasing energy demand while limiting greenhouse gas (GHG) emissions is a central challenge in India. Proposed policy solutions should be evaluated according to their impacts on the energy system and the economy to identify efficient policies. I have developed an energy-economic model for India that provides a comprehensive foundation for analyzing energy technologies and policies. This novel model based on a general equilibrium approach simulates the Indian economy, with detailed inter-sectoral linkages, and facilitates an understanding of economy-wide impacts of policies. The model allows for analysis of tradeoffs among different technology and policy choices in terms of their costs and efficiency in GHG emissions reduction. While comprehensive carbon pricing is arguably the most economically efficient measure for emissions reduction, political considerations often favor technology-specific choices. Support for renewable energy factors prominently in India's climate change mitigation strategy. To study the impact of policies that promote renewable energy, the model represents renewable electricity in detail. Impact of incentives and scale factors are also incorporated in projecting renewables expansion. I simulate India's Nationally Determined Contributions (NDCs) to the Paris Agreement and compare their effectiveness, benchmarking them against the theoretical least-cost alternative of broad-based carbon pricing. Specifically, India's NDCs include targets on non-fossil electricity capacity expansion and CO2 emissions intensity of GDP (GoI 2015a). This work provides valuable quantitative insights on the impact of these policy measures, and fills a critical knowledge gap in the design and implementation of effective climate policies in India. My findings suggest that compared to a reference case of no policy constraint, the average cost of reducing a tonne of CO2 is lowest in a scenario with an emissions intensity target implemented via CO2 pricing, and more than 43 times higher in the pure non-fossil electricity target scenario. Further, emissions intensity targets result in a 6.3% drop in total electricity demand, as the cost of fossil fuel based electricity increases. As CO2 emitting electricity sources become more expensive, non-fossil sources - particularly solar and wind - increase in the mix. Enforcing non-fossil electricity capacity targets leads to an additional 15.6% drop in total electricity demand as average electricity prices increase to account for a higher share of costlier non-fossil electricity. Non-fossil electricity capacity targets also result in leakage of emissions to non-electricity energy sectors. The magnitude of differences among these results depends on wind and solar electricity costs. Cheaper costs of wind and solar power lead to lower welfare losses and electricity demand levels that are comparable across scenarios.</Abstract>
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