Decarbonizing the Indian power sector by 2037 : evaluating different pathways that meet long-term emissions targets
Author(s)Rudnick García, Iván.
Massachusetts Institute of Technology. Institute for Data, Systems, and Society.
Technology and Policy Program.
Audun Botterud, Pablo Duenas-Martinez and Carlos Batlle.
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The Indian government is aiming to reduce carbon emissions intensity in the power sector through incentivizing the addition of renewables sources into the grid. India has set the goal that at least 40% of total power capacity must be non-fossil fuel-based by 2030 with more ambitious goals expected to be set for 2040 and 2050. To meet the decarbonization goals by the next decades, the central government is promoting a large-scale development of wind turbines and solar photovoltaic power plants. Achieving long-term decarbonization in the Indian power sector presents several challenges to the current electric grid. For example, the current generation mix relies heavily on coal power plants such that integrating solar and wind plants (i.e., variable renewable energy (VRE) sources) adds several layers of economic and technical complexity. Other challenges include improving the national quality of service and reducing local emissions.The overall effect is amplified by India's rapidly increasing electricity consumption, which has necessitated the build-out of additional capacity to meet the future load. The following thesis analyzes potential pathways to the decarbonization of India's grid by 2037. The study explores 24 different scenarios, each considering different technology costs (solar, wind, and storage), setting different gas prices, and defining different emissions limits. The analysis uses the capacity expansion model "GenX" developed internally at MIT. GenX is a deterministic capacity expansion planning model. The model optimizes generation, storage, and transmission capacity expansion decisions and dispatch of generation and storage resources on an hourly basis to meet the electricity demand in a year, at the lowest cost possible.The study successfully identifies the trade-offs between system costs, global emissions, and local emissions levels for different scenarios, enabling the assessment of the long-term impact of large infrastructure decisions in the electric power sector. Of the findings: (1) Scenarios without emission limits, continue to be dominated by coal and emissions rose relative to 2017 levels. (2) Scenarios with emissions limits had an increased share of VRE sources, greater than 50% in some scenarios. (3) Some scenarios with high VRE penetration required significant dispatchable capacity that could ramp up suddenly to meet net load, reaching 270 GW in peak load days. (4) Gas-based plants competed directly with storage technologies; both technologies are flexible and can adapt to abrupt changes in VRE generation. However, as storage costs rise, gas plants begin to dominate the generation mix.There are some challenges in developing new gas plants, as plants cycling increase and the gas fleet is underutilized in some scenarios. The thesis also addresses the policy implications for each scenario. To reduce greenhouse gasses emissions, setting emissions limits can be hard to enforce. Imposing a carbon tax is ideal, although it is hard to set the right price. Setting a non-fossil fuel portfolio standard can not necessarily help reduce emissions to a specific target. Many regulatory changes are required to encourage higher levels of VRE penetration such as promoting better coordination between state and regional system operators, reducing uncertainty in the use of the gas infrastructure, and promoting the development of storage technologies.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2019Cataloged from student-submitted PDF of thesis.Includes bibliographical references (pages 104-109).
DepartmentMassachusetts Institute of Technology. Institute for Data, Systems, and Society; Massachusetts Institute of Technology. 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.