Techno-Economic Assessment of Deep Electrification of Passenger Vehicles in India
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LBNL-1007121 ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Techno-Economic Assessment of Deep Electrification of Passenger Vehicles in India Nikit Abhyankar Anand Gopal Colin Sheppard Won Young Park Amol Phadke Energy Analysis and Environmental Impacts Division May 2017 This work was funded by the U.S. Department of Energy's Office of International Affairs under Lawrence Berkeley National Laboratory Contract No. DE-AC02-05CH11231. Disclaimer This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or The Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof, or The Regents of the University of California. Ernest Orlando Lawrence Berkeley National Laboratory is an equal opportunity employer. i Acknowledgements Lawrence Berkeley National Laboratory would like to thank the U.S. Department of Energy for providing financial support for this work. We are thankful to Rashid Waraich of Lawrence Berkeley National Laboratory, Anup Bandivadekar of The International Council on Clean Transportation, and Aman Chitkara of the Rocky Mountain Institute for their helpful reviews. Preliminary results of this analysis were presented at various fora and meetings. We thank Jarett Zuboy for careful editing of the report and Elizabeth Coleman and Heather Thomson for providing the administrative support. Any errors or omissions are the authors’ responsibility. This work was funded by the U.S. Department of Energy's Office of International Affairs under Lawrence Berkeley National Laboratory Contract No. DE-AC02-05CH11231. ii Contents Executive Summary ......................................................................................................................... 1 1. Introduction ............................................................................................................................. 7 2. Methods, Data, and Assumptions............................................................................................ 8 2.1. Plug-in Electric Vehicle Infrastructure (PEVI) Model ...................................................... 10 2.1.1. Total Vehicle Stock in 2030 ...................................................................................... 11 2.1.2. BEV Stock in 2030 ..................................................................................................... 13 2.1.3. Vehicle Efficiency ...................................................................................................... 13 2.1.4. Vehicle Kilometers Traveled ..................................................................................... 15 2.1.5. Vehicle Costs ............................................................................................................. 16 2.2. Power System Modeling Using PLEXOS .......................................................................... 17 2.2.1. Electricity Generation Capacity ................................................................................ 17 2.2.2. Wind and PV Generation Profiles ............................................................................. 18 2.2.3. Non-BEV Electricity Demand .................................................................................... 18 2.2.4. Generator Costs and Operational Parameters ......................................................... 19 2.2.5. Fuel Prices and Availability ....................................................................................... 20 2.2.6. Power Plant Emission Factors .................................................................................. 20 2.2.7. Transmission ............................................................................................................. 20 2.2.8. Smart Charging ......................................................................................................... 21 2.3. Estimating Per-Kilometer CO2 Emissions ........................................................................ 21 2.4. Estimating Crude Oil Consumption ................................................................................. 21 3. Results .................................................................................................................................... 22 3.1. BEV Owners Can Gain Significantly ................................................................................. 22 3.2. Additional Load due to BEV Charging Is Minor ............................................................... 24 3.3. BEV Charging Load Can Earn Additional Revenue for Utilities ....................................... 27 3.4. BEVs Can Reduce CO2 Emissions Significantly................................................................. 28 3.5. BEVs Can Avoid Crude Oil Imports .................................................................................. 31 3.6. Smart Charging Can Enable Cost-Effective RE Integration ............................................. 32 iii 4 Conclusion and Policy Implications ........................................................................................ 34 Appendix 1: Assumptions for Power System Modeling ............................................................... 37 Hourly PV and Wind Generation Forecast by Region ...................................................... 37 5.1.1 Wind Generation Profiles .......................................................................................... 37 5.1.2 Solar PV Generation Profiles ..................................................................................... 38 Operational Parameters of Generators ........................................................................... 39 Hydro Capacity and Energy Model .................................................................................. 39 Costs ................................................................................................................................. 40 Fuel Availability and Prices .............................................................................................. 42 Transmission .................................................................................................................... 44 Appendix 2: Assumptions for Operational Characteristics of Generating Plants ......................... 45 References .................................................................................................................................... 48 iv Executive Summary Introduction In India, there is growing interest among policymakers, planners, and regulators in aggressive electrification of passenger vehicles. For example, Piyush Goyal, the Minister of State for India’s Ministries of Coal, Power, and New and Renewable Energy, has announced an aspirational goal of full electrification of passenger vehicle sales by 2030. In 2012, India announced the National Mission on Electric Mobility, setting a countrywide goal of deploying 6–7 million hybrid and electric vehicles by 2020. Given that lithium ion battery costs have dropped 80% in the last six years and continue to fall, large-scale electrification of light duty vehicles is an attainable goal for India. This report assesses the system-level techno-economic impacts, if all light duty passenger vehicle (i.e. cars and two-wheelers) sales in India by 2030 were battery electric vehicles (BEVs). Methods and Assumptions We conduct the analysis using three simulation-optimization models: (a) the Plug-in Electric Vehicles Infrastructure (PEVI) model, an agent-based travel and charging demand model that simulates BEV driving and charging behavior, (b) PLEXOS, an industry-standard simulation model for least-cost investment planning and economic dispatch of the power system, and (c) the Economic and Environmental Impacts model, a spreadsheet-based tool that assesses the impact on emissions, oil imports, and utility finances. Using projections of travel demand in 2030, total BEV penetration and efficiency, and agent- based modeling of charging behavior, PEVI estimates the BEV charging load for each hour of the year. Using official government data and historical trends, we project hourly electricity demand in the country from sources other than BEVs. We then simulate the 2030 power system in India using certain assumptions on operational constraints and by creating the following two scenarios for the electricity generation capacity mix: (a) the Business as Usual (BAU) scenario, which includes the new electricity generation investments as identified in India’s 12th 5-year plan (up to 2022) and National Electricity Plan (up to 2027), extrapolated to 2030, and (b) the NDC Compliant scenario, which includes the aggressive renewable energy (RE) targets committed to by