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CONNECTKaro 2015 - Session 7A - GPC - Modeling Energy Demand from India’s Transport Sector


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Scenario building using a bottom-up national transport demand model

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CONNECTKaro 2015 - Session 7A - GPC - Modeling Energy Demand from India’s Transport Sector

  1. 1. Modeling energy demand from India’s transport sector Scenario building using a bottom-up national transport demand model 16th April 2015 ConnectKaro, New Delhi1
  2. 2. Need for developing demand side energy and emissions estimates  Top-down estimates from supply side useful for  Creating energy and emissions inventories  Ex-post assessment of policy/tech. interventions  Activity based bottom-up estimates help determine  Underlying factors resulting in a certain level of energy/emissions  Ex-ante estimates of different interventions  Present exercise showcases the outcomes of a bottom-up transport demand and related energy and emissions estimation modeling exercise 2
  3. 3. Objective of the exercise Determining the present and future demands of energy by the transport sector in India and identifying ways to reduce its energy needs under various scenarios 3
  4. 4. Energy demand for transport is an outcome of transport demand, mode and technology choice 1. How much do people and goods travel 2. What modes do they use to travel 3. What fuel/technology is used to drive these modes 4. How much energy do these modes consume per unit of travel 5. What is the aggregate demand for energy for transport 4
  5. 5. Bottom-up transport demand estimation  Passenger  Vehicle types  Utilizations  Occupancies  Technologies  Efficiencies 5 Activity Mode Share Intensity Fuel Mix ASIF Framework  Freight  Vehicle types  Utilizations  Loadings  Technologies  Efficiencies
  6. 6. An example of the bottom up transport demand and energy estimation  Estimating passenger transport demand met by cars  Total volume of registered cars (-) life of vehicles = total volume of on-road cars (x) Daily utilization of cars (km) (x) Fleet utilization – avg. percentage of cars being used daily (%) (x) Occupancy (Average no. of passengers) = PASSENGER KILOMETERS generated on cars  Segregating this number by vehicle fuel efficiencies give the resulting fuel used, and thereby the energy 6
  7. 7. Total Transport Passenger Road Cars/ Jeeps Petrol Diesel CNG LPG xEVs Taxis Diesel CNG LPG Three Wheelers Petrol Diesel LPG CNG Two Wheelers Petrol Electric Buses Diesel CNG xEVs Rail Diesel Electric Air Freight Road HCV LCV Rail Diesel Electric Air Multiplicity of modes and technologies complicates the modeling exercise 7 Transport of passengers and goods using inland waterways, coastal shipping and pipelines is being taken up for the next version of the tool
  8. 8. Model outcome Estimates of transport demand and energy 8
  9. 9. How much do people and goods travel in India?  Motorized mobility in India 2011-12  ~5,967 km/person (7,255 BPKM)  1,604 BTKM  Compares lowly to international transport demands  UK 2011 - 14,247 km/person  US 2011 – 28,500 km/person  EU 2009 – 11,700 km/person  Transport demand is expected to continue to grow rapidly  Increased economic activity  Higher levels of urbanization  Improved access to transport systems  By 2046-47:  Passenger: 18,978 km/person (32,342 BPKM)  Freight: 16,653 BTKM 9
  10. 10. 0 100 200 300 400 500 600 2012 2017 2022 2027 2032 2037 2042 2047 Growth in energy consumption by the transport sector Freight Passenger Components of energy consumption in the transport sector 7 times growth in energy use is expected between 2012 and 2047 (6% CAGR) 40% 60% Freight Passenger 45% 55% Freight Passenger Energy shares in 2012 Energy shares in 2047 73 mtoe 523 mtoe 93% 5% 2% ROAD RAIL AIR 94% 2% 4% ROAD RAIL AIR 73 523 MTOE 2011-12 2046-47
  11. 11. What modes do people travel on?  As of 2011-12  Most passenger travel happened on roads  Railways occupied only 14 per cent of the total passenger traffic  Aviation saw a very rapid growth in the last decade – still low share of traffic  Road based public transport (bus/omni-buses) occupy about 75 per cent of the total road traffic 11 ROAD 85% RAIL 14% AIR 1% BUS 73% ONMI- BUS 2% CAR 7% 2W 13% 3W 3%TAXI 2% Passenger transport shares in 2011-12
  12. 12. What fuel technology is used to drive these passenger modes?  As of 2011-12  Road transport consumes almost only petroleum products  Alternate fuel penetration is still very low and restricted to few urban centers  Half the railway traffic moves on diesel and the other half on electric traction 12 100% 77% 40% 18% 43% 96% 99% 99% 50% 2% 10% 3% 1% 1%2% 7% 2% 0% 50% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2W CAR 3W TAXI ONMI-BUS BUS RAIL Share of passenger traffic on different fuel types within each mode PETROL DIESEL CNG LPG ELECTRIC
  13. 13. The present and future passenger transport energy consumption 37% 3%18% 18% 7% 9% 4% 4% BUS ONMI-BUS CAR 2W 3W TAXI RAIL AIR 15% 1% 38% 9% 13% 15% 1% 8% Energy shares in 2012 Energy shares in 2047 0 100 200 300 400 2012 2017 2022 2027 2032 2037 2042 2047 BAU levels of passenger transport energy consumption (mtoe) • 73% of the present passenger traffic moves on buses and omni-buses consuming 40% of the energy • Cars and Jeeps handle only about 6% of the traffic but consume over 18% of the energy By 2047 • Energy consumption by personalized modes of transport continue to increase • Aviation is expected to drive 2.5% of the mobility - consuming over 8% of the energy of passenger transport • Share of rail based transport to marginally decline (14% to 12%)
  14. 14. Creating Energy Security Scenarios Various types of scenarios created for the Indian Energy Security Scenarios 2047 tool
  15. 15. Methods of reducing energy demand for passenger transport considered Considered four possible ways of reducing the energy demand for passenger transport 1. Reducing the total demand for passenger mobility  Better planning and strategic urban development to cut down travel 2. Shifting mobility to more energy efficient modes  Mode shift from air and road to rail based transport 3. Increasing the share of road based public transport  More urban bus services and introduction of transport demand measures to reduce private vehicle use 4. Introduction of energy efficient road vehicles  Increasing the energy efficiency of private road vehicles by introduction of electric, hybrid and fuel cell vehicles 15
  16. 16. Transport trajectories considered for the IESS 2047  Six different line levers considered for the transport sector  4 passenger transport lines  2 freight transport lines  4 different levels under each lever 16
  17. 17. Reducing levels of passenger transport demand  Four levels of passenger transport demand considered  Level 1: Business as usual levels of demand  Increased economic growth, increased access to transport  Continuous increase in the annual distance travelled per person  Level 2: Moderate effort (~10% demand reduction)  Increase in the number of activity centers across the country  Increasing urbanization leading to reduced migration trips  A reduction of per capita mobility demands in smart cities  Level 3: Dedicated effort (~20% demand reduction)  Aggressive use of ITES applications reducing the demand for travel  Corporate and industrial personnel travel planning  Level 4: Herculean effort (~30% demand reduction)  Herculean effort scenario, with incentive schemes to reduce commute trips  Work – residence – recreation trips better organized to reduce travel demand 17
  18. 18. Improving the share of the railways in passenger mobility  Trajectories visualized progressively increasing the share of railways  Level 1: Business as usual mode shares  Continuous increase in the share of personalized road vehicles  Increasing energy intensity for passenger transport  Level 2: Moderate effort  Increased focus on rail based transport (metro, train-sets, rapid rail)  Focus on increasing the share of railways  Level 3: Dedicated effort  Railway projects given top priority in planning – few HSR corridors and RRTS across various urban centers  Share of railways improves further  Level 4: Herculean effort  Metros and RRTS become commonplace across large urban centers  HSR to complement air travel on longer distances across the country 18
  19. 19. Other levers to reduce the sector’s energy use  Movement to public transport and efficient vehicles  Better urban designs and plans allowing increased use of public transport  Increased of efficient vehicles on electric and hybrid traction  Freight transport demand reduction  Improved use of logistic planning in freight mobility to reduce redundant freight movements  Growth of industrial clusters thereby allowing combined movement of similar traffic  Improved freight transport mode choice  Incentivize the movement of freight from road to rail  Improved last mile connectivity for railway services  Railways moves from being a mobility provider to a complete transporter 19
  20. 20. Large reductions in energy possible using all the levers  About 43% reduction possible from the 2047 energy consumption levels  Combined options: Demand reduction, mode choice, public vehicles, efficient electric vehicles 20 43% reduction
  21. 21. Limitations, lessons learnt and the way forward Outlining the issues for building activity based transport sector energy and emissions estimation models 21
  22. 22. Limitations of the activity based energy estimation methodology Methodology useful for a closed system such as the domestic transport sector Difficult to implement under porous systems such as states or cities/urban centers  Difficult to determine appropriate boundary conditions for non-stationary sector like transport Requires a large number of data items to increase the robustness of the model 22
  23. 23. Lessons learnt from developing a transport demand and energy estimation model  Useful methodology for estimating impacts of mode and technology choice changes at a macro-national level  Tool is easily customizable to evaluate the impacts of various kinds of policies/programs  Acute limitation in the availability of data related to transport use in India  Identified a very long list of data items that could be useful for increasing the robustness of the model 23
  24. 24. Way forward  Increase the use of such scientific methods in making infrastructure investment choices  Possible to incorporate costs and pricing  Fine tune methodology to also develop state, regional and city level energy emissions transport models  Start incentivizing different transport related agencies for collecting various data items  Need to put in place systems to regularly collect transport activity related data at all levels (urban, rural, intercity) 24
  25. 25. THANK YOU For more information on Transport Modeling exercise: India Energy Security Scenarios 2047: 25