Energy Futures for India. Rangan Banerjee Forbes Marshall Chair Professor Dept of Energy Science and Engineering IIT Bombay

Transcription

1 Energy Futures for India Rangan Banerjee Forbes Marshall Chair Professor Dept of Energy Science and Engineering IIT Bombay Guest lecture at Energy Technologies Research Institute (ETRI ), The University of Nottingham, May 20, 2015

2 India and UK (Selected Indicators for 2012) Population 1237 million 63.7 million GDP (PPP) 5567 Billion 2005 US$ 2021 Billion 2005 US$ (4258 $/person) ( $/person) Primary Energy 32.9 EJ 8.0 EJ Energy/person 26.6 GJ/person/year GJ/person/year Electricity/person 760 kwh/capita/year 5740 kwh/capita/year CO2 emissions Per person 1954 Million tonnes 484 Million tonnes 1.58 tonnes /capita/year 7.18 tonnes /capita/year 2 Per GDP kg /US$ ppp 0.22 kg /US$ ppp

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5 Share of Energy Imports - India Import Share (INDIA)

6 Energy Future - Questions # 1 Does the Structure of GDP Matter? Industry, Services, Agriculture Sectoral growths and Impacts #2 What will be the future supply mix for the Electricity sector? How much can renewables supply? #3 Can Energy Efficiency be a game-changer? Will Energy Efficient, Green Buildings make a difference? #4 Can we solve the problems of Energy Access and Equity? How does this relate to Low Carbon futures? 6

7 # 1 India Trends CAGR (%) Population (million) GDP ( PPP Billion 2005 US $ ) Energy use (EJ) Electricity use (Billion units) Oil imports (million tonnes) Share of energy imports 8% ~30% - Installed power generation capacity 46, , % of households un electrified Not known 40 - Renewable power installed capacity (excl large hydro) 0 17,297 MW - Share of Nuclear Generation 2.7% 3.5% - 7

8 # 1 Sectoral Shares of GDP in 1985 and % Industry 42.7% Services 55.19% Services 17.7% Agriculture 27.1% Industry 31.2% Agriculture Industry 23% 25% 26% 25% 27% 27% Services 36% 39% 44% 51% 57% 59% 8 Agriculture 42% 36% 30% 23% 16% 13.9%

9 # 1 Time Series Trends In Intensity 25 CAGR=3% CAGR=5% CAGR=5.5% CAGR=7% Energy Intensity of GDP (toe/10000$) Emissions Intensity of GDP (tco2/10000$) Emissions Intensity of Energy (tco2/toe) 5 0 9

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11 Decomposition Analysis # Change per year (%) Change per year (%) Change per year (%) Change per year (%) Total Emissions Intensity -0.10% 3.88% 0.62% -1.97% Change in Structure 0.83% 0.75% 0.70% 0.07% Change in energy intensity of GDP -1.54% -0.13% -2.70% -2.99% Change in Emissions Intensity of Energy 0.74% 3.10% 3.35% 1.57%

12 # 1 Sectoral Mix 12

13 Services # UK (37,61,1) India-1971 (23,36,42) China-1971 (27,19,53) T. Kanitkar et al 2015 Industry

14 # 1 Emission Reduction Effort T. Kanitkar et al 2015

15 #2 What will be the future supply mix for the Electricity sector? How much can renewables supply? 15

16 #2 Primary Energy Mix 100% 80% 16 Coal 60% Oil and Gas 40% 20% Renewables and Nuclear 16

17 #2 Power Generation Supply mix 100% 80% Thermal 60% Nuclear 40% 20% % Renewables (incl Hydro) 0

18 Installed Capacity - India 2015 (as on ) Diesel, 1200 Renewables, Waste to Power, 115 Solar Power, 3744 Bagasse, 3008 Hydro (Res.), Biomass, 1410 Small Hydro power, 4055 Wind power, Natural Gas, Coal, Nuclear, ,67,637 MW total installed capacity MW total installed capacity 18 Source: Ministry of Power and MNRE, Govt. of India

19 Elect. int/gdp #2 Electricity Intensity of GDP Trend Year 19

20 Renewable installed capacity and generation Installed Capacity* (MW) Estimated Capacity factor Estimated Generation (GWh) Wind % Biomass Power % 8371 Bagasse Cogeneration % Small Hydro % Waste to Energy % 504 Solar PV % 5630 Total % * as on MNRE website: 20

21 Share of total % Renewable Share in Power Renewable Installed Capacity 10 8 Renewable Generation Nuclear generation Year Nuclear Installed Capacity

22 Frozen Efficiency Scenarios for % (Low) Population (in billions) % (Moderate) 8% (High) GDP (in US 2005 Billion PPP) GDP/ capita Primary Energy (in EJ) Primary Energy per capita (in GJ)

23 Business as Usual Scenarios for % (Low) 6.4% (Moderate) 8% (High) Population (in billions) GDP (in US 2005 Billion PPP) GDP/ capita Primary Energy (in EJ) Primary Energy per capita (in GJ) Electricity Supply (in billion units) Electricity Supply (in units/ capita)

24 Supply Scenarios for 2035 (BAU- Moderate) - Electricity- High Coal (A) Supply Scenario (BAU) Projections for 2035 Coal Natural Gas Diesel Nuclear Hydro Renewab les Total % Electricity Supply Share 66% 12% 2% 3% 11% 6% 100% Electricity Supply/ year (in billion kwh) Average Load Factor 70% 70% 16% 70% 38% 26% Installed Capacity (in GW)

25 Supply Scenarios for 2035 (BAU- Moderate)- Electricity- High Renewables (B) Supply Scenario Green (Coal Low, Renewables High) Natural Gas Diesel Nuclear Hydro Renewab les Projections for 2035 Coal Total % Electricity Supply Share 50% 12% 2% 3% 11% 22% 100% Electricity Supply/ year (in billion kwh) Average Load Factor 70% 70% 16% 70% 38% 26% Installed Capacity (in GW)

26 Supply Scenarios for 2035 (BAU- Moderate)- Electricity- High Nuclear (C) Supply Scenario Green (Coal Low, Nuclear High, Renewables Moderately High ) Natural Gas Diesel Nuclear Hydro Renewabl es Projections for 2035 Coal Total % Electricity Supply Share 40% 12% 2% 13% 11% 22% 100% Electricity Supply/ year (in billion kwh) Average Load Factor 70% 70% 16% 70% 38% 26% Installed Capacity (in GW)

27 Power Generation Supply mix 80% A B C Thermal 60% Nuclear 40% 20% % Renewables (incl Hydro)

28 Renewable installed capacity and generation 2022 Installed Capacity* (MW) Estimated Capacity factor Estimated Generation (GWh) Wind % Biomass Power % Bagasse 60% Cogeneration Small Hydro % Waste to Energy % 2190 Solar PV % Total %

29 Installed Capacity (MW) Diffusion curve Upper limit of uncertainity Lower limit of uncertainity Potential = MW Year Diffusion Curves for wind energy 29

30 Installed Capacity(MW) PV Installed Capacity Growth

31 Installed Capacity(MW) PV Installed Capacity Projections

32 Plan Layout 32 32

33 A portion of the ELU map of Ward A of MCGM Corresponding Satellite Imagery for the area from Google Earth 33 Analyzed in QGIS To determine -Building Footprint Ratios - Usable PV Areas For Sample Buildings Source: R. Singh and Banerjee, 2015

34 0:01-1:00 1:01-2:00 2:01-3:00 3:01-4:00 4:01-5:00 5:01-6:00 6:01-7:00 7:01-8:00 8:01-9:00 9:01-10:00 10:01-11:00 11:01-12:00 12:01-13:00 13:01-14:00 14:01-15:00 15:01-16:00 16:01-17:00 17:01-18:00 18:01-19:00 19:01-20:00 20:01-21:00 21:01-22:00 22:01-23:00 23:01-24:00 MUs Jan, 2014 Typical Load Profile vs PV Generation Capacity Factor for Mumbai Axis Tracking Axis Highest eff. 1-Axix Median eff Fixed 19 deg. Annual Average with 1-Axis Tracking 1 19 deg. Fixed Highest eff deg. Fixed Median eff Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 34

35 Power generated in MW hours 9000 january June July August September Wind Generation Tamil Nadu Total Generation Jan-07 june july august sept

36 Wind energy generated (MU) Power generated in MW January June Hourly variation of wind power Hours September 1200 Monthly variation of wind energy generated Mean value 36 0 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Months

37 National Solar Thermal Power Facility Consortium supported by MNRE and led by IIT Bombay Thermal Storage Generato r Turbine Solar Field Thermic Oil Loop Heat Exchanger Condenser CLFR Direct Steam Cooling Water Circuit Pump Expansion Vessel Pump Water/ Steam Loop Schematic of 1 MW Solar Power Plant Simulator snapshot Consortium Members KIE Solatherm Parabolic Trough Solar Field Linear Fresnel Reflector Solar Field at Gwalpahari site 37

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40 #3 Can Energy Efficiency be a game-changer? Will Energy Efficient, Green Buildings make a difference? 40

41 41 Building stock growth

42 Methodology For Stock Type Urban + Rural Energy efficiency in Appliances + Envelope + Air-conditioning Scenarios for Rural/ Urban for 2035 Penetration Rates for AC & Appliances Efficiency of AC, Appliances & Envelope BAU Moderate Low High Hours of operation for AC Green Moderate Moderate Moderate Sustainable Moderate High Low 42 Factors affecting energy use Penetration rate Efficiency Hours of operation

43 Residential demand scenarios by energy use type 43

44 Residential demand scenarios by stock type 44

45 Building simulation based optimization through design of experiments Single storey air-conditioned solar powered building in Mumbai climate 45 Sankey diagram for the BAU case

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47 Comparison of designs Cooling load 47 Design Cooling load Life cycle cost Base case High Moderate Optimized designs Moderate Low Energy efficient case Low High

48 48 TEAM SHUNYA SOLAR DECATHLON EUROPE 2014

49 House in Versailles 26th June, 2014 Team Shunya 70 students 13 disciplines 12 faculty

50 #4 Can we solve the problems of Energy Access and Equity? How does this relate to Low Carbon futures? 50

51 Historical Household Electrification Rates 51 GEA, Chapter 19

52 Average Household Energy Use - India 52 GEA, Chapter 19

53 Cooking Energy Use (2010) 53 Source: 2010 NSSO

54 Energy Use Household (2005) Rural Urban 54 Khandker et al, 2012

55 No. of house holds: 29 Connected load : 1.4 kw 5 kwp Solar PV power plant at Rajmachi Village, Maharashtra 55 Source: Manoj and Banerjee, 2010

56 Power(Watts) and Voltage (Volts) Measurements VOLTAGE POWER :00 2:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36 0:00 Time (hrs) 56

57 Selco Case study For profit company Solar Home systems started 1996 sold about 100,000 SHS 90% of products credit schemes Partnership with 9 banks interest rates between 12-17% Financing Institutions pay 85% of the amount- monthly payments of Rs over a period of 5 years Financing/ repayment options tailormade to end users paddy farmers repayment schedule based on crop cycle, street vendors daily payments Rs 10 Funding from REEP meet margin amount for poor customers, reduce interest rate Source: SELCO,

58 DESI Power Biomass based power solutions Bihar- 25 kw to 100 kw Local distributors decide pricing Registered under CDM and sold CERs to Swiss buyer MNRE funds, Promoters Equity, ICICI Loan Monthly rate based on no of bulbs / loads, Circuit breaker to limit consumption Irrigation pump users Rs 50/ hour, Household Rs per month Underground trunk wiring-distribution Enabling micro-enterprises battery charging station, flour mill, workshop etc Tie up with Telecom towers increasing capacity factor 58

59 Husk Power Initial funding prize money kw biomass gasifiers- based on rice husk Energy audit of households Focus on household demand for lighting Lower production, operating costs use of bamboo, asbestos Overhead pole wiring Directly reach end user 59

60 Energy and Equity 60 Source: GEA, 2012

61 Residential Electricity Gini (Select countries) 61 Source: Jacobsen, Energy Policy, 2005

62 Electricity Lorenz Curves India Rural Urban Year GINI GINI Source: K.Mehta 2014 Urban 62

63 Social Accounting Matrix Input- Output Matrix Higher contribution of renewable energy the investment needed impacts government expenditure on other goods BAU 776 Billion Rs to 2575 Billion Rs Reduction in GDP Negative impact on equity GINI increases Assumption investments reduced in other sectors equally 63

64 HDI and Electricity use 64 Source: Pasternak, 2000

65 Summary Structure of economy important, Development pathways Industrial growth Increased renewables share, fossil declining to 50% of supply 180 GW target by ambitious need for storage, cost reduction, technology development, decentralised Efficiency New stock buildings- can make a difference Low carbon does not necessarily ensure access, equity, need for targetted investments for access Tradeoffs Capital investments 65

66 References ckinetics analytics, Rural Electrification Corp, NSSO IEA, Key World Energy Statistics 2012 United Nations, World Population Prospects (2009) Ministry of Power, Government of India, GEA, 2012 Chapter 10 & 19 : Global Energy Assessment - Toward a Sustainable Future, Cambridge University Press, Cambridge, UK and New York, NY, USA and the International Institute for Applied Systems Analysis, Laxenburg, Austria. T. Kanitkar et al 2015: Tejal Kanitkar, Banerjee, R. Banerjee and T. Jayaraman, Impact of economic structure on mitigation targets for developing countries, Volume 26, June 2015, 56 61, June Ministry of New and Renewable Energy (MNRE), Government of India, New Delhi, website: Ministry of Power, Government of India, R. Singh and Banerjee, 2015: Singh, R., and Banerjee, R., Estimation of rooftop solar photovoltaic potential of a city, Solar Energy, Vol. 115, , May NSSO Khandker et al, 2012 S Khazanchi, ETV 2035 (draft report), TIFAC MNRE, MOP A.Sarkar, ETV 2035, (draft report), ETV 2035, TIFAC. K.Mehta, 2014: Ketav Mehta, Dual Degree Thesis, 2014, IIT Bombay Anjali Summer Internship Report 66

67 References Anderson, 2012 Mukunda et al, Jacobsen, Energy Policy, 2005 Steinberger, Roberts, 2009 Julia K. Steinberger, J. Timmons Roberts(2009) Across a Moving Threshold: energy, carbon and the efficiency of meeting global human development needs, Vienna Foresight Sustainable Energy Management and the Built Environment Project (2008). Final Project Report.The Government Office for Science, London. Pillai and Banerjee, 2009: Renewable energy in India: Status and potential, Energy, (34)8, , August Manoj and Banerjee, 2010: Analysis of isolated power systems for village electrification, Energy for Sustainable Development, (14)3, , September TIFAC Energy Technology Vision 2035 draft in progress Jay Dhariwal & Rangan Banerjee "Building simulation based optimization through design of experiments." Paper presented at BSA2015 Building Simulation Applications 2nd IBPSA-Italy Conference, Bozen-Bolzano Rajan Rawal & Yash Shukla "RESIDENTIAL BUILDINGS IN INDIA: ENERGY USE PROJECTIONS AND SAVINGS POTENTIALS." Global Buildings Performance Network. 67

68 End- Note Alice :I was wondering if you could help me find my way. Cheshire Cat: Well, that depends where you want to go. Alice: It really doesn't matter, as long as... Cheshire Cat: Then it really doesn't matter which way you go. If you don't know where your going, then any road will get you there. Source: Lewis Carroll: Alice In Wonderland 68

69 Acknowledgment TIFAC ETV 2035 Advisory Group Members: + Additional Contributors Tejal Kanitkar Jay Dhariwal Balkrishna Surve Rhythm Singh 35 rangan@iitb.ac.in rangan,.banerjee@gmail.com Thank you