3 rd Meeting of Task Force 2 on Advancement of Transmission Systems Interconnection

Transcription

1 3 rd Meeting of Task Force 2 on Advancement of Transmission Systems Interconnection Presentation on the progress and preliminary findings of the study on Assessment of the Electricity Trading Potential in the South Asia region 25 th February

2 Presentation Outline Project objective and scope of work as per Terms of Reference Project approach and methodology Methodology for estimation of unrestricted electricity demand, electricity supply and peak demand forecast for South Asian Nations Findings/analysis on Demand-Supply projections of the South Asian Nations Introduction to ICF s Integrated Planning Model (IPM ) Model assumptions and model run results for India Data support needed from Task Force members Way Forward Appendices 2

3 Project Objective To identify the electricity trading potential of the South Asian nations (India, Bangladesh, Bhutan, Nepal, Sri Lanka, Pakistan, Maldives and Afghanistan) over a period of next 20 years by reviewing the existing long term Demand-Supply projections of the participating countries. 3

4 Project Scope of Work 1. The study to account all types of generating plants viz Hydro, Thermal, Nuclear and Renewable. 2. Collect, compile, review and analyze the existing/prevailing long term Demand-Supply (D-S) projections/data available in respect of each South Asian country. This shall include different generation capacity addition scenarios. 3. Assess whether existing D-S projections have adequately been taken up and have explored the Cross Border Electricity Trade (CBET) potentials of each South Asian country from the trading perspectives and in the time horizon of years. 4. If the data including the perspective generation capacity addition projections are not available from various sources for the time horizon of years, a proper methodology* to be adopted to arrive at reasonable D-S projections to explore the CBET potential of each South Asian country. 5. The above D-S projections shall include the year wise trading opportunities that arise out of seasonal variations, time zone difference, difference in load curve, different weekends and holidays being followed in each South Asian nation. *Methodology to be adopted for arriving at these projections shall be finalized in consultation with the respective Task Force 2 country members and shall include a sensitivity analysis of the same. Based on the approved methodology, country wise projections shall be made in respect of the various seasonal scenarios (including peak/off-peak conditions) and in terms of both MW and MWhr for the specified time horizon of next years. 4

5 Project Deliverables 1. (a) Submit a Draft report on the Findings/Analysis on the existing Demand-Supply projections (MW, MWh) of each South Asian Nation. (b) Wherever data projections are not available upto the specified time horizon, a separate draft report shall be submitted, identifying the shortcomings and the projections (including assumptions) made in respect of the Demand-Supply (MW, MWh) for a period of next years covering plantwise breakup of generation and the fuel being used etc. 2. Make presentation(s) on the above Draft reports to the Task Force 2 members as and when required 3. Submit an interim report, incorporating all suggestions/recommendations to the respective provisions by the Task Force 2 members and IRADe. 4. Make presentation(s) before the Task Force 2 members, Project Steering Committee (PSC), IRADe and USAID on the interim report, as and when required. 5. Submit the Final report based on the feedback received from all stakeholders. 5

6 Project Approach & Methodology The overall project approach has been divided into following three parts: 1. Power Sector Historical Analysis and Current Overview: a) Review of historical Demand-Supply trends. Collation of data on historical i. Peak load and energy demand ii. Capacity addition and generation Deliverable 1 (a) + iii. Energy and peak deficits partly 1 (b) b) Analysis of Existing and Future Transmission Capacity 2. Power Market Outlook (2014 to Years): Base case development using ICF s IPM (Integrated Planning Model). Towards populating the modeling framework, ICF will build develop assumptions on demand, supply, future generation and transmission builds, fuel supply and renewable forecasts besides other areas. 3. Scenario Analysis: Analysis around the base case to assess the impact of variables for same timeframe as base case IPM is a long-term capacity expansion and production costing model for electric power systems including generation and transmission. It is a multi-regional, deterministic, dynamic, linear programming model. 6

7 Methodology for estimation of unrestricted electricity demand, electricity supply and peak demand forecast Unrestricted electricity demand (GWh) forecast for all countries (except Sri Lanka # ) has been estimated using the following methodology: The actual electricity demand for 2013 has been used as the as base Energy Demand For the period , the electricity demand has been computed as the product of GDP and electricity elasticity * for each year GDP forecast for each country has been developed by using The World Bank s GDP growth forecast Electricity Elasticity for each country has been calculated by studying the relationship between the electricity demand and the GDP over last 10 years. Same elasticity value has been considered for all the future years for calculating the electricity demand Electricity supply (GWh) forecast (upto 2034), if unavailable in the respective national power plan document, has been developed by either estimating generation from upcoming power plants ** or assuming the generation of the last year upto which forecast is available to be constant for future years. Peak demand (MW) forecast, if unavailable in the respective national power plan document, has been estimated by using 5 year compound annual growth rate (CAGR). # In case of Sri Lanka, demand forecast is available in Ceylon Electricity Board s Generation Expansion Plan 2013 * Electricity Elasticity refers to the percentage change in energy demand to achieve one per cent change in national GDP ** if data on the same is available 7

8 Findings/Analysis on the existing Demand- Supply projections of the South Asian Nations Deliverable 1 (a) + partly 1(b) as per Project Terms of Reference 8

9 Afghanistan Findings & Analysis on Electricity Demand, Electricity Supply and Peak Demand 9

10 Afghanistan GDP & Electricity Demand Growth MU Data Source: GDP (absolute value & growth rate) Electricity Demand Till 2013 From 2014 Till 2013 From 2014 The World Bank The World Bank forecast; growth rate kept constant beyond 2016 U.S. Energy Information Administration - EIA ICF Analysis 10

11 Afghanistan Electricity Demand vs Supply & Peak Demand MU Data Source: Electricity Demand Electricity Supply Peak Demand Till 2013 From 2014 Till 2034 NA U.S. Energy Information Administration - EIA ICF Analysis 2013 supply assumed to be constant till 2034 NA 11

12 Afghanistan Load Profile 2013 Data for Afghanistan Load Profile (8760 hours) is Not Available 12

13 Bangladesh Findings & Analysis on Electricity Demand, Electricity Supply and Peak Demand 13

14 Bangladesh GDP & Electricity Demand Growth Data Source: GDP (absolute value & growth rate) Electricity Demand Till 2013 From 2014 Till 2013 From 2014 The World Bank The World Bank forecast; growth rate kept constant 2016 onwards BPDP - Bangladesh Power Development Board BPDP ICF Analysis 14

15 Bangladesh Electricity Demand vs Supply & Peak Demand Data Source: Electricity Demand Electricity Supply Peak Demand Till 2013 From 2014 Till 3030 From 2031 Till 2030 From 2031 BPDP ICF Analysis BPDP BPDP - Bangladesh Power Development Board Assumed Constant at 2030 supply BPDP Estimated using 5-yr CAGR Key Points: Since the commissioning of a HVDC line b/w Bheramara in Bangladesh to Baharampur in India in 2013, Bangladesh is importing about 500 MW of power MW of this is imported from unallocated resource of Indian Government through NTPC and the other 250 MW power from is sourced from the Indian market through PTC for short term 3 year contract. In the future, it is proposed to upgrade this 500 MW link to 1000 MW. 15

16 Bangladesh Load Profile Bangladesh Power Demand MW Jan-13 1-Feb-13 1-Mar-13 1-Apr-13 1-May-13 1-Jun-13 1-Jul-13 1-Aug-13 1-Sep-13 1-Oct-13 1-Nov-13 1-Dec-13 Data Source: Power Cell, Bangladesh 16

17 Bhutan Findings & Analysis on Electricity Demand, Electricity Supply and Peak Demand 17

18 Bhutan GDP & Electricity Demand Growth MU Data Source: GDP (absolute value & growth rate) Electricity Demand Till 2013 From 2014 Till 2013 From 2014 The World Bank The World Bank forecast; growth rate kept constant 2016 onwards Bhutan Annual Statistical Yearbook ICF Analysis 18

19 Bhutan Electricity Demand vs Supply & Peak Demand MU Data Source: Electricity Demand Electricity Supply Peak Demand Till 2013 From 2014 Till 2013 From 2014 Till 2030 From 2031 Bhutan Annual Statistical Yearbook ICF Analysis Bhutan Annual Statistical Yearbook NTGMP by CEA, India NTGMP by CEA, India NTGMP National Transmission Grid Master Plan for Bhutan CEA Central Electricity Authority Estimated using 5-yr CAGR Key Points: Electricity trade b/w India and Bhutan was initiated in 1961 when Bhutan started sourcing power from the Jaldhaka HPP set up in West Bengal, India. This was followed by construction of mini/micro hydel project in Bhutan with Grant Assistance from Government of India (GoI). Currently Bhutan is exporting about 1300 MW power from Chhukha, Kurichhu, Tala, Basochhu I&II Power Plants in the peak Monsoon season. The 126 MW Dagachhu Power Plant (built under PPP mode) in Bhutan is now commissioned and will soon participate in the open Power Markets operational in India. 19

20 Bhutan Load Profile 2013 Data for Bhutan Load Profile (8760 hours) is Not Available However, Power Data Book 2013 published by Bhutan Power Corporation Limited (BPCL) provides Load Curve for a typical day in 2013 summer and winter for Thimpu and Phuntsholing, as shown in the following slides: 20

21 Bhutan Thimpu Daily Load Curve 2013 Data Source: Bhutan Power Book 2013 published by Royal Government of Bhutan 21

22 Bhutan Phuntsholing Daily Load Curve 2013 Data Source: Bhutan Power Book 2013 published by Royal Government of Bhutan 22

23 India - Findings & Analysis on Electricity Demand, Electricity Supply and Peak Demand 23

24 India Electricity Demand vs Supply & Peak Demand Electricity Demand vs Supply and Peak Demand Electricity Demand_a (BU) Electricity Demand_f (BU) Electricity Supply_a (BU) Electricity Supply_f (BU) Peak Demand_a (MW) Peak Demand_f (MW) Suffix _a & _f Values Actual & Forecasted Electricity Demand Electricity Supply Peak Demand Till 2013 Central Electricity Authority, India From 2014 ICF Analysis Till 2013 Central Electricity Authority, India From 2014 ICF Analysis Till 2013 Central Electricity Authority, India From 2014 ICF Analysis Details on electricity shortages in India and its impact on Demand 24

25 India Load Profile , , , ,000 90,000 80,000 70,000 60, profile Data Source: Central Electricity Authority, India 25

26 India Load Duration Curve , , ,000 80,000 60,000 40,000 20, Load Duration Curve Data Source: Central Electricity Authority, India 26

27 Maldives Findings & Analysis on Electricity Demand, Electricity Supply and Peak Demand 27

28 Maldives GDP & Electricity Demand Growth % 4.50% 4.00% 3.50% 3.00% 2.50% 2.00% 1.50% 1.00% 0.50% 0.00% Data Source: Electricity Demand_a (MU) Electricity Demand_f (MU) GDP_a (Constant 2010 USD Million) GDP_f (Constant 2010 USD Million) % Electricity Demand Growth Rate_a % Electricity Demand Growth Rate_f % GDP Growth Rate_a % GDP Growth Rate_f Suffix _a & _f Actual & Forecasted Values GDP (absolute value & growth rate) Electricity Demand Till 2013 From 2014 Till 2013 From 2014 The World Bank The World Bank forecast; growth rate kept constant beyond 2016 U.S. Energy Information Administration - EIA ICF Analysis 28

29 Maldives Electricity Demand vs Supply & Peak Demand MU Data Source: Electricity Demand Electricity Supply Peak Demand Till 2013 From 2014 Till 2034 NA Key Points: 27 Islands, 27 power systems with overall installed capacity of ~62 MW U.S. Energy LTGEP Long Term Generation Expansion Plan Information ICF Analysis Administration - EIA 2013 supply assumed to be constant till 2034 NA No substantial generation capacity addition expected in future years 29

30 Maldives Load Profile 2013 Data for Maldives Load Profile (8760 hours) is Not Available 30

31 Nepal Findings & Analysis on Electricity Demand, Electricity Supply and Peak Demand 31

32 Nepal GDP & Electricity Demand Growth MU Data Source: GDP (absolute value & growth rate) Electricity Demand Till 2013 From 2014 Till The World Bank The World Bank forecast; growth rate kept constant 2016 onwards Nepal Electricity Authority Annual Report 2014 ICF Analysis Key Points: Nepal has very high electricity shortages Unrestricted Demand data for past 3 years has been used to forecast future demand 32

33 Nepal Electricity Demand vs Supply & Peak Demand MU Data Source: Electricity Demand Electricity Supply Peak Demand Till Till Till NEA Annual Report 2014 ICF Analysis NEA Annual Report 2014 Based on expected capacity additions (10,000 MW Hydro by 2030) Nepal Electricity Authority Annual Report 2014 Estimated using 5-yr CAGR Key Points: Power exchange between India and Nepal takes place in three modes: Free Power under River Treaty (~40 MW), Border Town Exchange Program (~50 MW) and Commercial Power Trading with PTC India during Dry season. Nepal is currently importing ~150 MW from India through medium term arrangements. In , Nepal s 18% electricity supply was met from imports from India. The quantum imported by Nepal has increased from 425 MUs in FY 2008 to 793 MUs in FY

34 MW Nepal Full System Load Data for Nepal Load Profile (8760 hours) is Not Available However, 24 hour load profile for a typical week in FY is available as shown below 1200 System Load ( ) ( ) peak days System Load Data Source: Nepal Electricity Authority 34

35 Pakistan Findings & Analysis on Electricity Demand, Electricity Supply and Peak Demand 35

36 Pakistan GDP & Electricity Demand Growth Data Source: GDP (absolute value & growth rate) Electricity Demand Till 2013 From 2014 Till 2034 The World Bank The World Bank forecast; growth rate kept constant 2016 onwards ICF Analysis using Electricity Demand Data from National Power System Expansion Plan prepared by the National Transmission and Despatch Company, Pakistan Key Points: Electricity demand in Pakistan follows an asymmetric pattern. The demand has strongly been influenced by GDP during high growth period

37 Pakistan Electricity Demand vs Supply & Peak Demand Data Source: Electricity Demand Electricity Supply Peak Demand Till 2013 From 2014 Till 2034 Till 2034 Key Points: Pakistan has been facing ~25% electricity shortages for many year and these are expected to persist in future too. Power System Statistics, LTGEP Long Term Generation Expansion Plan National Transmission ICF Analysis and Despatch Company National Power System Expansion Plan, National Transmission and Despatch Company National Power System Expansion Plan, National Transmission and Despatch Company 37

38 Pakistan Load Profile 2013 Data for Pakistan Load Profile (8760 hours) is Not Available 38

39 Sri Lanka Findings & Analysis on Electricity Demand, Electricity Supply and Peak Demand 39

40 Sri Lanka Electricity Demand vs Supply & Peak Demand Electricity Demand_a (BU) Electricity Demand_f (BU) Electricity Supply_a (BU) Suffix _a & _f Electricity Supply_f (BU) Peak Demand_a (MW) Peak Demand_f (MW) Values Actual & Forecasted Data Source: Electricity Demand Electricity Supply Peak Demand Till 2034 Till 2034 Till 2034 LTGEP, Ceylon Electricity Board LTGEP, Ceylon Electricity Board LTGEP, Ceylon Electricity Board LTGEP Long Term Generation Expansion Plan 40

41 Sri Lanka Full System Load Data for Sri Lanka Load Profile (8760 hours) is Not Available However, 24 hour load profile for a system maximum night peak in 2013 is available as shown below Data Source: Sri Lanka Sustainable Energy Authority 41

42 Conclusion: Demand-Supply Scenario for South Asian Nations 42

43 Demand-Supply Scenario for South Asian Nations Electricity Demand vs Supply Electricity Demand_a (BU) Electricity Demand_f (BU) Electricity Supply_a (BU) Electricity Supply_f (BU)Suffix _a & _f Actual & Forecasted Values Data Source: Sum of the Demand and Supply of all countries presented in previous slides 43

44 ICF s Integrated Planning Model (IPM ) 44

45 ICF provides Modeling tools across a range of sectors Fuels Power, EE Environment Gas Market Model Energy Asset Decision Support System Gas Market Clearing Engine Coal Asset Depletion Optimization Model Aviation Integrated Planning Model Building Energy Analysis Console (Beacon ) Energy Efficiency Potential Models International Carbon Pricing Tool (InCaP ) Carbon Planning Model (CPM ) Greenhouse Gas Emissions Management System Kyoto Project Risk Management System GHG Portfolio Rating and Evaluation System for Prioritizing Investments in Reducing Emissions 45

46 IPM is an excellent and versatile long range planning model IPM is a long-term capacity expansion and production costing model for electric power systems including generation, transmission, and process/district heat production from co-generation and stand-alone boilers It is a multi-regional, deterministic, dynamic, linear programming model Utilizes Dynamic Optimization Framework with an Objective Function of Minimizing the Present Value of Total System Cost subject to: Electricity & Steam Demand Constraints Reserve Margin Constraints Environmental Constraints Transmission Constraints Fuel Constraints Other Operational Constraints Simulates rational expectations for perfect foresight providing the framework for inter-temporal decision making 46 46

47 Integrated Planning Model (IPM ) More details on IPM in Appendix 47 47

48 IPM uses easy to comprehend yet extremely Powerful Linear Programming methodology Objective Function of IPM is to minimize present value of the total system costs and unserved load Major Types of Constraints in IPM - Energy Constraints and Capacity Constraints, Dispatch Constraints, Fuel Constraints, Environmental and other constraints Cost Coefficients in Objective Function Mathematical equations and definitions of all constraints mentioned above are provided in Appendix 48

49 Key outputs from IPM Power Markets - Trading Volumes - Power prices - Production costs - Generation dispatch - Generation capacity addition including reserve requirements - Transmission capacity addition - Transmission line congestion/utilization - Renewable energy capacity and generation Fuel Markets - Fuel consumption/demand - Fuel prices and opportunity cost - Fuel supply sources - Fuel transport economics Emissions Markets - Emissions price - REC / other program credit price - Abatement cost curve - Program performance (i.e., compliance, banking, borrowing, etc) - DSM penetration - Program cost More details on Key Outputs from in Appendix 49 49

50 India - Key assumptions for IPM modeling 50

51 Indian economy expected to show strong recovery Year ICF assumption % % % % % % % 2021 onwards 8.00% Average ( ) 7.53% Indian economy expected to recover in next few years on the back of strong reform agenda of the current Government. A high growth of ~8% is being targeted by Indian government with the objective of reducing the poverty levels significantly by 2050 In the long-term, the Planning Commission of India targets Indian economy to reach and stabilize at a GDP growth rate of ~8%. The World Bank has also estimated the long term GDP growth of India to remain ~8%. India was able to sustain high GDP growth rates in past on the back of strong reform measures taken by the Government during that period. Same measures are expected from the current Government. 51

52 Electricity Demand growth of 6.65% is expected during period 2014 to 2031 average demand growth rate of 6.65% against average GDP growth of 7.53% assuming a constant energy elasticity of 0.89 By 2031, per capita consumption reaches 2,200 kwh/person which is similar to that of Eastern European countries 52

53 India to add ~90 GW of name plate capacity during 2015 to 2019 RPO based * Based on RPO obligation Overall 92 GW capacity added from 2015 to 2019, of which 26.6 GW is because of RPO around 18 GW of capacity being added every year Major new capacity added is coal based; almost 9 GW of annual coal based capacity addition Wind and solar is added through mandatory Renewable Purchase Obligations Procurement market continues bifurcated between PSUs and IPPs 53

54 Firm hydro capacity additions (2015 to 2019) 800 MW (RoR: 5 (800 MW)) 2,500 MW (RoR: 10 (1,800 MW); Storage: 3 (700 MW)) 2,400 MW (RoR: 11 (2000 MW); Storage: 2 (400 MW)) State Capacity NR 5.7 SR 0.6 WR 0.6 NER 2.6 ER 3.1 Total

55 Indian coal power plants continue to witness a deficit of domestic coal Years Units CIL Supply MT SCCL Supply MT Captive supply MT Grand Total MT Coal Supplied to Power sector MT Coal Capacity supported* GW Coal capacity in System GW Coal capacity supported reflects coal capacity that can run at 80% PLF with coal supplied to power sector assuming a heat rate of 9800 Btu/kWh for coal plant Domestic Coal available for power sector is not sufficient to support current capacity and expected expansions in future Indian coal power plants have to increasingly rely on imported coal to meet their demand 55

56 Domestic gas supply reduces significantly forcing many plants to run at low PLFs Years Units Total gas production MMSCMD Gas allocated to power sector MMSCMD Gas Capacity supported* GW Gas capacity in System GW Gas capacity supported reflects gas capacity that can run at 40% PLF with gas allocated to power sector assuming a heat rate of 8000 Btu/kWh for gas plant. Domestic gas supply has significantly declined in last few years due to fall in production of KG D-6. New discoveries add only incremental gas to the current domestic gas supply Though excess imported LNG is available to power sector, but gas plants are not able to dispatch due to high cost of electricity produced from LNG 56

57 Imported coal cost Years Landed cost ($/Ton) Plant Dispatch cost (INR/kWh) Years Landed cost ($/Ton) Plant Dispatch cost (INR/kWh) Years CIF Prices ($/Ton) West Coast East Coast Years CIF Prices ($/Ton) Plant Dispatch Cost represents Total Variable cost of plant only 57

58 Domestic gas prices ($/MMBtu) Gujarat Delivered cost (USD/MMBtu) Plant Dispatch cost (INR/kWh) Delhi Delivered cost (USD/MMBtu) Plant Dispatch cost (INR/kWh) Maharashtra Delivered cost (USD/MMBtu) Plant Dispatch cost (INR/kWh) Andhra Pradesh Delivered cost (USD/MMBtu) Plant Dispatch cost (INR/kWh) Plant Dispatch Cost represents Total Variable cost of plant only Tamil Nadu Delivered cost (USD/MMBtu) Plant Dispatch cost (INR/kWh)

59 India IPM Modeling Results 59

60 All-India demand supply balance India does not need new capacity till end of 2019, as generation from stranded capacity and RPO based capacity will be sufficient to meet energy demand In 2022 and beyond, mainly the new capacity additions based on coal contribute to meet the growing energy demand 60

61 Share of Imported coal based generation reaches ~36% in 2031 In long-term, generation from imported coal is expected to play an important role in meeting increasing demand of system Of the total coal generation in the system, generation from imported coal contributes ~36% by 2031 Generation from RE sources (Wind, Solar, Small-Hydro and biomass) are primarily driven by RPO 61

62 India to add ~15 GW of coal capacity each year between 2022 and 2031 to meet growing energy demand (1) Coal capacity forms the major chunk along with Hydro RE (Wind and solar) based capacity addition increases rapidly owing mainly to the RPO 62

63 India to add ~15 GW of coal capacity each year between 2022 and 2031 to meet growing energy demand (2) in GW Coal Nuclear Gas Hydro Wind Solar Other RE Total India needs to add just 15 GW of coal capacity every year which should be fairly achievable given that India is already adding similar coal capacities every year As such there may not be any capacity constraints going forward in the system as witnessed in period 63

64 All in generation cost of new imported coal based plant to drive overall market prices Year 2022 Capacity Factor Heat Rate Non-Fuel Variable cost Fuel Cost Total Variable cost Fixed cost Total Fixed cost Total Cost (Variable &Fixed) Units % Btu /kwh INR/ kwh INR/ kwh INR/ kwh INR/ kw-yr INR/ kwh INR/ kwh Existing Coal Plant - Domestic 80% 9, New Coal Plant - Domestic 80% 9, Existing Coal Plant - Imported 80% 9, New Coal Plant - Imported 80% 9, Existing Gas Plant - Domestic 40% 8, New Gas Plant - Domestic 40% 7, New Wind 25% New Solar 24% New Hydro - RoR 40% New Hydro - Storage 45% In 2022, the new coal based plant running on imported coal will be at margin with an all inclusive cost of generation of ~ Rs 4.0 per kwh 64

65 Imports in NR from other regions - Summary NR Power Flow Imports* from ER and WR (MW) 7,500 10,000 20,000 35,000 Plant at Margin Imported coal plant in WR Imported coal plant in WR NR would be depending on imports from other regions Imported coal plant in WR Opportunity to replace especially the expected imports from imported coal based plants Imported coal plant in WR Price at Margin (Rs 2013 year) per kwh) Expected imports from Imported Coal based Plants (MW) Approximate Imported Coal based generation in WR (MW) *Average RTC imports 2,000-3,000 2,000-4,000 6,000-8,000 18,000 22,000 33,000 65

66 Key Insights Northern Region is a major importer from the Eastern and Western region The prices in NR will be in the range of INR per KWh in year 2022 with the possibility of additional benefit due to congestion charges in later years Assumptions suggest that it is economical to generate at pithead and transmit electricity rather than transporting coal to the load centre. This indicates heavy reliance on timely construction of transmission capacities both planned and unplanned Development of transmission links is key Imported Coal remains the marginal fuel and with large capacity additions, it removes any seasonality caused by hydro supply Coal based capacity addition is unlikely to be a constraint There is hardly any difference in the seasonal pricing due to (i) flattening load profile, and (ii) coal capacity additions based on imported coal It appears unlikely that there will be any peaking power market in India in the near future Prices are unlikely to change unless the nature of the demand curve changes 66

67 Way Forward In the short term, the Trading potential exists between India-Nepal, India-Bhutan and India-Bangladesh based on the seasonality of demand. ICF is in the process of collecting load profile data from all the countries which would form the basis for calculating short term trading potential. In the longer term, the setting up of new capacities can be avoided by the countries if there is a potential of buying power from other countries. However this would be subject to constraints on transmission, resource availability and the power prices in each market. ICF is in the process of populating the integrated resource model for South Asia region using its proprietary IPM model for calculating the actual trading potential. 67

68 Way Forward (cntd.) ICF has developed the data sheet for capturing information and assumptions from each country. ICF along with IRADe team is following up to capture this information IPM database has been already populated with Indian power sector database. The data from each of remaining South Asian nations would be populated to make the Base case For the Base case, the IPM run would be set up to calculate the year wise trading potential between each the South Asian countries. In this case, no transmission constraint is considered between any countries. In fact, the required cross border transmission required would be the output of the model For the Changed case, actual transmission would be built in the base model. New runs would be subsequently executed. 68

69 Data/Information Requirement from Task Force members of all countries S. No. Parameter Description 1 Energy Demand Energy demand data - actual and forecast 2 Peak Demand Peak demand data - actual and forecast 3 Energy Generation Eneergy generation data - actual and forecast 4 Hourly Load Hourly load profiles for past five years 5 Reserve Margin Planning Reserve margin and average availability during Peak Demand hours 6 Peak Availability Average availability during Peak Demand hours by Technology Type 7 Conventional Energy CF Conventional Energy Capacity Factor - monthly values for different fuel types 8 Renewable Energy CF Renewable Energy Capacity Factor - month wise hourly average 9 Outages Plant wise Monthly Planned and Forced Outage 10 Fuel Cost Build-up Fuel cost and other costs involved in building up final delivered fuel price 11 Existing Units Existing units information for the country 12 Firm Builds Description of recently operational and firmly planned builds 13 Firm Retirements List of proposed retirements 14 Financial Assumptions Financing assumptions for new units 15 RE Potential Renewable Energy Potential by source type 16 RPO Targets Renewable Purchase obligation as defined by the Govt of member countries 17 Transmission Transmission links connecting the country to India 69

70 Appendix Electricity Shortages in India Details on ICF s Integrated Planning Model (IPM ) Key outputs from IPMM Mathematical details on Modeling framework 70

71 Electricity shortages declining Source: CEA * For period Apr-Oct 2014 India s peak supply has grown at a CAGR of ~6% over FY10-FY14, compared to peak demand which grew at 3.5% Energy supply growth of 6.5% is higher than energy demand growth of 4.8%, bringing energy shortages down to ~4.1% over the last 5 years Shortages have gone down significantly in FY14 with good monsoon reducing demand and increase in hydro generation 71

72 Plant Load Factors Witnessed an Overall Decline All India PLF* FY13 FY14 FY15 April May June July August September October November December January February March Annual * For Coal and Lignite Based Plants (Source: CEA) Aggregate PLF for the gas based plants declined primarily due gas supply shortage PLFs of coal based power plants declined due to Accelerated capacity addition coupled with lower demand growth lower coal availability for each MW in system transmission constraints in W3 region which made dispatch of coal plants difficult Despite the decline, generation overall increase in generation was enough to reduce shortages 72

73 Depth of short term market (Bilateral and Exchange Markets) is increasing Share of Bilateral, Exchange and Long Term + UI in Energy Met 8% only * FY15 Data till September 2014 Source: CERC Overall short term market is around 7% - 8% of the total supply Share of bilaterally bought power has increased from ~2.6% to ~5.5% over the last few years Share of exchange traded power has increased from ~0.4% to ~3% in the same period Remaining energy has been met through long term PPAs and the UI balancing market Back to India Electricity D-S 73

74 IPM has evolved over 30 years of helping evaluate complex energy, fuel and environmental markets 1970s: Started as Coal Electric Utility Model (CEUM) to support US Clean Air Act (CAA) regulations 1980s: Expanded to IPM after complete power sector integrated to support US Environmental Protection Agency (EPA) in CAA rule making 1990s: Model used in building several utilities with integrated resource planning, including DSM 1990s: Model used to support EPA with CAA Amendments, cap-and-trade program for NO x, SO x and later mercury regulation; main modeling framework used by EPA in environmental planning for power sector 1990s: Used by US Federal Regulatory Electricity Commission for rule making 2000s: Widely used by states and regional agencies in power, environmental and renewable energy program development (e.g., western states renewable energy portfolio, regional haze, western climate initiative; midwest regional greenhouse gas initiative) 2000s: Widely used for power market forecasting, correctly used in forecast California power market crash and mid-west over build price crash 2000s: Widely used to support GHG analyses of power and non power sectors 2004: ICF launched the India Integrated Planning Model (I-IPM ); supported clients in evaluating Indian power sector fundamentals 74

75 Licensed by leading power companies for power market analysis MidAmerican Energy Pacificorp Exelon Nyserda International Power BP Polish Power and Generation Company 75

76 ICF India Engagements in Asia-Pacific and international fuel market ICF has helped support over $40 billion of power plant financing around the world India: Power Market Study Power Sale Strategy Renewable market study and analysis Technical Due Diligence for Coal Plant Asset Valuation Coal Mine Valuation Transmission & Evacuation Strategy Gas Market Analysis Natural Gas Grid Design Sri Lanka Power & Gas Market Assessment Nepal: Transmission & Evacuation Strategy China: Power Market Analysis Singapore: Asset Valuation Power Market Analysis Vietnam: Power & Gas Market Analysis South Korea: Power Market Analysis GHG Mitigation Strategy Australia: Power Sale Strategies for Wind REC Price forecast and sales strategy Carbon Price Forecast Asset Valuation Power Market Analysis Bangladesh: Energy Efficiency and Management Philippines: Asset Valuation Power Market Analysis Indonesia: Power Market Analysis Marginal Abatement Cost Curves (MACC) for Power Sector Japan: Power Market Analysis 76 76

77 Model Components Analyst 1 Graphical Interface Front End Analyst 2 Demand Forecasting Tool Transmission Flow Model Other Tools and Data Bases Data Base Optimization/ Simulation ENGINE Output Excel and text files 77

78 Modeling Framework Database - Front -End IPM Engine Results Power System Parameters E.g.: Demand All generating units cost, performance Fuel markets Transmission IPM Matrix Generator (.NET) LP Solver (e.g. DASH) Supplemented by transmission models (GE-PSLF, Power-world) IPM Report Writer (.NET) Capacity builds Plant dispatch Generation, expansion costs Power prices Fuel prices Transmission capacity builds & flows Emissions Back to ICF s IPM 78

79 Load (MW) Price (Rs./kWh) Power Prices (Nominal Rs./kWh) Power Prices (Nominal Rs./kWh) Detailed power price forecast Power Price forecast reflects operational considerations, 4.0 system dynamics and market fundamentals 2.0 Prices based on marginal cost 0.0 with merit order dispatch Simultaneously available for all states regions and at regional and national level Available for all hours and years of the planning horizon Plant specific generation costs can be used to derive cost plus regulated price Segmental prices mapped to chronological hourly prices Illustrative wholesale forward power price curves National Level Round The Clock Peak Prices Off-Peak Price ,000 20,000 15,000 10,000 5,000 Round The Clock Peak Prices Off-Peak Price Illustrative Load Duration and Price Duration Curve for Winter Maharashtra (2013) Hour

80 Dispatch Cost (Rs./kWh) Dispatch Cost (Rs./kWh) Detailed results on dispatch, merit order and marginal prices System System All India Dispatch Stack - Illustrative for Year 2010 All India Dispatch Stack - Illustrative for Year Coal Shortages, Hydro, Renewables and Nuclear Oil CC & CT Cumulative Capacity (GW) 9 CC Potential Build CC-F CT8 Potential Build CT-LM Potential 7 Build Hydro Hydro PS 6 Potential Build Diesel Oil Potential 5 Build Nuclear Nuclear Potential 4 Build Small Hydro Small Hydro Potential Build Wind 3 Wind Retierment Potential 2 Build Biomass Biomass Potential 1 Build Coal Coal Retrofit Coal 0 Coal Shortages, Oil CC & CT Hydro, Renewables and Nuclear Cumulative Capacity (GW) 80

81 Transmission flows and Energy transfers available for all lines and years of planning horizon Forecast based on I-IPM. India Wholesale Power Outlook

82 Transmission Corridor Utilization (%) Transmission congestion can be forecasted for all the years of planning horizon 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 1 Illustrative transmission line utilization under various seasons OR to AP (2011) WESTERN NORTHERN EASTERN 1 Hours UP MH MP AP CH 91 JH OR BI WB Illustrative Line Congestion in Peak segments (2011) SOUTHERN Weighted Average % of Hours Congested Forecast based on I-IPM. India Wholesale Power Outlook

83 Detailed forecast on REC prices Regional and national renewable market and policy analysis Renewable power market supply and demand analysis Long term REC price forecasting Renewable project strategy development and RPO compliance Renewable solicitations and power purchase agreements developments Illustrative REC price forecast TWh Higher Renewable generation in initial years ( ) banked for future ( ) REC Price (Rs./kWh) Renewable Target Renewable Generation REC Price Back to Key Outputs from IPM 83

84 IPM uses easy to comprehend yet extremely Powerful Linear Programming methodology c 1 x 1 + c 2 x c n x n min or in vector notation: a 11 x 1 + a 12 x a 1n x n > b 1 c T x min a 21 x 1 + a 22 x a 2n x n > b 2 Ax > b x > 0 a m1 x 1 + a m2 x a mn x n > b n x ij > 0 LP problem of IPM may include as much as: - 10,000,000 variables/columns - 1,000,000 constraints/rows -100,000,000 non-zero elements 84

85 Objective Function of IPM Minimize present value of the total system costs and unserved load capacity * * FOM year plant season segment fuel new_ build DSM _ programs sns season capacity * bnb segment contracts ( y1) 1 d generation * heat _ rate* fuel _ cos t VOM * 1 d book_ life transmissi on investment _ cos t * ccr* 1 d... _ * ( y1) unserved load VLL *(1 d) MIN ( y1) ( y1) 85

86 Major Types of Constraints in IPM Energy Constraints: DSM plants fuels dispatched _ capacity transmissi on links ( MW _ received MW _ sent) ( MW _ saved) unserved _ load segment _ load for each LDC segment, in each year, season, region or node Capacity Constraints: plants installed _ capacity* eff peak _ load transmissi on links transmissi on links ( firm _ MW _ exp orted)) for each each year, season, region or node ( firm _ MW _ imported ) contract contracts contract ( MW _ purchased MW _ sold) ( firm _ MW _ purchased) DSM firm _ MW _ sold) *(1 reserve_ margin) ( peak _ MW _ saved) 86

87 Major Types of Constraints in IPM (cont.) Dispatch Constraints: installed _ capacity*(1 ma int enance)*(1 forced _ outage_ rate) fuelssegments dispatched_ capacity for each plant, year, season Fuel Constraints: dispatched_ capacity plantsegment for each fuel, year, season Environmental Constraints: dispatched _ capacity* segment _ plantsegment * segment _ width * heat_ rate fuel_ available width * heat _ rate* unitary _ emission * emission _ reduction_ factor allowances_ banked allowances_ withdrown allowances_ purchased_ allowances_ sold emission _ cap for each constraint, year, season 87

88 Major Types of Constraints in IPM (cont.) Capacity Factor Constraints: segments dispatched _ capacity* segment _ width installed _ capacity(1 ma int enance)*(1 for chosen plants, years and seasons forced _ outage) Area Protection/Must Run Constraints: must_ run_ segments dispatched _ capacity must _ run_ coefficient * available_ capacity for chosen plants, years and seasons Turn Down Constraints: base_ load_ segments dispatched _ capacity coefficient * segmepeaki ng_ segments dispatched _ capacity for chosen plants, years and seasons 88

89 Cost Coefficients in Objective Function Variable cost coefficients assigned to dispatch operates years mapped VOM ( plant, segment, season, year) 1 * HR( plant,segment, season, year)*( fuel _ cos t( fuel, year) adder( fuel, season)) (1 disc( year)) year1 Fixed cost coefficients assigned to capacity vectors time horizon FOM ( plant, year) Capital _ cos t( plant, year)* CCR( plant, year) * year1 1 (1 disc( year)) where: CCR r( plant, year) 1( 1 r( plant, year) ) ( plant, year) book_ life( plant, year) Back to Modeling Framework 89

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