Flexibility to integrate variable power generation into the egrid Digital Transformation in Power Sector January 2019 BRAZIL CHINA EUROPE INDIA INDONESIA UNITED STATES Udetanshu udetanshu@cpilondon.orgorg climatepolicyinitiative.org
Agenda Flexibility needs in India are growing Different resources can meet these requirements Demand side measures Storage, including batteries Powerplant flexibility A portfolio approach of flexibility options provides the best combination of lower cost, greater certainty of outcome, and lower carbon emissions Developing and deploying flexibility options will take technology development, policy support and investment 2
A high renewable energy grid, enabled by demand side, storage and powerplant flexibility is almost the same as one largely powered by fossil fuels System cost including flexibility Current Trajectory (274 GW Wind and Solar) 4.7 Rs/kWh 4.5 Rs/kWh High RE (390 GW Wind and Solar) 5.1 Rs/kWh Energy shortfall* 4.6 Rs/kWh Storage Demand Flex Thermal, hydro, nuclear Renewables 2030 CTS Base Case (with shortfall) 2030 CTS Portfolio 2030 High RE Base Case (with shortfall) 2030 High RE Portfolio * Energy shortfall cost measured as fixed capacity and variable energy cost of backup diesel generators 3
Flexibility needs will increase faster than electricity demand, driven by changing consumption patterns and increased variable generation Growth in Key Flexibility Needs 20172030 Demand Flexibility Needs 6.3x 54x 5.4x 2.0x 2.2x 4.1x 3.9x 3.4x 34 3.5x 3.4x 31 3.1x 32x 2.9x 3.0x 3.2x 4.5x Current Traject ory Current Policy High RE Energy Peak Demand Reserve Maximum Seasonal Daily Requirement (GW) Requirement Ramp Balancing Balancing (TWh) (GW) (MW/min) (TWh/month) (GW) Total Energy (TWh) Peak Demand (GW) Reserve Need (GW) Ramp (MW/min) Seasonal Balancing (TWh/month) Daily Balancing Average (GW) Estimated as 3% Rate of Residual Average spread of peak demand plus 5% of peak renewable production, as a proxy for maximum 1 hour ramp in a year energy requirement (after VRE) in highest vs. lowest month between maximum and minimum residual demand (ft (after VRE) forecast errors 4
Without technology and/or policy changes, flexibility could become an issue in the next few years Preliminary evaluation of current Indian electricity system s ability to deliver key types of flexibility Under TERI high renewable energy scenario Type of flexibility 2017 2020 2025 2030 Time rations Real Oper <1 min 5 min 15 min Spinning and loadfollowing Shortterm reserve Schedu uling and Forec casting hour day Ramping Daily balancing Regional Issues Regional Issues Plan nning season Year(s) Seasonal balancing Regional Issues Regional Issues 5
Even under the current trajectory scenario, new resources will be needed before 2026 Excess Generation in Current Trajectory Scenario (% of VRE Generation) 6.0% 6.4% 0.0% 2.5% 2017 2021 2026 2030 Peak Capacity Shortfall without additional resources in Current Trajectory Scenario (GW) 41 GW 5 GW 2017 2021 2026 2030 6
Flexibility needs will arrive sooner and be more significant in some states Excess Generation (% of VRE, before thermal minimum) Load factor of residual demand (%) 20% 80% 18% 16% 14% 12% Karnataka Tamil Nadu 70% 60% 50% Uttar Pradesh Bihar All India (CPS) 10% 40% 8% 6% 4% All India (after thermal minimum) 30% 20% Tamil Nadu Karnataka 2% 0% 2017 2021 2026 2030 All India (CPS) 10% 0% 2017 2021 2026 2030 7
Agenda Flexibility needs in India are growing Different resources can meet these requirements Demand side measures Storage, including batteries Powerplant flexibility A portfolio approach of flexibility options provides the best combination of lower cost, greater certainty of outcome, and lower carbon emissions Developing and deploying flexibility options will take technology development, policy support and investment 8
India may have new options beyond existing power plants flexible demand and storage to help meet flexibility needs by 2030 Demand side Readiness of flexibility options to deliver flexibility 2017 2030 Storage Powerplant Demand side Storage Powerplant Operating Reserves Ramping Daily Balancing Seasonal Balancing 9
Demand side measures have high potential and low cost 2030 Reserve Supply Curve Rs. / kwh 14,000 9,000 4,000 Reserve need: ~25 GW (1,000) 25 50 75 100 125 150 175 200 225 250 275 GW 2030 Daily Balancing Supply Curve / kwh Rs. 30 25 20 15 10 5 Daily balancing need: 845 GWh 200 400 600 800 1,000 1200 1,200 1400 1,400 1600 1,600 1800 1,800 2,000 GWh/Day 10
Significant low cost potential for demand side flexibility maybe challenging to unlock 600 GW 2030 Flexibility Operating Reserve Ramping Flexibility Daily Flexibility Seasonal Flexibility Industry Industry 20 GW 20 GW/hr 20120 GWh/day Possible, Not Quantified EV Charging EV Charging 12.5 GW 12.5 GW/hr 75 GWh/day Ag. Pumping Agri Pumping 37.7 GW 37.7 GW/hr 226.3 GWh/day 180 GW Room AC 90 GW Central AC 40 GW Space Cooling 19.8 GW 19.8 GW/hr 27.8 GWh/day Connected Load Low Mid High Potentially Flexible by 2030 11
Battery Storage costs are declining rapidly as manufacturing capacity scales, but the majority of supply will go to the EV market Lithium Ion Battery Storage System Capex Cost (per kwh of energy storage capacity) Global Lithium Ion Battery Demand (GWh/yr) 587 USD 41,000 INR 404 USD 28,000 INR 244 USD EV demand will drive the market and cost reductions 17,000 INR 142 USD 10,000000 INR 2017 2020 2025 2030 Pack BOS Soft Costs EPC Costs Based on McKinsey figures, assuming India BOS discount of 25% by 2030, increasing from no discount in 2017. 2030 extended based on 20172025 CAGR. Exchange rate 70 INR/USD. Source: BNEF 2018, assumes 100% of stationary storage demand met by lithium ion. 12
Battery Storage will become more cost competitive and highly scalable by 2030 2017 Daily Balancing Supply Curve Rs. / kwh 30 25 20 15 10 5 Daily balancing need: 160 GWh per day Battery Technologies 150 300 450 600 750 900 1,050 1,200 1,350 1,500 1,650 1,800 1,950 2,100 GWh/Day kwh Rs. / 30 25 20 15 10 5 2030 Daily Balancing Supply Curve Daily balancing need: 870 GWh per day Without Demand Flexibility Battery Technologies 150 300 450 600 750 900 1,050 1,200 1,350 1,500 1,650 1,800 1,950 2,100 GWh/Day 13
Battery Storage can serve multiple flexibility needs, and stacking values makes storage more competitive Additional cost of battery and pumped hydro capex Storage cost vs. value High RE storage portfolio vs. thermal portfolio 8.0 17.2 2.4 6.0 8.9 Shift from highcost to low cost thermal plants Reduced thermal generation Avoided thermal capacity Cost Value Rs. / kwh 30 25 20 15 10 5 Daily Flexibility Only Need w/o Demand Flexibility Battery Technologies 50 100 150 200 250 300 350 2030 Daily Balancing Supply Curve Battery Capex Paid for by Other Services Need w/o Demand Flexibility 50 100 150 200 250 300 350 GW Batteries become highly hl cost GW competitive when capex costs are amortized across multiple services 14
Existing and planned power plant capacity can provide costeffective ways to meet multiple flexibility needs 2030 Daily Balancing Supply Curve Rs. / kwh 30 25 20 15 10 5 Daily balancing need: 870 GWh per day Without Demand Flexibility 25 50 75 100 125 150 175 200 225 250 275 300 325 350 GW 2030 Seasonal Balancing Supply Curve Rs. / kwh 50 40 30 20 10 Existing hydro power plants New hydro power plants Existing thermal power plants New thermal power plants Peak daily balancing need: 685 TWh Seasonal balancing need 770 TWh 100 200 300 400 500 600 700 800 900 1,000 TWh/year 15
Unlocking potential flexibility from existing thermal power plants depends on addressing contractual limitations and operating practices Potential Flexible Capacity from Existing Thermal Power Plants Existing Additions and Adjust for Adjust for Minimum Capacity Retirements Availability Generation 268 GW Diesel (mostly DG) Gas (mostly CCGT) Subcritical nonpithead 258 GW 70 GW Opportunity to increase flexible range through retrofit of subcritical plants 81 GW Sub. pithead Supercritical nonpithead 107 GW Supercrit. pithead Existing Plants Existing Plants in 2030 (TERI High RE Case) Adjusted for Availability Flexible Range 16
Hydro power plants can offer valuable flexibility, but only during some periods Indiawide minimum and maximum daily hydro production, 2014 (CEA) 80% 70% 60% Reservoir capacity (and silting) limits amount of monsoon rains that can be stored for later capacity % of total hydro 50% 40% 30% 20% 10% Irrigation or contractual flows contribute to production profiles Seasonal and interannual rainfall patterns drive variations in flows 0% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Maximum daily hydro output Flexible range of hydro capacity Minimum daily hydro output 17
Integrating captive diesel generation into grid operations for flexibility may be an important option to meet peak daily balancing needs 2017 Peak Daily Balancing Supply Curve Rs. / kwh 350 300 250 200 150 100 50 Peak daily balancing need: 300 GWh/day Captive Diesel Gensets @ 2% Capacity Factor 25 50 75 100 125 150 175 200 225 250 275 300 325 350 GW 2030 Peak Daily Balancing Supply Curve / kwh Rs. 350 300 250 200 150 100 50 Peak daily balancing need (CPS): 1080 GWh/day Without demand Captive Diesel Gensets @ 2% Capacity Factor flexibility 25 50 75 100 125 150 175 200 225 250 275 300 325 350 GW 18
Agenda Flexibility needs in India are growing Different resources can meet these requirements Demand side measures Storage, including batteries Powerplant flexibility A portfolio approach of flexibility options provides the best combination of lower cost, greater certainty of outcome, and lower carbon emissions Developing and deploying flexibility options will take technology development, policy support and investment 19
The cost and construction of optimal flexibility portfolios will depend on the level of variable renewable energy and the availability of demand side flexibility Maximum potential Availability of demand side flexibility None (Today s level) Likely outcome: Demand side driven Unlocking significant demand side flexibility with limited new thermal, reduced curtailment of RE Cost Low to medium Decarbonisation Medium B Likely outcome: Portfolio driven Portfolio of flexibility options with mix of high quality demand and storage, supported by hydro and residual thermal powerplants Cost Medium Decarbonisation High Likely outcome: Powerplant driven Likely outcome: Storage driven Dominated by existing and Dominated by battery new thermal and hydro, storage (with low cost curtailment of RE, modest batteries) and pumped addition of battery hydro, with limited new storage, pumped hydro thermal (as seasonal and demand flexibility resource) and modest Cost Moderate to high demand flexibility Decarbonisation Low to A Cost Medium to High Today medium Decarbonisation High Today Meeting government targets D C High RE scenarios Penetration of variable renewable energy 20
Thermal power plant contribution to flexibility depends on interactions with other system resources Demand Side, Storage and Thermal Driven Portfolio Thermal Driven Portfolio Stored/shifted energy Storage Demand Flex Coal Sub. NPH Coal Sup. NPH Coal Sub. PH Coal Sup. PH Biomass Nuclear 916 917 918 919 920 921 922 916 917 918 919 920 921 922 Solar Wind Hydro Thermal Asset Roles: Thermal Asset Roles: Cheapest pithead plants turn down infrequently Even cheapest pithead plants turning down Limited intraday ramping and balancing daily Relatively flat profile More expensive non pithead plants ramping Storage and demand shifting absorb most midday solar production and follow changes in load High minimum generation levels contribute to / RE substantial midday d excess energy production substantially to balance supply and demand 21
Profile Charts Compared for High Renewable Energy Scenario Powerplant Driven Demand Driven Storage Driven Portfolio Approach Dispatch Profile Late January 4,00,000 3,50,000 000 3,00,000 2,50,000 2,00,000 1,50,000 1,00,000 50,000 127 128 129 130 131 21 22 127 128 129 130 131 21 22 127 128 129 130 131 21 22 127 128 129 130 131 21 22 Dispatch Profile July 4,00,000 3,50,000 3,00,000 2,50,000 2,00,000 1,50,000 1,00,000 50,000 78 79 710 711 712 713 714 78 79 710 711 712 713 714 78 79 710 711 712 713 714 78 79 710 711 712 713 714 22
Portfolios of demand, storage, and powerplant flexibility perform best on most metrics, and are the least risky Portfolio Performance (2030) Current trajectory Scenario Target Met? Excess Energy Total Cost Carbon emissions Portfolio Performance (2030) High RE Scenario Target Met? Excess Energy Total Cost Carbon emissions Yes 10% 4.8 (Rs/kWh) 0.6 (t/mwh) Powerplant Driven Powerplant Driven Yes 13.8% 5.0 (Rs/kWh) 0.5 (t/mwh) Demand Demand Flex Yes 83% 6% 6% Flex Yes 63% 7% 9% Driven Driven Storage Driven Yes 95% 4% 6% Storage Driven Yes 80% 5% 10% Balanced Portfolio Yes 97% 5% 8% Balanced Portfolio Yes 82% 8% 12% 23
India can integrate 390 GW of wind and solar by 2030 without increasing costs System Cost Including Flexibility Current Trajectory (274 GW Wind and Solar) High RE (390 GW Wind and Solar) Energy shortfall* 4.7 Rs/kWh 4.8 Rs/kWh 4.5 Rs/kWh 4.5 Rs/kWh Storage Demand Flex 5.1 Rs/kWh 5.0 Rs/kWh 4.6 Rs/kWh 4.6 Rs/kWh Thermal, hydro, nuclear Renewables Base with Shortfall Thermal Flexibility Demand Flexibility Portfolio Base with Shortfall Thermal Flexibility Demand Flexibility Portfolio * Energy shortfall cost measured as fixed capacity and variable energy cost of backup diesel generators Key Insights Demand side is important in High RE scenarios Balanced and demand flexibility portfolios significantly reduce costs, even at low RE ambitions A flexible, High RE system is less expensive than an inflexible low RE system 24
Agenda Flexibility needs in India are growing Different resources can meet these requirements Demand side measures Storage, including batteries Powerplant flexibility A portfolio approach of flexibility options provides the best combination of lower cost, greater certainty of outcome, and lower carbon emissions Developing and deploying flexibility options will take technology development, policy support and investment 25
Role of Digitalisation in delivering flexibility Connect Digital infrastructure and automated communications Gather Usage profile and flexibility e.g. price elasticity Process Automated analytics on usage and flexibility Incentivise Generate incentives to affect behavior Control and Manage Automated Centralised Access Payments and Settlement Match flexibility supplied with value generated 26
Role of Digitalisation in delivering flexibility: Examples 15,000 Ramping need: ~887 MW/Min Delivering EV for ramping needs Rs. / kwh 10,000 5,000 Rs s. / kwh 30 25 20 15 10 5 730 1,460 2,191 2,921 3,652 4,382 5,113 MW/Min Daily Flexibility Only Need w/o Demand Flexibility Battery Technologies 50 100 150 200 250 300 350 GW Value stacking in battery storage Batteries become highly costcompetitive when capex costs are amortized across multiple services 27 Battery Capex Paid for by Other Services Need w/o Demand Flexibility 50 100 150 200 250 300 350 GW
Role of Digitalisation in delivering flexibility: Examples Delivering demand dside for Daily Balancing Rs. / kwh 30 25 20 15 10 5 Daily balancing need: 845 GWh 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 GWh/Day Delivering captive diesel gensets for Peak Balancing Rs. / kwh 350 300 250 200 150 100 50 Peak daily balancing need (CPS): 1080 GWh/day Without demand Captive Diesel Gensets @ 2% Capacity Factor flexibility 25 50 75 100 125 150 175 200 225 250 275 300 325 350 GW 28
Flexibility to integrate variable power generation into the grid Thank You 29