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Cutter - E3 Valuing Storage short
1. Utilities currently evaluate energy storage based on its net market value within traditional utility planning models and valuation frameworks that focus on costs and today's markets. However, better matching of storage technologies to grid services could unlock more value for ratepayers. 2. High renewable penetration will require increased grid flexibility that can be provided by flexible resources like energy storage. Future cost reductions and operational experience with storage will help reduce costs and make storage more competitive for renewable integration. 3. There is uncertainty around the optimal amount of energy storage investment given uncertainty in future cost reductions for storage technologies. A range of cost scenarios can help identify the timing and least-cost strategies for procuring energy storage.
Cutter - E3 Valuing Storage short
- 1. Uncertainty and theValue of Energy Storage Storage Week January 25, 2016 San Diego, CA Eric Cutter
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- 3. $0 $50 $100 $150 $200 $250 $300 $350 Levelized$/kW-Yr Combustion Turbine (2014) Fixed Cost $200 Net Revenue $63 Net Capacity Cost $137 Utilityview of storage: a CT Fitting storage into a “standard” capacity product undervalues storage Best value for ratepayers requires better matching of technologies the grid services 3 aka “CONE”: Cost of New Entry
- 4. $0 $50 $100 $150 $200 $250 $300 $350 Levelized$/kW-Yr Flexible Capacity Product Fixed Cost Net Revenue Net Capacity Cost Reducing costof storage Cost benchmarks that reflect future system needs Forward looking flexibility value with high RPS Operating experience and cost reductions for the storage needed in 2020 4
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- 6. Flexibility needed forhigh renewable penetration 6 Over- generation is a new challenge in solar- dominant systems like CA 40% RPS Spring Day Generation Profile Grid benefits performed by flexible resources
- 7. 7 Net Market Value Utilitiesevaluate storage based on net market value Utility planning assumptions and models determine benefits Today Tomorrow
- 8. Challenges selling toutility Not necessarily convinced they need storage Use traditional models and valuation framework Focus on cost Focus on today’s markets Getting multiple departments to sing in unison Little sense of urgency: wait and see approach 8
- 9. LOOKING AHEAD -WEST 9
- 10. 10 WECC Wide FlexibilityStudy 10 Main zone: • Optimal investment decisions • Detailed treatment of operating reserves Other zones: • Exogenous resource assumptions and loads by scenario Flows may be impacted by: • Min and max intertie flow constraints • Min and max simultaneous flow constraints for groups of interties • Ramping constraints on interties • Hurdle rates Example zonal structure – High Renewable West Scenario
- 11. 11 California dispatch, averagenet load day in May California Overgeneration Driven by Mid-day Solar Production Gas fleet operates at minimum, subject to min gen constraint Renewable production from solar PV causes mid-day oversupply, leading to curtailment Significant imports during shoulder periods Renewable Penetration: 50% (% of load) Renewable Curtailment: 8.7% (% of annual renewables) Curtailment Frequency: 20% (% of hours per year)
- 12. 12 Northwest dispatch, averagenet load day in May Renewable Penetration: 30% (% of load) Renewable Curtailment: 6.1% (% of annual renewables) Curtailment Frequency: 10% (% of hours) Northwest Overgeneration Results from Combined Hydro & Wind Curtailment occurs throughout day but is most pronounced at night (low loads & high wind) Hydro energy accounts for significant shares of daily load Significant exports during off-peak hours, but limited during middle of day
- 13. 13 Southwest Scale (MW) 0 7,000 Northwest Scale (MW) 0 4,000 HE01HE24 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec HE01 HE24 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec California HE01 HE24 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec HE01 HE24 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Tot: 8.7% Scale (MW) 0 16,000 Tot: 3.0% HE01 HE24 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec HE01 HE24 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Regional Coordination is a Low- Hanging Fruit Among Solutions Historical Intertie Limits Physical Intertie Limits Tot: 5.6% Tot: 2.0% Tot: 7.3% Tot: 6.1% Large reductions in nighttime curtailment Large reductions in non-spring curtailment Limited impact on curtailment
- 14. 14 Storage Downward Flexibility ReducesCurtailment Addition of 6 GW of long- duration storage relieves curtailment Addition of 6 GW of flexible CCGTs has little impact Source: TEPPC Western Interconnection Flexibility Assessment 04 Nov 2015
- 15. LOOKING AHEAD -EAST
- 16. 16 Forward curves underenergy policy uncertainty Reference case represents best in class energy market and capacity market dispatch. Extension to scenario analysis approach describing key context and impact of policy on energy market identifies critical market disruptions 16 Reference Case: Compliance with existing policy, with expected technology advancements and cost reductions High Renewables: Implement required renewables to hit goal despite budget constraints. Increasing to 50% renewable generation REV Policy Case: Assuming successful policy implementation and increased DER participation in energy markets. Changing the load profile and load factor $0 $20 $40 $60 $80 $100 $120 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 EnergyPrice($/MWh) Year Historical Business-as-usual High Renewables Long Island Baseload Energy Price ($/MWh) Results show significant changes in market fundamentals depending on policy case and zone
- 17. 17 REV Background andImpact The goal of the REV proceeding is to facilitate the deployment of distributed energy resources (DER), provide consumers with choice and value over their energy use, and improve system efficiency Details of how to these goals will be achieved are not finalized, but a successful REV program should improve system efficiency To assess wholesale impacts of distributed resources, we assume NYISO’s system load factor improves to 60% by 2030 (agnostic to technology) Details 17 1 24 Load(MW) Hour Hourly Load Shape in 2030 Base load shape REV load shape Flatter due to various DER deployment 40% 45% 50% 55% 60% 65% 70% 75% 80% 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029 LoadFactor(%) Year NYCA Annual Load Factor Historical Base System efficiency continues to decline REV Scenario DER improves system efficiency
- 18. 18 0 1,000 2,000 3,000 4,000 5,000 6,000 BAU High REREV SummerCapability(MW) Scenario New Gas Plant Investment by 2035 CT Gas CC Gas Investment Outlook for New Plants Economics of new investment varies substantially across scenarios 18 Technology BAU High RE REV Combined Cycle High Low Medium Combustion Turbine Medium Medium Low Onshore Wind Medium High Medium Offshore Wind Low High Low Utility-scale Solar Low High Low CC outlook poor due to depressed energy market CTs still attractive in capacity market DER impact on load shape reduces need for peaking plants Summary of Investment Outlook
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- 20. System Overview Oahu MauiMolokaiHawaii EnergyProduction by Type Peak Load (MW) 193 6 1176 197.3 Min Load (MW) 82 2 521 86.7 Pmin+ Downward Reserve (MW) 61 1.8 277 46.98 Intermittent RE Capacity ‘15 (MW) 111.8 1.7 420.1 134.3 Preapproved DG PV (MW) 25 0.426 117.2 35 44% RE 8% RE 8% RE 32% RE
- 21. Island system constrainedby Pmin & reserves Determine whether the net load ever drops below Pmin + reserves • If so, normal system operations are interrupted How often do these events occur? What is the frequency and size of the problem? What are the potential solutions? headroom 21
- 22. Comparing Curtailment Costto Battery Cost 2016 Curtailing renewables is cheaper than installing storage – using traditional evaluation framework
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- 24. Renewable integration solutions 24 Varioussolutions have been proposed, with different performance characteristics and costs • Energy storage (pumped hydro, batteries, compressed air, etc) • Flexible loads or advanced DR • Flexible gas resources (new flexible CCGTs, Aero CTs, Reciprocating Engines or retrofits to existing plants) • Expansion/consolidation of balancing areas • Time-of-use rates Teslamotors.com http://renews.biz/67193/vattenfall-pumps-new-life-into-80mw Wartsila.com http://allthingsd.com/files/2012/10 /Nest-Cooling-2.jpg http://www.theiet.org/membership/member- news/31a/ev-charging-course.cfm
- 25. Economics of renewableintegration The consequence of failing to supply enough flexibility to integrate renewables is renewable curtailment Full capability from procured renewables Delivered energy from procured renewables Curtailment Renewable energy target
- 26. Option 1. Overbuild renewables Anticipatedrenewable build Curtailment-related renewable overbuild Option 1. Overbuild the renewable fleetOverbuilding the renewable fleet allows for policy goal to be met with some allowance for curtailment Curtailment
- 27. Option 2. Pursue integrationsolutions Option 2. Pursue integration solutionsIntegration solutions (eg. storage, balancing area consolidation) permit more effective delivery of existing renewable fleet Energy Storage Renewable build Energy storage build
- 28. Option 3. Mix ofsolutions (Options 1 & 2) Option 3. Find optimal solutionOptimal solution combines multiple strategies based on costs and benefits Energy Storage Curtailment Energy storage build Anticipated renewable build Curtailment-related renewable overbuild
- 29. Option 3 isOptimal Solution Balances Storage with Overbuild Optimal amount of storage is highly sensitive to assumed technology costs
- 30. Identifying optimal investmentin solutions 30 Single solution case: • The cost of the solution can be weighed against the avoided cost of overbuilding renewables for RPS compliance Multiple solution case: • Multidimensional optimization • Complex interactive effects • Requires sophisticated model that treats both operations and investment costs Optimal investment point: Marginal avoided cost of renewable overbuild = Marginal cost of solution
- 31. Example analysis: Optimal storageinvestment 31 Wide uncertainty in future cost reductions Wide range in optimal storage build Base Assumption Q. Given the wide range of potential future cost trajectories, what is the optimal amount of energy storage? RESOLVE: Storage cost scenarios can be designed to provide a plausible range of least-cost storage procurement strategies; can also: • Identify timing of storage build across sensitivities • Test cost impacts of suboptimal storage build Storage technology costs ultimately determine the optimal energy storage investment High level of uncertainty complicates the planning problem
- 32. STORAGE IN WORLDOF UNCERTAINTY - IDSM 32
- 33. Capacity Value ofRenewables Declines Significantly Above 33% High penetration of solar PV pushes the “net peak” demand that must be met with dispatchable resources into evening hours California will continue to need capacity resources to meet peak demands 0 10 20 30 40 50 60 1 2 3 4 5 6 7 8 9 101112131415161718192021222324 Load(GW) Hour 0 1 2 3 4 5 6 0 6 12 18PeakLoadReduction(GW) Installed Solar PV Capacity (GW) Daily Load Shape with Increasing Solar PV Cumulative Peak Load Reduction
- 34. Storage as Partof Optimal Portfolio 34 Description Current situation Key metrics 13.5 MW:Current peak 56,000 MWh:Energy 5%/year:Load Growth 24 hr load profile Year on year load profile BaseCaseForecast Alternative future states Upgradeelements DER 1Hardware DER 2 11 MW 8 MW 4 MWHardware Solar DR EE Storage Keymetrics 24 hr load profile 0 MW 1.6 MW 4.4 MW 0 MW 3.3 MW 3.3 MW 0 MW 1.6 MW 1.6 MW 0 MW 0 MW 5 MW Cash flow 24 hr load profile Cash flow 24 hr load profile Year on year load profile Year on year load profile Year on year load profile Cash flow High load growth in urban area where upgrades are expensive due to site constraints
- 35. Storage Reduces Risk 35 Nextgen solution ▪ Plan based on value of reliability and cost of upgrade ▪ Factor in forecast uncertainty into investment decision IDSM ApproachCurrent solution ▪ Engineering studies to identify N-1 redundancy requirement Identifying investment ▪ Choose from traditional T&D capital investment supply options ▪ Expand options to meet load growth and reliability needs to include DER ▪ Integrate DER and traditional investments in decision process Investment options for maintaining reliability Peak load served (MW) Systemavailability (%likelihood) 99.999% Additional service from investment Forecast Years PeakLoad(MW) Forecast uncertainty captured substation modular Integrated DER Presentvalue$ substation modular Integrated DER Expectedoutage$
- 36. Conclusions for energystorage Utilities feel little sense of urgency: have a wait and see approach Traditional models and valuation frameworks undervalue the flexibility that storage provides To utilities regional coordination and renewable curtailment look like cheaper alternatives to storage Looking further ahead with stochastic, portfolio models is crucial to fully value storage Need to show utilities that storage is part of an optimal portfolio in an uncertain world 36
- 37. Thank You! Energy andEnvironmental Economics, Inc. (E3) 101 Montgomery Street, Suite 1600 San Francisco, CA 94104 Tel 415-391-5100 Web: http://www.ethree.com Eric Cutter (eric@ethree.com)