Presentation is loading. Please wait.

Presentation is loading. Please wait.

ENERGY VALUE. Summary  Operational Value is a primary component in the Net Market Value (NMV) calculation used to rank competing resources in the RPS.

Similar presentations


Presentation on theme: "ENERGY VALUE. Summary  Operational Value is a primary component in the Net Market Value (NMV) calculation used to rank competing resources in the RPS."— Presentation transcript:

1 ENERGY VALUE

2 Summary  Operational Value is a primary component in the Net Market Value (NMV) calculation used to rank competing resources in the RPS Calculator  It reflects the operational value of a resource and its ability to meet net load based on its generation profile  The new methodology in Version 6.0 now reflects the declining marginal value of energy as renewable penetrations increase RPS Calculator Valuation Framework Levelized Cost of Energy Transmission Cost Capacity Value Energy Value Net Resource Cost Integration Cost* − = − *Not currently quantified in RPS Calculator

3 Dynamic Energy Valuation  Methodology used to value output of renewable generation captures declining returns to scale, allowing for better analysis of high penetrations Version 6.0  Energy value evaluated endogenously in each year based on other renewable resources in portfolio  Value streams calculated based on impact to ratepayers over term of a resource’s contract Version 6.0  Energy value evaluated endogenously in each year based on other renewable resources in portfolio  Value streams calculated based on impact to ratepayers over term of a resource’s contract Version 2.0 – 5.0  Energy value attributed to renewable resources based on static assumptions  Value based only on snapshot in 2020 Version 2.0 – 5.0  Energy value attributed to renewable resources based on static assumptions  Value based only on snapshot in 2020

4 Energy Value 4  Energy value intended to capture the direct impact of renewable generation on system operations  In Version , renewable resources were each given a fixed energy value ($/MWh)  Differentiated between renewable resources based on the time in which they generate  Assumed that the market heat rate was not impacted by continued renewable build Guiding Principle: Resources that avoid thermal generation during hours with higher prices have more value

5 Why is a New Method Needed? 5  The marginal value of each renewable technology is impacted by the other renewables online  Example: Today, solar generation during peak hours avoids generation from the most costly thermal units  Solar build puts downward pressure on energy prices, reducing the value of incremental solar build  At high penetrations, solar generation can saturate the system  Version 6.0 evaluates energy value by focusing on two impacts on system operations: 1.Reduction in variable cost of operations 2.Overgeneration resulting from renewable build-out

6 Goals for New Methodology 6 Model FunctionalityVersions 1-5Version 6 Differentiate energy value between renewable resources  Capture renewable portfolio effects  Capture declining energy value with resource saturation  Account for renewable overgeneration 

7 Theoretical Thermal Generation Supply Curve 7  Dynamic Analysis  Guiding principle: the primary determinant of the value of energy at a given time is the amount of load that must be met with gas generation + imports Figure is illustrative only

8 Energy Valuation 8  Dynamic Analysis  Guiding principle: the primary determinant of the value of energy is the amount of load that must be met with gas generation + imports  Methodology 1.Approximate the amount of Gas + Import generation (MW) needed to serve load at a month-hour level from load and renewable shapes 2.Develop relationship between Gas + Import dispatch levels (MW) and marginal dispatch heat rate based on fleet characteristics 3.Approximate energy prices by month-hour from Gas + Import dispatch in future years and market heat rate function from Step 2 4.Calculate an average production value by technology in future years based on energy prices and month-hour generation shapes

9 Energy Value Calculation Assumptions –All gross load is inflexible –All gas and import generation is perfectly flexible –Overgeneration results in an energy price of $0/MWh Not addressed: –Incremental energy storage procurement –Potential exports from CAISO to reduce curtailment –Localized transmission constraints Energy Value ($/MWh) Marginal Avoided Heat Rate (MMBtu/MWh) Gas plus CO2 Price ($/MMBtu) Avoided Variable O&M Cost ($/MWh) Varies by month-hour and net load shape Escalates each year

10 Dynamic Value Analysis Step 1. Gas + Import Dispatch Marginal energy value at a point in time is determined by the variable cost of the marginal unit (i.e. market price of energy) Variable cost of marginal unit depends on both demand- and supply- side conditions –Hourly load level –Renewable generation (wind, solar, baseload) –Hydro conditions –Other inflexible generation (cogeneration, nuclear) The amount of gas/imports needed to serve load is approximated for each month-hour in each year based on these conditions –12x24 shapes

11 A minimum amount of thermal generation is necessary to provide reserves and inertia to the system –The minimum thermal generation is a key driver of overgeneration RPS Calculator assumes 15% of gross load must be served by thermal generation in CAISO (includes dispatchable & cogeneration plants) Dynamic Value Analysis Step 1. Gas + Import Dispatch Based on 26,000 hourly observations from ; data from CAISO Daily Renewables Watch

12 Dynamic Value Analysis Step 1. Gas + Import Dispatch Minimum gas generation Renewables, hydro, cogen, and nuclear are subtracted from gross load Residual need is served by gas (and/or additional imports) At low penetrations, minimum thermal constraint is not binding

13 Dynamic Value Analysis Step 1. Gas + Import Dispatch Also identifies renewable curtailment Minimum gas generation As additional renewable generation is added to the system, the shape of the net load changes At high penetrations, minimum thermal constraint becomes binding, implying curtailment/overgen

14 Dynamic Value Analysis Step 2. Market Heat Rate Function Thermal “supply curve” developed based on CPUC LTPP assumptions & TEPPC plant heat rates: Stack evolves over time as plants are added & removed (also based on LTPP): CCGTs CTs OTC retirements

15 Dynamic Value Analysis Step 3. Hourly Operational Value In today’s operations, hourly renewable energy value is driven by the load shape –Resources that generate on-peak have higher energy values Example is illustrative of calculator functionality and is not a model result Highest value coincides with summer peak

16 Dynamic Value Analysis Step 3. Hourly Operational Value 16 By 2020, incremental hourly renewable energy value will be impacted by both the load and renewable output Resources with highest production value generate in hours of peak net load [load-renewables], rather than peak load Example is illustrative of calculator functionality and is not a model result Highest value occurs as solar production wanes Increase in gas/CO2 prices drives higher energy value

17 Dynamic Value Analysis Step 3. Hourly Operational Value 17 By 2030, incremental hourly energy value is zero in many hours if solar procurement dominates Production valuation methodology identifies hours of curtailment Example is illustrative of calculator functionality and is not a model result Value drops to zero during periods of overgeneration

18 Dynamic Value Analysis Step 4. Average Energy Value Energy value for each category of resource is calculated as the product of the marginal energy value and the resource’s production profile Because of changes to net load shape, values assigned to different resources evolve with the creation of a portfolio

19 Declining Energy Value As the net load peak shifts to later in the day: Operational value for on-peak resources tend to decrease Operational value for off-peak resources increases at a stable rate Value begins to decline due to coincidence of solar with overgeneration

20 Renewable Overgeneration  This method assumes that incremental renewables provide zero operational value in hours in which curtailment events occur  Additionally, curtailed generation is assumed not to contribute to RPS requirements, which increases the cost per MWh of procurement  When curtailment events occur, the MWh-delivered by incremental resources will be less than the MWh-available  The effect of renewable overgeneration is expressed in the RPS Calculator as a multiple on the net levelized cost  Both costs and benefits calculated on a $/MWh-available basis  Net levelized costs must be scaled up by: [MWh-available]/[MWh-delivered] = 1/(1-[marginal overgeneration])

21 RPS Calculator Guide The parameters that affect Energy Value can be found on the following tabs: –Generators: list of non-renewable generators in the CAISO and/or contracted to CAISO loads Includes capacity & heat rate assumptions for each thermal plant Aligned with LTPP –Dispatch_Curve: development of year-by-year thermal resource supply curve based on ‘Generators’ list –Energy: calculation of average net load and marginal cost of generation in each month-hour –Valuation: calculation of technology-specific energy value ($/MWh) and overgeneration (%) used in resource screening and selection process


Download ppt "ENERGY VALUE. Summary  Operational Value is a primary component in the Net Market Value (NMV) calculation used to rank competing resources in the RPS."

Similar presentations


Ads by Google