ENERGY VALUE. Summary Operational Value is a primary component in the Net Market Value (NMV)...

ENERGY VALUE

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

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 2.0 – 5.0

Energy value attributed to renewable resources based on static assumptions

Value based only on snapshot in 2020

Energy Value

4

Energy value intended to capture the direct impact of renewable generation on system operations

In Version 2.0-5.0, 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

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

Goals for New Methodology

6

Model Functionality Versions 1-5 Version 6

Differentiate energy value between renewable resources

Capture renewable portfolio effects Capture declining energy value with resource saturation Account for renewable overgeneration

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

CCGT

CTST

Varia

ble

Cost

of G

ener

ation

($

/MW

h)

Megawatts

Figure is illustrative

only

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

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

Dynamic Value AnalysisStep 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

• 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)

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0% 20% 40% 60% 80% 100%

Perc

ent o

f Loa

d Se

rved

by

Ther

mal

Percent of Observations


99th Percentile:

15%

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5%

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30%

90% 95% 100%

99th Percentile:

15%

0%

5%

10%

15%

20%

25%

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90% 95% 100%

Based on 26,000 hourly observations from 2010-2013; data from CAISO Daily Renewables Watch

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

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2012

Cogeneration

Gas


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2012

Renewables

Hydro

Cogeneration

Nuclear


Minimum gas generationRenewables, 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


Also identifies renewable curtailment


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2030

Cogeneration

Gas


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Renewables

Hydro

Cogeneration

Nuclear

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

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Btu/

MW

h

GW

2030 Thermal Stack

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MM

Btu/

MW

h

GW

2020 Thermal Stack

0.02.04.06.08.0

10.012.014.016.018.0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

MM

Btu/

MW

h

GW

2012 Thermal Stack

Dynamic Value AnalysisStep 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

Dynamic Value AnalysisStep 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


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Mar

gina

l Ene

rgy

Valu

e ($

/MW

h)

2012

Highest value coincides with summer peak


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• 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



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/MW

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2012

2020

Highest value occurs as solar production wanes

Increase in gas/CO2 prices drives higher energy value


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• By 2030, incremental hourly energy value is zero in many hours if solar procurement dominates

• Production valuation methodology identifies hours of curtailment



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/MW

h)

2012

2020

2030

Value drops to zero during periods of overgeneration

Dynamic Value AnalysisStep 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


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rgy

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2012

2020

Jan Feb Mar AprMay Jun Jul Aug Sep Oct Nov Dec

Prod

uctio

n Pr

ofile

Utility Scale Solar PVJan Feb Mar AprMay Jun Jul Aug Sep Oct Nov Dec

Prod

uctio

n Pr

ofile

Wind

$46

$64

$45

$66

$0$10$20$30$40$50$60$70

2012 2020

$/M

Wh

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

Utility-Scale Solar PV

Wind

$0

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$70

$80

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

Aver

age

Prod

uctio

n Va

lue

($/M

Wh)

Value begins to decline due to coincidence of solar with

overgeneration

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])

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

ENERGY VALUE. Summary Operational Value is a primary component in the Net Market Value (NMV)...

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