Transcript Presentation - Northwest Power & Conservation Council

Systems Analysis Advisory
Committee (SAAC)
Thursday, December 19, 2002
Michael Schilmoeller
John Fazio
1
Last Agenda
• Approval of the Oct 24 meeting minutes
• Review and questions from the last meeting
– Representation of dispatchable resources in the portfolio
model
– Metrics
• Representations in the portfolio model
– Price responsive demand
– Renewables and conservation
• Hydro (worksheet function, sustained peaking)
• Loads (HELM model, Terry Morlan’s DSI model)
• Natural gas prices (description of processes)
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Northwest Power Planning Council
Today’s Agenda
• Approval of the Nov 22 meeting minutes
• Review and questions from the last meeting
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Dispatchable plants (Beaver)
Price responsive demand
Renewables and conservation
Hydro
Loads
Representation of Transmission Reliability
Representation of Resource Diversity
Influence Diagram of Effects
Statistical Results for
– Natural gas prices, electricity prices, load, temperature, aluminum
prices, hydro, transmission congestion
– Correlations among these
3
Northwest Power Planning Council
Today’s Agenda
• Approval of the Nov 22 meeting minutes
• Review and questions from the last meeting
–
–
–
–
–
•
•
•
•
Dispatchable plants (Beaver)
Price responsive demand
Renewables and conservation
Hydro
Loads
Representation of Transmission Reliability
Representation of Resource Diversity
Influence Diagram of Effects
Statistical Results for
– Natural gas prices, electricity prices, load, temperature, aluminum
prices, hydro, transmission congestion
– Correlations among these
4
Northwest Power Planning Council
Today’s Agenda
• Approval of the Nov 22 meeting minutes
• Review and questions from the last meeting
–
–
–
–
–
•
•
•
•
Dispatchable plants (Beaver)
Price responsive demand
Renewables and conservation
Hydro
Loads
Representation of Transmission Reliability
Representation of Resource Diversity
Influence Diagram of Effects
Statistical Results for
– Natural gas prices, electricity prices, load, temperature, aluminum
prices, hydro, transmission congestion
– Correlations among these
5
Northwest Power Planning Council
Plan Issues
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incentives for generation capacity
price responsiveness of demand
sustained investment in efficiency
information for markets
fish operations and power
transmission and reliability
resource diversity
role of BPA
global change
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Northwest Power Planning Council
Review
Representation of dispatchables
• The monthly spread option model gives a
reasonable representation of expected
capacity factors (and hence value) of
resource options
• Given that the uncertainty in hourly prices
exceeds the expected variation, the detailed
information about hourly prices from any one
scenario tells us little about the expected
capacity factor and value of resource options
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Northwest Power Planning Council
Review
Price responsive demand
• Intended to represent short-term (1 day to 1 month)
load reduction, on- and off-peak, if the price is right
• Does not address longer term DSI load curtailment
(which is addressed later)
• Described by a supply curve
• Energy available represented as special continuous
function of price
– Zero variable cost, but some fixed cost
• Supply curve developed by Ken Corum
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Northwest Power Planning Council
Review
Conservation & Renewables
• Represent as non-dispatchable energy
• Supply curve for conservation developed by Tom
Eckman
• Renewables cost and operating characteristics
assembled by Jeff King
• Credit and availability advantages can be valued by
adding these uncertainties to alternatives, such as
contracts
• Modularity benefits require a new approach
• Example of Sustained Orderly Development (SOD)
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Northwest Power Planning Council
Review
wholesale electricity market
“Real Options”
minimum restart period
minimum shut-down period
evalulation phase
aluminum-elec
price spread
expected price trend
evalulation phase
time
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Northwest Power Planning Council
Review
Loads
• Non-DSI Loads
– Calibrate with data from NWPP
– Short-term uncertainty driven by random
temperatures (HELM)
– Long term uncertainty from Terry Morlan’s
work
• DSI Loads
– Terry Morlan’s aluminum industry model
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Northwest Power Planning Council
Review
Hydrogeneration
• Excel Add-in has 50-year record
Demonstrate:
– Parameters to pull out different data
– Use as random draw & correlation with other
assumptions
– Use of function to pull out specific year
• Reflects 10-hour sustained peaking capability
from the trapazoidal approximation studies
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Northwest Power Planning Council
Review
Today’s Agenda
• Approval of the Nov 22 meeting minutes
• Review and questions from the last meeting
–
–
–
–
–
•
•
•
•
Dispatchable plants (Beaver)
Price responsive demand
Renewables and conservation
Hydro
Loads
Representation of Transmission Reliability
Representation of Resource Diversity
Influence Diagram of Effects
Statistical Results for
– Natural gas prices, electricity prices, load, temperature, aluminum
prices, hydro, transmission congestion
– Correlations among these
13
Northwest Power Planning Council
Transmission Reliability
• To Show: The economic consequences of
transmission congestion can be captured with
the portfolio model
• The likelihood of congestion is related to
other variables we are considering in the
model
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Northwest Power Planning Council
Transmission Reliability
Transmission Reliability
• The portfolio model is not a reliability model
or a transmission flow model
• We will rely on Genesys and primary data to
provide insight into conditions when
congestion is likely to occur
• For transmission flow information, we will rely
on expert opinion. The Council currently has
no transmission flow model.
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Northwest Power Planning Council
Transmission Reliability
Transmission Reliability
• Begin with a
common
representation of
the uncongested
economic
transport of energy
(e.g., Aurora,
Henwood’s
Prosym)
• Simple model: no
losses or variable
wheeling charges
Native
Net
*
*
Net
Native
*
Native
Net
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Northwest Power Planning Council
Transmission Reliability
Unconstrained Case
• Given resource
stacks in each
area, the flows
and prices are
determined by
total native
loads, and all
prices are the
same.
Native
Net
*
*
Net
Native
*
Native
Net
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Northwest Power Planning Council
Transmission Reliability
Constrained Case
• To get some
constraint, we
assume the native
load in one region
increases a lot
• Transmission lines
are filled to their
maximum capacity
• Higher native load
means higher net
load
• Prices disconnect
Native
Net
*
*
Net
Native
*
Native
Net
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Northwest Power Planning Council
Transmission Reliability
Constrained Case
• In the constrained
case, the marginal
value of transmission is
the difference in price
between areas of price
difference.
• Equivalently, the
cumulative value of
transmission is the
difference in costs to
meet load, with and
without the congestion.
Native
Net
*
*
Net
Native
*
Native
Net
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Northwest Power Planning Council
Transmission Reliability
Statistical Representation
• In these situations, cause and effect is clear.
The native loads drive prices. When the
system is uncongested, prices in all regions
are the same. When the system is
congested, higher demand in some areas
will result in the dispatch of more costly
resources, resulting in higher prices for the
high demand area than for other areas.
• Statistics does not care about causality. It
deals with relationships among the values.
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Northwest Power Planning Council
Transmission Reliability
Statistical Representation
• If the prices are all equal, the transmission system is
uncongested. We know exactly which resources are
on the margin in each area and consequently what
each net load is. (If we know the native load, we can
also calculate the transmission flows.)
• If the prices are not equal, the transmission system
is congested. We know exactly which resources are
on the margin in each area and consequently what
each net load is. Since the transmission flows are at
their maximum capability, we know what native loads
are.
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Northwest Power Planning Council
Transmission Reliability
Constrained Case
• The same information
can be obtained either
with information about
the native loads or the
native prices.
• The value of improved
transmission reliability,
of course, will also be
the same.
Native
Net
*
*
Net
Native
*
Native
Net
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Northwest Power Planning Council
Transmission Reliability
Conclusions about
Transmission Reliability
• Market prices in regions, in particular the differences
among prices, will give a “dual” representation of the
state of the system.
• To predict when prices between regions are likely to
be different (when congestion is likely to occur), we
need statistical information relating congestion to
other variables, such as temperatures or loads.
• Transmission congestion can then be modelled
using a distribution of price differences that are
correlated with the other variables.
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Northwest Power Planning Council
Transmission Reliability
Today’s Agenda
• Approval of the Nov 22 meeting minutes
• Review and questions from the last meeting
–
–
–
–
–
•
•
•
•
Dispatchable plants (Beaver)
Price responsive demand
Renewables and conservation
Hydro
Loads
Representation of Transmission Reliability
Representation of Resource Diversity
Influence Diagram of Effects
Statistical Results for
– Natural gas prices, electricity prices, load, temperature, aluminum
prices, hydro, transmission congestion
– Correlations among these
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Northwest Power Planning Council
Resource Diversity
• Benefits of resource diversity
– Enhanced reliability
• ensemble forced outage rate
• not susceptible to transmission congestion
– Depending on the technology, some diversification
away from other, more dominant technologies
– Distribution system advantages
• Voltage support
• Lower losses
• Delayed distribution system expansion costs
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Northwest Power Planning Council
Resource Diversity
Benefits of resource diversity
• Some benefits may be addressed as fixed cost adjustments
– Voltage support (displacement of turbine capacity or reactive
power elements)
– Delayed distribution system expansion costs (displacement of
comparable quantities of transforms)
• Lower losses benefit may be modelled by systematic modification
to loads or an adjustment to the unit’s capacity
• The reliability enhancement related to having resources closer to
the load may be modelled in the same way that we model local
versus remote resources, i.e., by the price the resource sees
• The technology diversification is handled automatically
• Enhanced reliability due to ensemble forced outage rate may be
represented using a different binomial distribution for availability
(continued)
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Northwest Power Planning Council
Resource Diversity
Ensemble Forced Outage Rate
• At the user’s discretion, unit availability may be
modelled using a binomial distribution (assumed
independent of other stochastic variables)
Probability density
1.2
Hour’s Load
1
density
0.8
0.6
LOLP
0.4
0.2
0
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Hour's Load
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Northwest Power Planning Council
Resource Diversity
Conclusions of Resource
Diversity Representation
• We can expect that the economic
advantages of resource diversity can be
captured with the portfolio model
• We will rely on the Council’s Jeff King for
the operational and economic detailed
attributes of these technologies
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Northwest Power Planning Council
Resource Diversity
Today’s Agenda
• Approval of the Nov 22 meeting minutes
• Review and questions from the last meeting
–
–
–
–
–
•
•
•
•
Dispatchable plants (Beaver)
Price responsive demand
Renewables and conservation
Hydro
Loads
Representation of Transmission Reliability
Representation of Resource Diversity
Influence Diagram of Effects
Statistical Results for
– Natural gas prices, electricity prices, load, temperature, aluminum
prices, hydro, transmission congestion
– Correlations among these
29
Northwest Power Planning Council
Influence Diagram of Effects
• Objectives:
– To share views
and develop
some consensus
on the
significance and
relationships
among variable.
– To construct a
roadmap for
finding
relationships
among variables
Transmission
Congestion
Rescource
Outages
Hydro
Generation
Reserve
Margin
Market Prices
for Electricity
DSI Loads
Aluminum
Prices
Fuel Prices
Non-DSI
Loads
Temperature
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Northwest Power Planning Council
Influence Diagram
Rescource
Outages
Transmission
Congestion
Hydro
Generation
Reserve
Margin
Market Prices
for Electricity
DSI Loads
Aluminum
Prices
Fuel Prices
Non-DSI
Loads
Temperature
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Northwest Power Planning Council
Influence Diagram
Today’s Agenda
• Approval of the Nov 22 meeting minutes
• Review and questions from the last meeting
–
–
–
–
–
•
•
•
•
Dispatchable plants (Beaver)
Price responsive demand
Renewables and conservation
Hydro
Loads
Representation of Transmission Reliability
Representation of Resource Diversity
Influence Diagram of Effects
Statistical Results for
– Natural gas prices, electricity prices, load, temperature, aluminum
prices, hydro, transmission congestion
– Correlations among these
32
Northwest Power Planning Council
Statistics
• Statistics
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Historical Dailie
Distributions within the month, year
Reasons for variation over time
Correlation among electricity, load, temperature,
aluminum prices, hydro, natural gas prices
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Northwest Power Planning Council
Statistics
Statistics
• Daily correlation between gas prices and
electricity prices
• Daily correlation between hydro generation
and electricity prices
• Weaker correlation between gas prices and
California temperatures
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Northwest Power Planning Council
Statistics
Next Meeting
• Remaining work on statistics
• Issue: Incentives for new generation
• Review of risk management problems of
2000-2001
– What worked and what did not
• Initial optimization for Region, using all
mechanisms
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Northwest Power Planning Council
Background Slides
• These are intended primarily to answer
questions that come up
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Northwest Power Planning Council
Representation of dispatchables
• Oil
price
forecast
35
?
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25
20
History
Low
15
Medlo
Medium
10
Medhi
?
High
EIA02-R
5
EIA02-H
EIA902-L
0
8 Others
1990
1995
2000
2005
2010
2015
2020
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Northwest Power Planning Council
Representation of dispatchables
• NG
price
forecast
?
4.5
4
3.5
History
Low
2000$/MMBtu
3
Medlo
Medium
2.5
Medhi
High
2
EIA-Ref
?
1.5
EIA-Low
EIA-High
1
DRI-WEFA
GRI
0.5
CEC
ICF
0
1995
2000
2005
2010
2015
2020
2025
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Northwest Power Planning Council
Electricity Markets
• By its nature, distinct markets for electricity
exists for different locations and times
• Variation vs
Volatility
• The prices
in the figure at
the right have
NO volatility
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Northwest Power Planning Council
Terms and Concepts
Mid-Columbia price forecast
Average annual w/comparisons
?
$55
$50
Price (2000$/MWh)
$45
$40
$35
$30
$25
$20
?
Current Trends Hi Shape (092702)
$15
5th Plan corrected transfer (062402).
$10
Adequacy & Reliability Study (Feb 2000)
$5
$0
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
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Northwest Power Planning Council
DSI Loads
$3,500
$3,250
$3,000
$2,750
$2,500
$2,250
$2,000
$1,750
$1,500
$1,250
$1,000
Cash
15-Month
Real Cash
Linear (Real Cash)
$0.80
$0.70
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89
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90
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91
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92
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93
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94
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95
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96
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97
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98
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99
20
00
20
01
20
02
US$/Tonne
LME Cash Aluminum Prices:
Daily 1989-2002
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Northwest Power Planning Council
Non-DSI Loads
Total Sales
Non-DSI
45000
97.5%
Average Megawatts
40000
35000
30000
25000
20000
97.5%
15000
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20
20
20
17
20
14
20
11
20
08
20
05
20
02
20
99
19
96
19
93
19
90
19
87
19
84
19
19
81
10000
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Northwest Power Planning Council
Natural Gas Prices
• Data from Gas Daily
• Statistics?
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Historical Dailies
Price processes
Distributions within the month, year
Future uncertainties (Terry)
Reasons for variation over time
Correlation with electricity, load, temperature,
aluminum prices, hydro
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Northwest Power Planning Council
Natural Gas Prices
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1. Mean Reversion - Vasicek Model
P(t+dt) - P(t) = Beta*(Alpha - P(t))*dt + Sigma*sqrt(dt)*N(0,1)
2. Mean reversion - CIR Model
P(t+dt) - P(t) = Beta*(Alpha - P(t))*dt + Sigma*Sqrt(P(t))*sqrt(dt)*N(0,1)
3. Geometric Brownian Motion - GBM
P(t+dt) - P(t) = Drift*P(t)*dt + Sigma*P(t)*sqrt(dt)*N(0,1)
4. Mean reversion - unrestricted
P(t+dt) - P(t) = Beta*(Alpha - P(t))*dt + Sigma*P(t)^Gamma*sqrt(dt)*N(0,1)
5. Jump-diffusion (Use the same time step for estimation and simulation - h doesn't
scale!!)
P(t+dt) = P(t)exp( Drift*dt + Sigma*sqrt(dt)*N(0,1)+Y*N(Drift_j,Sigma_j))
Y=1 with probability h and Y=0 with probability (1-h)
6. Brennan and Schwartz Model
P(t+dt) - P(t) = Beta*(Alpha - P(t))*dt + Sigma*P(t)*sqrt(dt)*N(0,1)
7. Mean reversion with jump-diffusion, Vasicek type diffusion
P(t+dt) - P(t) = Beta*(Alpha - P(t))*dt + Sigma*sqrt(dt)*N(0,1)+Y*N(Drift_j,Sigma_j)
Y=1 with probability h and Y=0 with probability (1-h)
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Northwest Power Planning Council
Natural Gas Prices
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8. Mean reversion with jump-diffusion, CIR type diffusion
P(t+dt) - P(t) = Beta*(Alpha - P(t))*dt +
P(t)^0.5*(Sigma*sqrt(dt)*N(0,1)+Y*N(Drift_j,Sigma_j))
Y=1 with probability h and Y=0 with probability (1-h)
9. Mean reversion with jump-diffusion, Brennan-Shcwartz type diffusion
P(t+dt) - P(t) = Beta*(Alpha - P(t))*dt +
P(t)*(Sigma*sqrt(dt)*N(0,1)+Y*N(Drift_j,Sigma_j))
Y=1 with probability h and Y=0 with probability (1-h)
10. Mean reversion with jump-diffusion, "Unrestricted" type diffusion
P(t+dt) - P(t) = Beta*(Alpha - P(t))*dt +
P(t)^gamma*(Sigma*sqrt(dt)*N(0,1)+Y*N(Drift_j,Sigma_j))
Y=1 with probability h and Y=0 with probability (1-h)
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Northwest Power Planning Council