Cost-Causation and Integration Cost
Analysis for Variable Generation
Michael Milligan, Ph.D.
National Renewable Energy
Laboratory
NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.
About this presentation
•  Information in this
presentation is taken
from “Cost-Causation
and Integration Cost
Analysis for Variable
Generation,” Milligan,
M.; Ela, E.; Hodge, B.
M.; Kirby, B.; Lew, D.;
Clark, C.; DeCesaro,
J.; Lynn, K.
•  http://www.nrel.gov/
docs/fy11osti/
51860.pdf
National Renewable Energy Laboratory
2
Innovation for Our Energy Future
Outline
•  Power system operation:
variability and uncertainty
•  Cost-causation and
integration tariffs
•  Thought experiments:
testing tariffs
•  Conclusions
National Renewable Energy Laboratory
3
Innovation for Our Energy Future
Time scale for power system operation
National Renewable Energy Laboratory
4
Innovation for Our Energy Future
Additional ramping/rangemore flexibility
10000
8000
MW
6000
4000
2000
0
800
Net load (load-wind)
Additional ramping needs with wind
Maximum/Minimum
Load
Peak Load
Ramp (MW/hour)
600
400
200
0
-200
-400
-600
-800
0
20
National Renewable Energy Laboratory
40
60
80
Hours (1 week)
5
100
120
140
160
Innovation for Our Energy Future
Integration costs: wind and solar
•
•
Wind and solar generation increase
the variability and uncertainty in
power systems operation
Solar and wind integration issues are
similar
–  Wind is becoming reasonably well
understood
–  Solar
•  PV has high potential for short-term
variability from cloud variations, but the
impact of large PV plants is largely
unknown because of limited experience
with small plants
•  CSP without storage has some thermal
inertia and is likely less variable than PV
•  CSP with storage is thought to be much
less of an integration challenge but still
unknown
•
•
Cycling efficiency
Are not unique to wind or solar
National Renewable Energy Laboratory
6
Innovation for Our Energy Future
Variability and Uncertainty
Variability: Wind and solar generator outputs vary on different 3me scales as the intensity of their energy sources (wind and sun) Uncertainty: Wind and solar genera3on cannot be predicted with perfect accuracy Variability Uncertainty 2500
CSP Actual
CSP Forecasted
20000
2000
15000
1500
MW
MW
25000
10000
1000
Wind Actual
5000
500
Forecasted Wind
0
0
0
6
12
18
24
Hours
30
36
42
0
48
6
12
18
24
Hours
30
36
42
48
Variability: load varies throughout the day, conven3onal genera3on can o=en stray from schedules Uncertainty: Con3ngencies are unexpected, load forecast errors are unexpected National Renewable Energy Laboratory
7
Innovation for Our Energy Future
Integration cost of wind and solar
•
•
Delta Market Value ($)
5
0
0
-5
-50
Daily flat energy block ($52.33/MWh)
Daily flat block difference $/MWh (right)
6-Hour flat energy block ($48.59/MWh)
6_Hour flat energy block difference $/MWh (right)
(Wind: $48.98/MWh)
40
-10
10
5
20
0
0
-20
-40
-5
-60
-80x10
3
-10
0
20
40
60
80
100
120
140
160
Related reports: Milligan, M.; Kirby, B. (2009). Calcula3ng Wind Integra3on Costs: Separa3ng Wind Energy Value from Integra3on Cost Impacts. 28 pp.; NREL Report No. TP-­‐550-­‐46275. hXp://www.nrel.gov/docs/fy09os3/46275.pdf Milligan, M.; Ela, E.; Lew, D.; Corbus, D.; Wan, Y. H. (2010). Advancing Wind Integra3on Study Methodologies: Implica3ons of Higher Levels of Wind. 50 pp.; NREL Report No. CP-­‐550-­‐48944. hXp://www.nrel.gov/docs/fy10os3/48944.pdf –  Do all AGC units follow the
signal?
–  Are there efficiency costs of
adding conventional
generators?
National Renewable Energy Laboratory
(Flat block value) - (wind value)
50
Delta Market Value ($)
•
Can it be measured?
If so, how is it defined?
What is the proper
benchmark unit?
How are cost and value
untangled?
What about units in one
region that economically
respond to needs in
another region?
Are there integration costs
for other units?
10
3
Over or Under-estimate of Wind Value ($/MWh)
•
•
•
100x10
8
Innovation for Our Energy Future
How are integration costs calculated?
•  Compare two (or more) alternative simulations of
the power system using production simulation/cost
models
–  With wind/solar
–  Without wind/solar
•  To provide an energy-equivalent basis, a
hypothetical unit is often chosen for the “without
wind/solar” case
•  This proxy resource may introduce unintended
consequences
•  It is natural to ask about integration costs, but
extremely difficult, if not impossible, to measure
them accurately
National Renewable Energy Laboratory
9
Innovation for Our Energy Future
Wind/Daily Block (MW)
The flat-block proxy resource distorts the value of the energy
6000
Flat block value - wind value
5000
4000
3000
2000
1000
0
10
200
5
Delta Market Value ($)
100
0
0
-100
-5
-200
-300x10
Wind Generation
Daily wind-equivalent energy block
Daily flat energy block $43.12/MWh
Daily flat block difference $1.06/MWh
6-Hour flat energy block $42.18/MWh
6-Hour flat energy block difference $0.11/MWh
(Wind: $42.06/MWh)
3
150
100
10
5
50
0
0
-50
-5
-100
-150x10
-10
3
-10
0
20
National Renewable Energy Laboratory
40
60
80
100
10
120
140
160
Average Over or Under-estimate of Wind Value ($/MWh)
300
Innovation for Our Energy Future
Total system costs or integration costs
•  Total operating costs are relatively easy to
calculate
•  Integration costs are difficult to calculate
correctly
•  Both of these are sensitive to assumptions
about the other parts of the power system
–  What is the mix of conventional generation?
–  What is the transmission build-out (if any)?
–  What are the institutional constraints?
–  Electrical footprint?
–  Do markets allow access to physical capability that
exists, or is this access constrained?
–  What will the power system look like in 20xx?
National Renewable Energy Laboratory
11
Innovation for Our Energy Future
Are there other sources of integration costs?
•  Contingency reserves
•  Conventional units may impose additional
variability and uncertainty that must be
managed
•  Interaction between generators in the economic
dispatch process can result in generator A
imposing a cost on generator B, even if both
units are “conventional”
•  Gas purchase/nomination requirements
National Renewable Energy Laboratory
12
Innovation for Our Energy Future
Contingency reserves
•  Specific rules vary, but the contingency reserve
is typically set by the largest unit in the pool.
•  Often the specific reserve allocation is based on
load ratio share or other similar metric
•  When the largest unit is replaced by a still larger
unit, contingency reserve obligations increase
•  à if I am a generation owner/operator, I will
find my contingency reserve obligation may
increase independently of any action I have
taken (or not taken)
National Renewable Energy Laboratory
13
Innovation for Our Energy Future
Contingency reserve costs could be allocated based on generators’
contribution to contingency reserve activation…but this is not done
National Renewable Energy Laboratory
14
Innovation for Our Energy Future
Conventional units may impose regulation costs
Two similar coal fired generators: both are trying to provide regula;on but the upper generator is following dispatch instruc;ons fairly well providing regula;on while the lower generator is not and is imposing a regula;on burden on the power system.
National Renewable Energy Laboratory
15
Innovation for Our Energy Future
New, low-cost base-load may cause
integration costs
1. Coal is operated as base-load unit
2. With new wind generation
added, gas and coal cycling
increase and capacity factors
decline
3. Instead of adding wind, a new,
cheap base-load technology is
introduced. Coal cycling
increases; gas is nearly pushed
out. Both coal and gas have lower
capacity factors.
National Renewable Energy Laboratory
16
Innovation for Our Energy Future
Gas nominations
•  Day-ahead nominations
•  Week-end (or holiday
weekends) can pose
challenges because of
long forecast horizons
and uncertainty, and
can increase costs and/
or limit flexible use of
gas generation
•  This is an institutional
issue and is unrelated
to the capability of the
gas generation
National Renewable Energy Laboratory
17
Innovation for Our Energy Future
Principles of Cost-causation: 1
•  Maintaining reliability is critical
•  If tariffs are based on costs, they provide
transparency and can induce desired behavior
National Renewable Energy Laboratory
18
Innovation for Our Energy Future
Principles of Cost-causation: 2
•  Individuals who cause costs should pay
•  Individuals who mitigate (reduce, eliminate)
costs should either incur a lower cost, or be
paid for helpful actions
•  Complex systems like electric grids product
both joint produces and joint costs that must be
allocated among the users of the system
•  Joint costs can be recovered base on the
principle of “relative use.”
National Renewable Energy Laboratory
19
Innovation for Our Energy Future
Principles of Cost-causation: 3
•  Tariffs should not collect revenue if no cost is
incurred
National Renewable Energy Laboratory
20
Innovation for Our Energy Future
Principles of Cost-causation: 4
•  Tariffs should be based on the physical
characteristics of the power system
•  Aggregate load and generation must be
balanced
•  It is un-necessary and usually quite costly to
balance individual loads or resources, and this
is inconsistent with the way the power system is
operated
National Renewable Energy Laboratory
21
Innovation for Our Energy Future
Principles of Cost-causation: 5
•  Tariffs should result in an efficient allocation of
resources
•  This can be tested: is there another way that the
required services can be supplied at less cost?
Or is there another way that the system can be
planned or operated at less cost?
•  If either of these are true, resources are not
efficiently allocated
National Renewable Energy Laboratory
22
Innovation for Our Energy Future
Other characteristics of tariffs
•  Vertical consistency:
individuals who impose higher
costs should be assessed
more than an individual who
imposes lower (or no) cost
•  Horizontal consistency:
individuals who cause similar
(identical) costs should be
assessed similar (identical)
costs
National Renewable Energy Laboratory
23
A: High cost
B: Low cost
A
B
A and B have similar
cost contributions
Innovation for Our Energy Future
The sum of all parts physically cannot exceed
the whole
•  Methods that separate
regulation, following, uncertainty
for the analysis must follow the
principle of re-composition.
•  à The sum of
–  Regulation
–  Following
–  Uncertainty
•  Components must combine so
that they do not exceed the total
variability + uncertainty…
•  Sum of all parts of the tariff
revenue cannot exceed total
costs
National Renewable Energy Laboratory
24
Innovation for Our Energy Future
Thought experiments: How can tariffs be
tested to see how they behave?
National Renewable Energy Laboratory
25
Innovation for Our Energy Future
Thought experiment #1: Block schedules and
regulation
Useful to test the behavior of proposed, or actual, tariffs
How does the tariff treat perfect following of a volatile
schedule?
1600
350
29000
1400
1400
250
27000
1200
1200
150
1000
50
800
-50
600
-150
Load
25000
1000
23000
800
Block schedule
21000
Load
Pure block schedule
19000
600
Generation schedule (MW)
1600
400
Pure Block Schedule
400
Generation ramp rate (MW/min)
31000
Scheduled Generation (MW)
Total Load (MW)
•
•
-250
Generation ramp rate
17000
00:00
200
03:00
06:00
09:00
12:00
15:00
18:00
21:00
200
00:00
00:00
Time
National Renewable Energy Laboratory
-350
03:00
06:00
09:00
12:00
15:00
18:00
21:00
00:00
Time
26
Innovation for Our Energy Future
Thought experiment #2: Ramping
•
1600
35
29000
1400
1400
25
27000
1200
1200
15
1000
5
800
-5
600
-15
Load
25000
1000
23000
800
Load
Ramped block schedule
Block schedule
21000
19000
600
Generation schedule (MW)
1600
400
Ramped Block Schedule
400
Generation ramp rate (MW/min)
31000
Scheduled Generation (MW)
Total Load (MW)
•
Should a tariff quantify peak-to-peak movements of generator
or load?
Ramping the block schedule does not impact the energy
delivery or forecast accuracy but reduces regulation
requirements.
-25
Generation ramp rate
17000
00:00
200
03:00
06:00
09:00
12:00
15:00
18:00
21:00
200
00:00
00:00
Time
National Renewable Energy Laboratory
-35
03:00
06:00
09:00
12:00
15:00
18:00
21:00
00:00
Time
27
Innovation for Our Energy Future
Thought experiment #3: Ramp metric
•
•
•
•
Some approaches to assessing ramping needs (or supply) may not
produce desired result
Red: regulation, lots of small movements
Green: longer time interval but essentially energy-neutral
Blue: likely the most challenging
•
If considered in isolation, does not capture what the system must do
60
50
MW
40
30
20
10
0
0
10
20
30
40
50
60
Minutes
National Renewable Energy Laboratory
28
Innovation for Our Energy Future
Thought experiment #4
•  Equal but opposite behavior is benign to the
power system operator
•  Even though #4 may not be realistic, it can
identify tariffs that over-charge based on this
principle
30000
1500
System Load
Wind Generator
Mirror Wind Generator
20000
1000
15000
500
10000
00:00
Generation (MW)
Total Load (MW)
25000
2000
0
03:00
06:00
09:00
12:00
15:00
18:00
21:00
00:00
Time
National Renewable Energy Laboratory
29
Innovation for Our Energy Future
Thought experiment #5
•  How does the tariff assess beneficial movement?
•  For example, would both coal plants be paid the
same amount?
National Renewable Energy Laboratory
30
Innovation for Our Energy Future
Other considerations
•  Does the tariff recognize all cost-causers?
•  Does the tariff recognize all helpful actions
(intended or otherwise)?
National Renewable Energy Laboratory
31
Innovation for Our Energy Future
Common errors in integration analysis
•  Double-counting
•  Assuming fixed schedules/resources that may
be variables in the long-run
•  Balancing individual actors
•  Scaling
•  How are wind/solar forecasts simulated?
•  Excessive or unknown implied CPS
performance
•  Assumptions regarding replacement power
sources and costs
National Renewable Energy Laboratory
32
Innovation for Our Energy Future
Common errors in integration analysis
•  Constant reserves (wind and solar generation
cannot be less than zero, nor greater than
rated)
•  Failure to release following (or related reserves)
when they are called on
•  Excessive lead times prior to the dispatch
period
•  Assuming specific fleet characteristics (limited
turn-down, for example) for future scenarios
•  Generally – nearly any aspect of the system
may change in the future. Assuming all else
constant may drive results
National Renewable Energy Laboratory
33
Innovation for Our Energy Future
Accommodating Wind and Solar Integration
Large BA
 Geographically Dispersed Wind and Solar
 Wind/Solar Forecasting Effectively Integrated Into System Operations
 Sub-Hourly Energy Markets
 Fast Access to Neighboring Markets
 NonSpinning and 30 Minute Reserves for Wind/Solar Event Response
 Regional Transmission Planning For Economics and Reliability
 Robust Electrical Grid
 More Flexible Transmission Service
 Flexibility in Generation
 Responsive Load
 Overall

Example Utility Structures
10
8
7
10
7
2
7
6
7
7
3
7
Large RTO with spot markets
6
6
6
3
3
2
6
4
7
2
2
4
Smaller ISO
1
3
2
1
2
1
2
3
2
2
2
2
Interior west & upper Midwest (non-MISO)
7
6
6
2
2
2
5
4
2
5
2
4
Large vertically integrated utility
1
3
2
1
2
1
2
4
2
2
2
2
Smaller Vertically Integrated Local Utility
1
1
1
1
1
1
1
1
1
8
Unconstrained hydro system
3
Heavily fish constrained hydro system
1
1
11
Weightings Factors
Adapted from Milligan, M.; Kirby, B.; Gramlich, R.; Goggin, M. (2009). Impact of Electric Industry Structure on High Wind Penetra3on Poten3al. 31 pp.; NREL Report No. TP-­‐550-­‐46273. hXp://www.nrel.gov/docs/fy09os3/
46273.pdf National Renewable Energy Laboratory
34
Innovation for Our Energy Future
Conclusions
•  There is no universal agreement on integration cost
methods, or whether these costs are measureable
•  Integration costs are part of normal power systems
operation, beyond wind/solar
–  Conventional units may impose integration costs
–  Performance-based tariffs are more appropriate than
technology-based tariffs, assuming other factors are
properly considered
•  There are many potential non-(wind/solar) cases
that may be good base cases
•  High penetrations of wind/solar will have an impact
on the conventional plant mix and institutional
practice
National Renewable Energy Laboratory
35
Innovation for Our Energy Future
Questions?
36