Electric Power Planning for Flexibility

Electric Power Planning for Flexibility: Integrating Unit Commitment Constraints into Long-term planning for Renewables

Bryan Palmintier Massachusetts Institute of Technology

EE500E Energy & Environment Seminar University of Washington Oct 13, 2011

Overview o  Background

o  Renewable Impacts o  Flexibility & Unit Commitment o  Planning

o  UC + Planning… is it worth it? n  Infeasible Mixes n  Wrong policy (CO2 price) conclusions

o  A way to do it n  Full system size, full 8760 n  Much, much, faster

2 Palmintier, UW EE500E Seminar 2011-10-13

The Electric Power System Today Uncertainties: o  Fuel Prices o  Load Growth o  Policy Simplified by: o  Predictable

Load Cycles o Decoupled

Dynamics

Palmintier, UW EE500E Seminar 2011-10-13 3

Icon Image Credits: PT: Powered Templates UniS: science.uniserve.edu.au/school/sciweek/2005/ RMI: Rocky Mountain Institute

Advanced Electric Power System Uncertainties: o  Fuel Prices, Load

Growth, Policy o  Renewable Output o  Demand Participation o  Tech. Development

Complicated by: o Uncertain

Load Cycles o Coupled

Dynamics


Icon Image Credits: PT: Powered Templates UniS: science.uniserve.edu.au/school/sciweek/2005/ RMI: Rocky Mountain Institute

Renewables Impacts o Uncertainty o Variability

o More Operational Flexibility Required


!"

#"

$!"

$#"

%!"

%#"

&!"

&#"

'!"

'#"

#!"

!"#$%&'(

)*&

+",%-.&/"%&0&#$$1&'23%45*&

()*+"

,-."()*+"

Power system Flexibility drivers o  Generator Operating Constraints

n  Minimum output level n  Ramp Rates n  Startup costs & cycling limits

o  Operating Reserve Requirements n  Function of Wind Forecast

o  Policy/Market n  Wind priority, Must Run n  Timing

o  (And others)


Flexibility Comparison

Technology Impact on Operations Flexibility

Wind Bad Storage Good Demand Response Good NG (+ CCS?) Good (OK?) Coal (+ CCS?) Bad (Worse?) Nuclear Bad


Electric Power Model Types


Modeling Flexibility: Unit Commitment o  Generator Operating Constraints




o  (And others)


Modeling Flexibility: Unit Commitment o  Generator Operating Constraints




o  (And others)


Difficult Optimization Problem: Mixed-Integer (Combinatorial) Lots of Constraints Long run times even for short time periods

Planning – Load Duration Curve


!"

#!"

$!"

%!"

&!"

'!"

(!"

)!"

*!"

+!"

#"#'!"

$++"

&&*"

'+)"

)&("

*+'"

#!&&"

##+%"

#%&$"

#&+#"

#(&!"

#)*+"

#+%*"

$!*)"

$$%("

$%*'"

$'%&"

$(*%"

$*%$"

$+*#"

%#%!"

%$)+"

%&$*"

%'))"

%)$("

%*)'"

&!$&"

&#)%"

&%$$"

&&)#"

&($!"

&)(+"

&+#*"

'!()"

'$#("

'%('"

''#&"

'((%"

'*#$"

'+(#"

(##!"

($'+"

(&!*"

('')"

()!("

(*''"

)!!&"

)#'%"

)%!$"

)&'#"

)(!!"

))&+"

)*+*"

*!&)"

*#+("

*%&'"

*&+&"

*(&%"

!"#$%&'()*(

)&+,-.&

/01'2&3445&6&347&,%"#)8&6&347&0!9&+:;<&1'3.&&

,-./0"

1234"

,-.//-0"

/567"

,897:6;"

Planning – Load Duration Curve


!"

#!"

$!"

%!"

&!"

'!"

(!"

)!"

*!"

+!"

#"#'!"

$++"

&&*"

'+)"

)&("

*+'"

#!&&"

##+%"

#%&$"

#&+#"

#(&!"

#)*+"

#+%*"

$!*)"

$$%("

$%*'"

$'%&"

$(*%"

$*%$"

$+*#"

%#%!"

%$)+"

%&$*"

%'))"

%)$("

%*)'"

&!$&"

&#)%"

&%$$"

&&)#"

&($!"

&)(+"

&+#*"

'!()"

'$#("

'%('"

''#&"

'((%"

'*#$"

'+(#"

(##!"

($'+"

(&!*"

('')"

()!("

(*''"

)!!&"

)#'%"

)%!$"

)&'#"

)(!!"

))&+"

)*+*"

*!&)"

*#+("

*%&'"

*&+&"

*(&%"

!"#$%&'()*(

)&+,-.&

/$)&0"12&3(%14"5&678'9&:;;<&=&:;>&,%"#)?&=&:;>&7!@&+ABC&8':.&&

,-./"

01234"

3567"

0123314"

0897:6;"

!"

#!"

$!"

%!"

&!"

'!"

(!"

)!"

*!"

+!"

#"#'!"

$++"

&&*"

'+)"

)&("

*+'"

#!&&"

##+%"

#%&$"

#&+#"

#(&!"

#)*+"

#+%*"

$!*)"

$$%("

$%*'"

$'%&"

$(*%"

$*%$"

$+*#"

%#%!"

%$)+"

%&$*"

%'))"

%)$("

%*)'"

&!$&"

&#)%"

&%$$"

&&)#"

&($!"

&)(+"

&+#*"

'!()"

'$#("

'%('"

''#&"

'((%"

'*#$"

'+(#"

(##!"

($'+"

(&!*"

('')"

()!("

(*''"

)!!&"

)#'%"

)%!$"

)&'#"

)(!!"

))&+"

)*+*"

*!&)"

*#+("

*%&'"

*&+&"

*(&%"

!"#$%&'()*(

)&+,-.&

/01'2&3445&6&347&,%"#)8&6&347&0!9&+:;<&1'3.&&

,-./0"

1234"

,-.//-0"

/567"

,897:6;"

Planning – Screening Curve


!"

#!"

$!"

%!"

&!"

'!"

(!"

)!"

*!"

+!"

#"#'!"

$++"

&&*"

'+)"

)&("

*+'"

#!&&"

##+%"

#%&$"

#&+#"

#(&!"

#)*+"

#+%*"

$!*)"

$$%("

$%*'"

$'%&"

$(*%"

$*%$"

$+*#"

%#%!"

%$)+"

%&$*"

%'))"

%)$("

%*)'"

&!$&"

&#)%"

&%$$"

&&)#"

&($!"

&)(+"

&+#*"

'!()"

'$#("

'%('"

''#&"

'((%"

'*#$"

'+(#"

(##!"

($'+"

(&!*"

('')"

()!("

(*''"

)!!&"

)#'%"

)%!$"

)&'#"

)(!!"

))&+"

)*+*"

*!&)"

*#+("

*%&'"

*&+&"

*(&%"

!"#$%&'()*(

)&+,-.&

/$)&0"12&3(%14"5&678'9&:;;<&=&:;>&,%"#)?&=&:;>&7!@&+ABC&8':.&&

,-./"

01234"

3567"

0123314"

0897:6;"

Run Time

Tota

l Cos

t

Impact of Detailed Operations


!"

#!"

$!"

%!"

&!"

'!"

(!"

)!"

*!"

+!"

#"#'!"

$++"

&&*"

'+)"

)&("

*+'"

#!&&"

##+%"

#%&$"

#&+#"

#(&!"

#)*+"

#+%*"

$!*)"

$$%("

$%*'"

$'%&"

$(*%"

$*%$"

$+*#"

%#%!"

%$)+"

%&$*"

%'))"

%)$("

%*)'"

&!$&"

&#)%"

&%$$"

&&)#"

&($!"

&)(+"

&+#*"

'!()"

'$#("

'%('"

''#&"

'((%"

'*#$"

'+(#"

(##!"

($'+"

(&!*"

('')"

()!("

(*''"

)!!&"

)#'%"

)%!$"

)&'#"

)(!!"

))&+"

)*+*"

*!&)"

*#+("

*%&'"

*&+&"

*(&%"

!"#$%&'()*(

)&+,-.&

/$)&0"12&3(%14"5&678'9&:;;<&=&:;>&,%"#)?&=&:;>&7!@&+ABC&8':.&&

,-./"

01234"

3567"

0123314"

0897:6;"

!"

#!"

$!"

%!"

&!"

'!"

(!"

)!"

*!"

+!"

#"#'!"

$++"

&&*"

'+)"

)&("

*+'"

#!&&"

##+%"

#%&$"

#&+#"

#(&!"

#)*+"

#+%*"

$!*)"

$$%("

$%*'"

$'%&"

$(*%"

$*%$"

$+*#"

%#%!"

%$)+"

%&$*"

%'))"

%)$("

%*)'"

&!$&"

&#)%"

&%$$"

&&)#"

&($!"

&)(+"

&+#*"

'!()"

'$#("

'%('"

''#&"

'((%"

'*#$"

'+(#"

(##!"

($'+"

(&!*"

('')"

()!("

(*''"

)!!&"

)#'%"

)%!$"

)&'#"

)(!!"

))&+"

)*+*"

*!&)"

*#+("

*%&'"

*&+&"

*(&%"

!"#$%&'()*(

)&+,-.&

/$)&0"12&3(%14"5&678'9&:;;<&=&:;>&,%"#)?&=&:;>&7!@&+ABC&8':.&&

,-./"

01234"

3567"

0123314"

0897:6;"

Planning Today

o  Power Systems n  2 iterative stages:

1.  Screening for Adequacy 2.  Scenario Analysis

o  Policy Makers n  Use screening tools directly

o  Today’s screening tools n  Simple operations n  Can’t assess flexibility


Simple operations models assume perfect flexibility

!"

#!"

$!"

%!"

&!"

'!"

(!"

)!"

!"#$%&'(

)*&

+",%-.&/"%&0&)$$1&'2$34$56$%*&

*+,-"

./01234"

.2*0./056"

./076"

./055/6"

.2*0./055/6"

893:"

.2*0593:"

.;8:23<"

.2*0.;8:23<"


ERCOT 2009 + 20% growth with 20% RPS + $75/ton CO2

Merit order economic dispatch

Unit commitment models capture key technical constraints

!"

#!"

$!"

%!"

&!"

'!"

(!"

)!"

!"#$%&'(

)*&

+",%-.&/"%&0&)$$1&'2$34$56$%*&

*+,-"

./01234"

.2*0./056"

./076"

./055/6"

.2*0./055/6"

893:"

.2*0593:"

.;8:23<"

.2*0.;8:23<"


Same Installed Generators

ERCOT 2009 + 20% growth with 20% RPS + $75/ton CO2

Unit Commitment Operations

2 1 3 4 5

New Approaches

o  Flexibility: an additional iterative step? 1.  Screening for Adequacy 2.  Flexibility assessment 3.  Scenario Analysis

o Our approach: combine Screening & Flexibility assessment into one tool


New Approaches

o  Flexibility: an additional iterative step? 1.  Screening for Adequacy 2.  Flexibility assessment 3.  Scenario Analysis

o Our approach: combine Screening & Flexibility assessment into one tool


Discrete Variables

Combinatorial Explosion

i.e. Hard

Is it Worth it?

$0/ton C02e Cost (20% RPS)


8760 Hour. 195 existing + >100 Possible new Units. Simple = Economic Dispatch with baseload minimum. Detailed = Clustered Integer Unit Commitment including Ramping, Flexibility Reserves as a function of Wind, Startup Costs & Limits, Minimum Output. Actual ERCOT 2009 Load and Wind Data, Linear Scale. ERCOT 2007 Gen mix from eGrid2010. Costs & Tech Parameters from Northwest Power Plan #6, 2010.

ERCOT 2009 + 20% growth with 20% RPS

!"#"$"%"&"'!"'#"'$"'%"'&"#!"

()*+,-"" .-/0),-1"

!"#

$%&'

&()*+$,-./$

0'"1&2345$637"8$

$$!"#$9:"1;&8$$%&'&()*+"

!"

2!"

'!!"

'2!"

#!!"

#2!"

3!!"

32!"

$!!"

()*+,-"".-/0),-1"

93*&8$-

"4"1&2

34$,9

.:/$

0'"1&2345$637"8$

$$<4"1=+$6)>"

!"

2!"

'!!"

'2!"

#!!"

#2!"

()*+,-"".-/0),-1"

?44

@&8$<;)55)34

5$,6

*$%0A"/$

0'"1&2345$637"8$

$$

456789:-0;-<"4567758"

4=;-"

>)?1"

7@0,"

%&1B34$<;)55)345"





!"#"$"%"&"'!"'#"'$"'%"'&"#!"

()*+,-"" .-/0),-1"

!"#

$%&'

&()*+$,-./$

0'"1&2345$637"8$

$$!"#$9:"1;&8$$%&'&()*+"

!"

2!"

'!!"

'2!"

#!!"

#2!"

3!!"

32!"

$!!"

()*+,-"".-/0),-1"

93*&8$-

"4"1&2

34$,9

.:/$

0'"1&2345$637"8$

$$<4"1=+$6)>"

!"#!"$!"%!"&!"'!!"'#!"'$!"'%!"'&!"

()*+,-"".-/0),-1"

?44

@&8$<;)55)34

5$,6

*$%0A"/$

0'"1&2345$637"8$

$$

456789:-0;-<"4567758"

4=;-"

>)?1"

7@0,"

%&1B34$<;)55)345"


!"#"$!"$#"%!"%#"&!"&#"'!"

()*+,-"" .-/0),-1"

!"#

$%&'

&()*+$,-./$

0'"1&2345$

$$!"#$67"18&9$$%&'&()*+"

!"

#!"

$!!"

$#!"

%!!"

%#!"

&!!"

&#!"

'!!"

()*+,-"".-/0),-1"

63*&9$-

"4"1&2

34$,6

.7/$

0'"1&2345$

$$:4"1;+$<)="

!"

$!"

%!"

&!"

'!"

#!"

2!"

3!"

4!"

()*+,-"" .-/0),-1"

>44

?&9$:8)55)34

5$,<

*$%0@"/$

0'"1&2345$

$$

56789:;-0<-="5678869"

5><-"

?)@1"

8A0,"

%&1A34$:8)55)345"




Problems with Simple Ops

Design Model

Scenario Simple Detailed (UC)

Optimal Expansion with $45/ton + 20% RPS

$40.0B/yr 61.7Mt CO2

9GW CT + 13.5GW Nuke

$38.4B/yr 68.2Mt CO2

14GW CT + 8GW Nuke

Optimal Expansion with 44.5Mt CO2 cap + 20% RPS

Infeasible Can’t reach RPS + Cap

$42.5B/yr $97.6/t CO2

4GW CT+4GW CCGT+13.5GW Nuke


1.  Assume target CO2=44.5Mt ($45/t) 2.  Find optimal plan(s) 3.  Run using detailed UC model

Note: using older EIA costs and conservative technical constraints

What is going on?

2000 20 40 60 80 100 120 140 160 180

200

50

60

80

100

120

140

160

180

Carbon Emissions (Mt CO2e)

Tota

l Ann

ual C

ost

($B/

yr)

Lots o' Coal

Way over built

Minimum Emissions

Simple OperationsReserve Constraints

Lots o' Gas


Tota

l Ann

ual C

ost

Carbon Emissions

A Combined Model

o Capacity Planning n  Minimize Investment + Ops Cost n  RPS, CO2 cost, CO2 cap

o Unit Commitment (Operations) n  On/Off decisions n  Min/Max output per plant n  Ramping n  Startup costs & limits


“Classic” Approach o Unit Commitment: Binary On/Off

n  Every Plant n  Every Hour

o Capacity Planning: Build/Not Build n  New Plants only n  Every ~Year

o Can reduce to 3 states/gen/time:


...OnOff

Not Built

Nmax1

Clustered Integer Approach

1.  Group units into clusters

2.  Two integers: n  # Built n  # Committed

Assumption: identical plants in cluster (same tech.)


See paper for mathematical formulation and specifics

0

Nmax

Plants Built

Plants on-line

Reduced Curse of Dimensionality Traditional Binary Clustered Integer

Combinations 100 units in 10:20:70 Clusters

1047 107

CPLEX equations 235units x 168hr Generation Expansion

536,731 12,319

CPLEX equations 235units x 8760hr Generation Expansion

Too Large 630,775


Enables

o High time resolution: 8760hr o  Full size system:

195 existing units, 128+ new units


Performance Comparison

Problem Traditional UC Cluster Integer UC Capacity Planning Old data

00:00.57 56:55.22

Capacity Planning New data

8 sec 10800+ sec (time limit)

Operations Only New data

0.3 sec 25 sec


o  Identical Problems/Solutions o  168hr (1 week) only o  324 units, 8-9 clusters

Time to solve Mixed Integer problem to 0.02% MIP tolerance. Solver CPLEX 12.2, formulation in GAMS, Single 2.4GHz core. ERCOT2009 + 20% growth + 20% RPS from earlier examples except ops only: 0.95% growth with 10% RPS. Minimum data output

100-5000x Faster

Conclusions o  Operations constraints critical for

planning with renewables n  Infeasible mixes n  Emission Targets

o  Clustered Integer Unit Commitment Formulation is efficient n  Enables 8760hr & 300+unit

o  Other potential uses n  Annual Emission Cap n  Initial Integer solution


0

Nmax

Plants Built

Plants on-line

Design Model

Scenario Simple Detailed (UC)

Optimal Expansion with $45/ton + 20% RPS

$40.0B/yr 61.7Mt CO2

9GW CT + 13.5GW Nuke

$38.4B/yr 68.2Mt CO2

14GW CT + 8GW Nuke

Optimal Expansion with 44.5Mt CO2 cap + 20% RPS

Infeasible Can’t reach RPS + Cap

$42.5B/yr $97.6/t CO2

4GW CT+4GW CCGT+13.5GW Nuke

On-going research

o  Clusters for Long-term Unit Commitment o  Heterogeneous Clusters o  Uncertainty

n  Operations, including forecasts n  Long-term: policy, prices, etc.

o  Multi-stage investment decisions n  Approximate Dynamic Programming n  Multi-fidelity models


QUESTIONS?


Documents

Electric Power Planning for Flexibility