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Co st Re duc tio n Po te ntia ls in Co st Re duc tio n Po te ntia ls in the Ge rma n Ma rke t fo r Ba la nc ing Po we r K K ai F ai F linke rbusc h (MSc E linke rbusc h (MSc E c ) Dr Mic hae l He ute rke s c ), Dr. Mic hae l He ute rke


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SLIDE 1

Co st Re duc tio n Po te ntia ls in Co st Re duc tio n Po te ntia ls in the Ge rma n Ma rke t fo r Ba la nc ing Po we r

K ai F linke rbusc h (MSc E c ) Dr Mic hae l He ute rke s K ai F linke rbusc h (MSc E c ), Dr. Mic hae l He ute rke s Unive rsity o f Münste r

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SLIDE 2

Supply

=

Demand

Transmission system operator (TSO)

Demand

(TSO)

  • Provides ancillary services
  • Monopsony

Consumers +

Un‐ anticipated Events Balancing power Balancing power

Three types of balancing power

  • Primary balancing power
  • Secondary balancing power

Producers

Events

Control areas Secondary balancing power

  • Tertiary balancing power

Supply

  • Four areas:

EnBW, e.on, RWE, Vattenfall

  • Each area is controlled

separately

Demand

l l h d l

separately

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 2

Motivation Data Results Conclusion The Model

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SLIDE 3

Pro c ure me nt o f balanc ing po we r

1. T SO spe c ifie s de ma nd 2. T SO buys quantitie s by auc tio n 3. Supplie rs submit bids (de mand rate , e ne rg y rate ) 4. T SO o rde rs bids by de mand rate (sc o ring rule )

Demand

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 3

Motivation Data Results Conclusion The Model

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SLIDE 4

Ac tiva tio n o f ba la nc ing po we r

1. Co ntro l are a imbalanc e o c c urs 2. T SO o rde rs supplie rs by e ne rg y rate (se ttle me nt rule )

Imbalance

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 4

Motivation Data Results Conclusion The Model

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SLIDE 5

Co st re duc tio n po te ntia ls

  • 1. E

ffe c t: Ne tting antipodal use of balanc ing powe r

  • 2. E

ffe c t: Mor

e e ffic ie nt pr

  • c ur

e me nt auc tions

  • 3. E

ffe c t: L

e ss pr

  • vision of balanc ing powe r

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 5

Motivation Data Results Conclusion The Model

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SLIDE 6

Da ta

  • Obse rve d Pe rio d

12 mo nths

De c 2007 – No v 2008

  • So urc e

We bsite s o f T SOs

  • T

wo distinc t datase ts 1. Auc tio n data (bids fro m pro c ure me nt auc tio ns) ( p ) 2. Ac tivatio n data (po we r flo ws)

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 6

Motivation Data Results Conclusion The Model

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SLIDE 7
  • 1. Auc tio n Da ta

Pr imar y Balanc ing Powe r Se c ondary Balanc ing Powe r

  • Bids are valid fo r1 mo nth
  • Po sitive / ne g ative

g

  • Pe ak- / o ffpe ak

T e r tiar y Balanc ing Powe r y g

  • Bids are valid fo r4 ho urs
  • Po sitive / ne g ative

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 7

Motivation Data Results Conclusion The Model

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SLIDE 8

Se c o nda ry ba la nc ing po we r: Bid size s

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 8

Motivation Data Results Conclusion The Model

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SLIDE 9

De ma nd ra te s

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 9

Motivation Data Results Conclusion The Model

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SLIDE 10

E ne rg y ra te s

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 10

Motivation Data Results Conclusion The Model

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SLIDE 11
  • 2. Ac tiva tio n Da ta

Ac tual po we r flo ws Data fre que nc y

  • Quarte ro f an ho ur
  • 35,136 o bse rva tio ns

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 11

Motivation Data Results Conclusion The Model

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SLIDE 12

Se c o ndary balanc ing po we r [MW]

E nBW E nBW

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 12

Motivation Data Results Conclusion The Model

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SLIDE 13

e on e .on

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 13

Motivation Data Results Conclusion The Model

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SLIDE 14

RWE RWE

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 14

Motivation Data Results Conclusion The Model

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SLIDE 15

Vatte nfall Vatte nfall

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 15

Motivation Data Results Conclusion The Model

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SLIDE 16

T e rtia ry ba la nc ing po we r [MW]

RWE RWE

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 16

Motivation Data Results Conclusion The Model

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SLIDE 17

Market design is known

  • Scoring Rule

S ttl t R l

  • Settlement Rule
  • Control Areas

Data is available

  • Auction Data

A ti ti D t

  • Activation Data

Simulation of the market for balancing power with GAMS

  • Scenario 1: Status quo
  • Scenario 2: One united control area
  • Scenario 2: One united control area

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 17

Motivation Data Results Conclusion The Model

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SLIDE 18

T e sting the mo de l

  • T

e c hnic al re stric tio ns

  • Data fre que nc y
  • Mo de l spe c ific atio n

Ave ra g e we ig hte d e ne rg y ra te s:

AWER ENBW AWER EON AWER RWE AWER Vattenfall DATA SIM DATA SIM DATA SIM DATA SIM Mean 60.10 58.24 36.74 36.43 52.40 49.09 53.02 47.19 Median 61.00 61.00 0.00 0.00 2.00 2.00 3.00 2.75

l l h d l

Correlation 0.98 0.99 0.97 0.97

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 18

Motivation Data Results Conclusion The Model

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SLIDE 19

120

Scenario 1: "status quo"

80 80 M € Activation tertiary Procurement tertiary Activation secondary 40 Activation secondary Procurement secondary Primary

l l h d l

December‐07 November‐08

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 19

Motivation Data Results Conclusion The Model

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SLIDE 20

120

Scenario 2: United control area

80 80 M € Activation tertiary Procurement tertiary Activation secondary 40 Activation secondary Procurement secondary Primary

l l h d l

December‐07 November‐08

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 20

Motivation Data Results Conclusion The Model

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SLIDE 21

Co mpa riso n o f a bso lute le ve ls

Primary Secondary Tertiary Primary Secondary Tertiary Procurement Activation Procurement Activation Sum ( ) Scenario1 (M€) 114.8 230.4 351.3 227.5 30.7 954.8 Scenario2 (M€) 114.8 229.4 190.6 227.3 29.8 792.1 difference 0.00% ‐0.43% ‐45.72% ‐0.07% ‐3.06% ‐17.04%

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 21

Motivation Data Results Conclusion The Model

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SLIDE 22

Co mpariso n o f share s

Scenario 1 Scenario 2

12% 24% 3% 14% 4% Primary P t d 24% 29% 29% Procurement secondary Activation secondary Procurement tertiary 37% 29% 24% Activation tertiary l l h d l 37% %

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 22

Motivation Data Results Conclusion The Model

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SLIDE 23

Conclusion

  • When sufficient grid capacity is assumed, antipodal use of

balancing power is inefficient Conclusion balancing power is inefficient

  • Netting area imbalances  major cost reductions (160 M€)
  • This is mostly on account of secondary balancing power

Further research

  • Co‐operation of e.on, EnBW and Vattenfall
  • Efficiency of scoring rule and settlement rule

Further research c e cy o sco g u e a d sett e e t u e

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 23

Motivation Data Results Conclusion The Model

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SLIDE 24

Co ntac t: K ai F linke rbusc h L e hrstuhl für Vo lkswirtsc haftsthe o rie We stfälisc he Wilhe lms-Unive rsität Münste r We stfälisc he Wilhe lms Unive rsität Münste r K a i.F linke rbusc h@ wiwi.uni-mue nste r.de

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 24

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SLIDE 25

Ba c kup

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 25

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SLIDE 26

Mo de l se que nc e

Step 1: Procurement

min!

  • Scoring rule:
  • s.t.

  

 

b t c c t b c t b

m dr PC

, , , , min! c t b c t b

m m

, , ,

Step 2: Activation

  • Settlement rule:
  • s.t.
  • and

  

 

b t c c t b c t b

x er AC

, , , , min!

 

c c t b c c t b

m x

, , , , c t b c t b

CAI x

, , ,

c t b c t b , , ,

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 26

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SLIDE 27

AWER ENBW AWER EON AWER RWE AWER VET

DATA SIM DATA SIM DATA SIM DATA SIM Mean 60.101 58.240 36.749 36.434 52.404 49.094 53.027 47.192 Median 61.000 61.000 0.000 0.000 2.000 2.000 3.000 2.750 Maximum 475.000 289.370 322.000 282.060 599.000 331.760 501.000 262.190 Minimum 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Correlation 0.984 0.993 0.977 0.975 Obs 35136 35136 35136 35136 35136 35136 35136 35136 Obs. 35136 35136 35136 35136 35136 35136 35136 35136 Table 3: Descriptive statistics of average weighted energy rates

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 27

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SLIDE 28

Co -o pe ratio n o f E nBW, e .o n and Vatte nfall

De c e mbe r2008 Re duc tio n o f antipo dal use

May 2009 Re duc tio n o f pro c ure me nt

June 2009 Pre qualific atio n fo runite d c o ntro l are a

Oc to be r2009 Jo int me rit o rde r

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 28

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SLIDE 29

L ite rature Re vie w

Haubrich (2008): Gutachten zur Höhe des Regelenergiebedarfs

  • Computation of the potential economies of scope of a united control area
  • Result: Provision of balancing power could be reduced by 400 MW (positive) and 1000

Result: Provision of balancing power could be reduced by 400 MW (positive) and 1000 MW (negative)

  • Effect not included in our article

LBD‐Beratungsgesellschaft (2008): Untersuchung des Einsparpotenials bei der regelzonenübergreifenden Saldierung

  • Computation of the netting‐effect in a united control area
  • Result: Cost reductions of 314 million euros are possible
  • Results are based on average weighted energy rates

l l h d l

Oc to b e r10, 2009 K a i F linke rb usc h, Dr. Mic ha e l He ute rke s 29

Motivation Data Results Conclusion The Model