model for area price determination-kjetil for area price determination and congestion management in...

1SINTEF Energy Research

Model for Area Price Determination and Congestion Management in Joint Power

Markets

Market splitting Flow based market coupling

Gardermoen, 26-27 Oct. 2005

Kjetil Uhlen, Leif Warland, Ove S. GrandeSINTEF Energy Research


Outline of presentation

Background and aims of the modelHourly day-ahead markets, focus on the Nordic systemDifferent requirements and solutions for price calculations and congestion management

Alternative model for area price determination Implementation of the demo model

Case studies and sample resultsConcluding remarks


Market splitting – Market coupling

Basically the same thingImplicit auction

Difference only in the way prices are calculatedMS: First compute system price. Then, split into separate price areas if exchange limits are violatedMC: First compute price vs. exchange in each area. Then, connectthe areas and compute actual prices and exchanges.

Best suited in systems where the areas are radiallyconnected” (refer to “EXCHANGES” not “FLOWS”)Well suited for hierarchical structures

MC can be used to harmonise two different markets (e.g. Nordel vs. Germany)


Advantages of market splitting/coupling

The day-ahead prices in the total system are calculated simultaneously

The price differences between the predefined areas willadjust the power exchange to the available transfer capability (ATC) and

reflect the consequences of congested corridors

Separate auctions for the network are not necessary


Limitations with market splitting

One major weakness / limitation of the Nordic Area Price model:

The model lacks representations of the physical lines / transmission corridors between the price areas

⇓

may lead to sub-optimal utilization of the transfer capacity (in meshed networks)

The real physical Flow as a consequence of different areaprices is not calculated

Major drawback in highly meshed networks


E2

E1

E3

E4

1

2

3

4Ei = Net exchange

from area i

E2

E1

E3

E4

1

2

3

4Ei = Net exchange

from area i

Market splitting(zonal pricing)

LMP(nodal pricing)

Good solution from the market point of viewToo simple for congestionmanagement

Good solution for congestionmanagementComplex solution and less acceptable from the market pointof view

Compromise

?

”Flow of dollars vs. the flow of physics”


Proposed model

Basic principle: Combination of market splitting and nodal pricing Each area is defined as one nodeUses a network equivalent representing the transmission system between the areasPrice calculation based on dc optimal power flowCriterion of optimization: Minimization of the socio-economic congestion cost

Improved utilisation of the available transfer capability and

reduced market player risk


F12F13

F23

F24

F34

1

23

4(F = Flow)

E2

E1

E3

E4

1

23

4(E= Exchange)

Present model New model

Alternative model for Area Price determinationand congestion management


Area equivalent and cost function

p0

E0

p0

∆E

∆Ε


Implementation

A demo model of the proposed method is implemented in MATLAB

Simple graphical interface to display results

Use of the model:Input data are:

aggregate supply curves (marginal cost of generation) for each area(Constant) load and exchange to external (not modelled) areas network impedanceslimits on transmission corridors

The model computes a solution by minimizing the cost functionwithout violating transfer limitsIn addition, the load flow equations must be fulfilled


Case studies

Sample results to demonstrate the functionality of the model and the user interface.Examples are shown to highlight main features of the model:

How one congested corridor result in different area pricesHow marginal generation changes in one area can affect congested corridors and prices in other areas.How control of HVDC links is included to maximize utilization ofthe transmission system.

Disclaimer: The examples do not intend to represent a real system or a real operating situation.


Market demand: Power flow identifies bottleneck on NO2 NO1


”Run”: Minimizes congestion costs while enforcing transfer limits


Trying to reduce loop flow NO1 SE1 DK1…


Trying to increase export from Finland…


Concluding remarksAn alternative approach to area price determination in physical day-ahead (spot) markets has been described.

The method combines the advantages of market splitting (area pricing) with power flow calculations.

The criterion of optimization is minimization of the socio-economic congestion cost.

The proposed method is implemented and demonstrated in a demo model

The proposed method/model corresponds to the FMC model proposed by EU


Extra slides..


POWERNEXT

Transmissionconstraint

Market regionin which pricescorrelate

Nordic/Baltic

Mittel

Iberia

FRANCE

NorthwestEurope

RUSSIA

FINLAND

AUSTRIA

ITALYSPAIN

SWEDEN

NORWAY

GERMANY

HUNGARYROMANIA

BULGARIA

TURKEY

DENMARK

POLAND

BELARUS

UKRAINE

UK

CZECH REP.

SLOVAKIA

GREECE

BELGIUM

IRELAND

SERBIA

ALBANIA

MOLDOVA

LITHUANIA

LATVIA

ESTONIA

LUX.

MONTENEGRO

BOSNIA

CROATIA

SLOVENIASwitz

MACEDONIA

Britannica

EPX/POWERNEXT(2001 ?)

UKEKUKPX

USAPX

APX

SPXIPX

(2001 ?)

PPX

NORDPOOL

EEXLPX

APX

UKEKUKPX

USAPX

POWERNEXT

SPX

PPX

PHELIX

NORDPOOL

IPX

European Power Exchanges


Congestion Management in Continental Europe

ETSO paper and EU statements conclude that:Market splitting (Area pricing) is a very interesting principle for congestion management, but it has severe requirements that have to be addressed before considering implementation outside Nordel:

* In highly meshed networks will congested lines change withdemand and generation

* Neighbouring constraints are strongly interdependent

(* Impact on bilateral trade)

Optimal utilisation of a highly meshed network will imply co-ordinated load-flow calculations as an integral part of the final allocation procedure.


Proposed concept to integrate market information in Power system simulators

Load data:-Load forecast-outage schedules

Market inputs:Aggregate bid curves

MARKETmodel

DISPATCHmodel

SIMULATORS-Power flow-Dynamic simulator- …

User control

Prices

Exchanges

Pgen, Pload

Topologydata

Technical data:-Network data-generator data


Application examples(Potential benefits of a market model)

It can be used simply as an aid to establish study cases of interest.

It becomes possible tostudy the impact of changing transfer limits on system security, stability, etc. and on market prices study the impact of the (supply and demand) bid curves on systemoperation (sensitivity analysis) e.g. study the impact of having more price-responsive demand.

Educational purposes – useful enhancement of operator training simulators


Further work and possibilities

The Nordic Area price model is considered as a basis for the future model of the European spot market

Advantages seen from ETSO and EU- The day ahead prices in the system are calculated

simultaneously- Price differences between areas adjust the transfer to

the transfer capacity- Separate auctions of transfer capacity will not be

needed


A|Fmax|

(deficit)B

(surplus)

ps

pA

Fre

d

pB

Fred

ConsumersurplusProducersurplus

a

b c de

f

g

hc’

e’d’

i

j

Flow

Price

Flow Flow

PricePrice

Area A Area B

System

i’

b’

Socio-economic congestion costs


Price

MW

Supply ADemand A

FmaxpA-B

System Price

MW

Σ Supply

Σ Demand

Price

MW

Supply B

Demand B

A B|Fmax|

(surplus) (deficit)

F1

Fmax

pSpA

pB

CongestionCongestion managementmanagementPrinciplePrinciple ofof Market SplittingMarket Splitting

p’A

p’B

F1


Price

Price vs. exchange A

Price

MW

Price vs, exchange B

A B|Fmax|

(surplus) (deficit)

-F1

pS

CongestionCongestion managementmanagementPrinciplePrinciple ofof Market Market CouplingCoupling

p’A

p’BF1

MW

pA-B

Area Prices at Fmax

MW

FmaxpA

pB

pS


Methodology and approach

The proposed model meets the following requirements1) Each node represents a predefined price area

(reflecting network constraints)2) The network equivalent represent the real power lines

between the price areas3) The Bid Curves are estimated based on real curves

from Nord Pool4) Optimisation criterion: Minimization of the Socio-

economic congestion cost


Optimisation criterion

Reduce the total congestion costs in the Nordic systemAn optimal power flow problem

pi Ci

Ei

psi

Esi

pi0

Ei0

bEEEpp

Ep iisi

isii +

−−

≈0

0)(

22

0

0 )(21)(

21

siii

isii

isi

isi EE

Ep

EEEEpp

C −∆∆

=−−−

=

2

1

1 ( )2

Ni

total i sii i

pCost E EE=

∆= −

∆∑


Supply and demand curves

Data from Nordpool

C:\Flex\SAPRI\20011015\ak20011015t20.txt

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 2000 4000 6000 8000 10000

MWh/h

NOK/M

Wh


Optimisation problem..

An optimal power flow problem with a quadratic objectfunction and linear constraints:

2

1

1min ( )2i

Ni

i siE i i

p E EE=

∆−

∆∑maxmin

gigigi PPP ≤≤

maxijij SS ≤

maxjiji SS ≤

1min min ( )2

T Ttotalx x

Cost G x x Hx F x= = +

bAx ≤ eq eqA x b= bb UxL ≤≤

The HVDC links are represented in the optimization as controlvariables (load or generation) with zero cost


Methodology … cont.

Solving the load flow- The method used is Direct Current load flow- Relevant in cases where the only interest is in the active

power flow and where a rough approximation is accepted

The power Ei injected into the bus for each area isE=P+Yδ,

P is the flow in the HVDC links and represented as load/generation depending on the direction of the flow

The flow Fij between area i and j is Fij=Yij(δi-δj)


Methodology … cont.

Estimating the impedances in the area model

12

1312 12

1 2313*

223 12*

*12 12 113*

13 *2

23 23^^

112 1212^

13 ^2

1323^

23

0 0 0 00 0 0 0 0

0 0 0 0 00 0 0 00 0 0 0 00 0 0 0 00 0 0 00 0 0 0 00 0 0 0 0

FFY YFY

Y FY Y

FYY F

Y Y FY

FY

F

δδ

δ

δ

δ

δ

⎡⎢

−⎡ ⎤ ⎢⎢ ⎥⎡ ⎤ ⎢⎢ ⎥⎢ ⎥ ⎢⎢ ⎥⎢ ⎥ ⎢⎢ ⎥⎢ ⎥ ⎢−⎢ ⎥⎢ ⎥ ⎢⎢ ⎥⎢ ⎥ ⎢=⎢ ⎥⎢ ⎥ ⎢⎢ ⎥⎢ ⎥ ⎢⎢ ⎥⎢ ⎥ ⎢−⎢ ⎥⎢ ⎥ ⎢⎢ ⎥⎢ ⎥ ⎢⎣ ⎦⎢ ⎥⎢ ⎥⎣ ⎦

⎣

⎤⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥

⎢ ⎥⎢ ⎥⎢ ⎥⎢ ⎥⎦

12 12 1 12

13 13 2 13

23 23 3 23

00

0

Y Y FY Y F

Y Y F

δδδ

−⎡ ⎤⎡ ⎤ ⎡ ⎤⎢ ⎥⎢ ⎥ ⎢ ⎥− =⎢ ⎥⎢ ⎥ ⎢ ⎥⎢ ⎥⎢ ⎥ ⎢ ⎥−⎣ ⎦⎣ ⎦ ⎣ ⎦

⇒

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