1

1

Alfred HoffmannBewag AG, Berlin23th January 2003, St. Veit, Austria

Alfred HoffmannBewag AG, Berlin23th January 2003, St. Veit, Austria

Long-Term Trading StrategiesLong-Term Trading Strategies

2

Structure

Definition of the strategy

Implementation of the strategy

Case Study

Conclusions

2

3

Value chains in the power industry

Gas Value ChainGas Value Chain

Power and Heat Value ChainPower and Heat Value Chain

Dis-tribution

RetailSalesHeat Extraction

Dis-tribution

RetailSales

FuelPreparation Generation

Transmis-sion and SystemService

GasOilNuclearCoal

Dis-tribution

RetailSales

Transportation and StorageExploitation Processing

Heat Extraction

FuelPreparation Generation

GasOilNuclearCoal

4

Planning-periods and their aims

Time-horizon

Long-Term Mid-Term Short-Term Online

10 days - n years 2-10 days 1 day Online

Model

Model-definition usually more complex with shorter time-horizons

Reasons for the fragmantation of time-horizonUncertainty of parameters higher then model-accuracyTime-performance higher then useful

Aims

planning of maintenance short-term-maintenance unit-dispatching reaction on outagesplanning of fuel-amounts unit-commitment dispatch of ancillaray servicesEvaluation of technical dispatch of fuel control of productionand economical scenarios

3

5

Milestones of Long-Term-Trading-Strategies

Define the objective of the generation business-unit (BU)

Identify the risks of the BU

Define responsibilities

Search for / develop suitable hedge-products

Establish portfoliomanagement

Establish continuous risk-measurement and -reporting

6

Define the objective

Maximise the profits!

How much risk are you willing to take?

How much risk are your shareholders willing to take?

Define the benchmarkEBITAROCE

...

Take a look at your portfolio!

Maximise the volume and minimise the specific costs?

!!!! !!

4

7

Risks (I): Investment Risk

Mostly not focused during the implementation of portfolio-management, because investments are already taken

Possibility to avoid stranded investments through

Legal acts (KWKMG, EEG, Lex-Veag)

Long-term-sales-contracts and –fuel-contracts

Or define it as general business-risk

8

Risks (II): Operational Risk

Technical RiskOutage of technical equipment, fire etc. -> mainly hedged by producer guaranties and insurancesWaste of revenues is often unconsidered!

Human ResourcesRecruitment of adequate staff is key-task of the management and HR-department

Model RiskExamination and verification of your risk-models have to be established

Organisational RiskEnsure the process-chain (responsibility, time-schedules, effectiveness)

5

9

Risks (III/1): Market Risk

PricePrices are volatile and influence the production-portfolio in a significant way

LiquidityVolumes may influence the prices on the wholesale market.

An OTC-Term-Volume of approx. 1500 TWh (300%) and day-ahead-volume of 50 TWh (10%)

do not affect small producers.

10

Risks (III/2): Market Risk

VolumeEspecially coal (oil) comprises volume-risk, caused by the transport-specialities like availability of the transport-system (boat and river), capacity of the storage and the fuel-characteristics which at best influences the generation-process and at worst makes it impossible (gross calorific value, ash, sulphur)

CurrencyCurrency-Risk of Europe-wide electricity-sales do not exist (transborder-capacity-risk is more evident)

Fuels, with the exception of lignite, comprise currency-risk

6

11

Risks (IV): Counterpart Risk

Credit-RiskSuppose that close-out-netting is possible the counterpart-credit-exposure should be limited to an amount of 2-3 months

Position-Recovery-RiskNo matter if you have sold or bought electricity to/from the concerned counterpart - you have to recover your position which could provoke losses, because the market had moved.(generators generally buy energy too to manage their portfolio)

12

Forward-Prices

2 2 ,2 5 €

2 2 ,4 5 €

2 2 ,6 5 €

2 2 ,8 5 €

2 3 ,0 5 €

2 3 ,2 5 €

2 3 ,4 5 €

2 3 ,6 5 €

2 3 ,8 5 €

2 4 ,0 5 €

2 4 ,2 5 €

2 4 ,4 5 €

2 4 ,6 5 €

2 4 ,8 5 €

2 5 ,0 5 €

2 5 ,2 5 €

2 5 ,4 5 €

De z 0 1 Ja n 02 Fe b Mrz A p r Mai Ju n Ju l A u g Se p Okt No v D

V e rg le ic h : [A V G - Ja h r B as e - De uts c h la n d] (b la u ) u n d [A V G - Ja h r B as e - De uts c h la n d] ( ro t)

31 ,00 €

32 ,00 €

33 ,00 €

34 ,00 €

35 ,00 €

36 ,00 €

37 ,00 €

38 ,00 €

39 ,00 €

Dez 01 Jan 02 Feb Mrz A pr Ma i Jun Ju l A ug S ep Okt Nov D

V erg le ic h : [A V G - Jah r Peak - Deu ts c hland ] ( b lau) und [A V G - Jah r Peak - Deu ts c h land ] ( ro t)

Base-Prices of 2003 and 2004

Peak-Prices of 2003 and 2004

Best-Trading-Situations

7

13

How to realise this trades

In general it is nearly impossible to sell the energy at the highest price

The only thing which is possibleIf the CHP-Operator is willing to take risk this might be useful if forward-price-volatility is highCheck the effects of volatility on the portfolio (e.g. by stochastic programming)

Realise trades when prices seem to be high compared to your long-term-expectations and volatilities Never stay outside your limits as prices may fall (unexpectedly)

14

Exchange-Spot-Prices

LPX Phelix base

0

5

10

15

20

25

30

35

40

45

50

Jan02

Feb02

Mrz02

A pr02

Mai02

Jun02

Jul02

A ug02

Sep02

Okt02

Nov02

Dez02

€/M Wh

0

50

10 0

150

2 0 0

2 50

3 0 0

3 50

4 0 0

4 50

50 0

GWh

V olume Price

Beware of chances and risks of short-term-price-movements !

8

15

Case-Study: Coal fired condensing-extraction-turbine

G

P [MW]

dQ/dtfuel [MW] dQ/dtheat [MW]

boiler

turbine

condenser

generator

heat-customer

wholesale-electricity wholesale-ancillary-services

transformer

fuel

16

Characteristics: Market environment, contracts

Electricity-wholesale-pricesgiven by the forward curve and an hourly volatility

Secondary-reserve-pricesgiven e.g. by RWE-history and an hourly volatility

Fuel pricesgiven by a long-term „Take or Pay“-Contract

additional volumes are to be bought at the spot-market

Heat-demandHeat-demand varies depending on the temperature

9

17

Expectation of EBITA

15

9

423

37

18

4

Cas

h-fl o

w [M

io. €

]

9

16

CH

P-El

ectri

city

CH

P-KW

KMG

Con

dens

ing-

Elec

trici

tyPe

riphe

ral

Prod

uctio

n

Hea

t

Anci

llary

-Se

rvic

es

Fuel

Staf

f

Mai

nten

ance

,In

sura

nces

,...

Dep

reci

atio

n

8

-1

3

2

18

Define your book-structure

HeatPossible Limits: EBITA (PaR), VaR, ROCE, ...

ElectricityPossible Limits: EBITA, Net-Position-Energy, Net-Position-Power, VaR, ROCE, ...

CoalPossible Limits: EBITA, Net-Position-Energy, VaR, Storage, ROCE, ...

Whole portfolioEBITA, VaR, ROCE, ...

10

19

Take a look at your books

Calculated viaStress testing,

Monte Carlo Simulation,

Analytic approach (difficult, because of the non-linearity's)

HeatElectricity

Portfolio

012

- 1- 2

Mio. €

Jan. Jul. Dez.

100

200

0

0

2

- 2

- 4

Mio. €GWh

Jan. Jul. Dez.

02

- 2- 4- 6- 8

- 10

200

300

100

0

4Mio. €GWh

Jan. Jul. Dez.

20

Books after first hedge

PortfolioHedging-Transactions:Electricity-Forward-ShortCoal-Forward-LongTemperature-Hedge(March, April, October, November)

100

200

0Jan. Jul. Dez.

02

- 2- 4- 6- 8

- 10

200

300

100

0

4

Jan. Jul. Dez.

012

- 1- 2

Mio. €

Jan. Jul. Dez.

HeatElectricityMio. €GWh Mio. €GWh

Caused by volume-sensitivity based on thesmall spread between coal and electricity!

0

2

- 2

- 4

11

21 * Evaluation against the market

-1.000

0

1.000

2.000

3.000

4.000

5.000

6.000

7.000

8.000

-1 -0,5 0 0,5 1 1,5 2

Profit of portfolioDerivative ProductOver all ProfitPr

ofit

T€

Ave

rage

Yea

r

Temperature-Differance in K compaired to Long-Term-Average

*

Weather-Hedge

22

Portfolio after second hedge

Summer-volatility could be hedged by „Coal-Spark-Spread“ or by „Electricity-Put“ and „Coal-Call“ both linked with paymentsPut/Call realised and EBITA-Range between 2,9-x,x Mio. €

Additional small transactions necessary

Jan. Jul. Dez.Feb. Mrz. Apr. Mai. Jun. Aug. Sep. Okt. Nov.

0

1

2

- 1

- 2

Mio. €

12

23

Conclusions

Generation-portfolio is the most complex (non-linear interconnected with every energy-based-wholesale-market)

Product-variety is great and increases continuously, but liquidity is still boundedHedging should be realised near to the front desk of Trading

Risk should be reported every dayPortfolio-aggregation is favourable as risk „is“ smaller and limits are always short (enterprise-wide-risk-management!) „Step by step“-hedging is supported by trading-software but best-hedge-optimisation might be more interesting, even if to date the idea is unable to be carried out due to IT performance constraints.OSCOGEN-Project !

24

Thank you for your interest.Thank you for your interest.

CHP - Mitte in Berlin