Long-Term Trading Strategies

Transcription

1 Long-Term Trading Strategies Alfred Hoffmann Bewag AG, Berlin 3th January 3, St. Veit, Austria 1 Structure Definition of the strategy Implementation of the strategy Case Study Conclusions

2 Value chains in the power industry Gas Value Chain Exploitation Processing Transportation and Storage Distribution Retail Sales Heat Extraction Distribution Retail Sales Gas Oil Nuclear Coal Fuel Preparation Distribution Transmis- Generation sion and System Service Power and Heat Value Chain Retail Sales 3 Planning-periods and their aims Long-Term Mid-Term Short-Term Online Time-horizon 1 days - n years -1 days 1 day Online Aims planning of maintenance short-term-maintenance unit-dispatching reaction on outages planning of fuel-amounts unit-commitment dispatch of ancillaray services Evaluation of technical dispatch of fuel control of production and economical scenarios Model 4 Model-definition usually more complex with shorter time-horizons Reasons for the fragmantation of time-horizon Uncertainty of parameters higher then model-accuracy Time-performance higher then useful

3 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 5 Define the objective 6 Maximise the volume and minimise the specific costs? Maximise the profits! How much risk are you willing to take? How much risk are your shareholders willing to take?! Define the benchmark!! EBITA ROCE... Take a look at your portfolio!

4 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 7 Risks (II): Operational Risk Technical Risk Outage of technical equipment, fire etc. -> mainly hedged by producer guaranties and insurances Waste of revenues is often unconsidered! Human Resources Recruitment of adequate staff is key-task of the management and HR-department Model Risk Examination and verification of your risk-models have to be established Organisational Risk Ensure the process-chain (responsibility, time-schedules, effectiveness) 8

5 Risks (III/1): Market Risk Price Prices are volatile and influence the production-portfolio in a significant way Liquidity Volumes may influence the prices on the wholesale market. An OTC-Term-Volume of approx. 15 TWh (3%) and day-ahead-volume of 5 TWh (1%) do not affect small producers. 9 Risks (III/): Market Risk Volume Especially 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 fuelcharacteristics which at best influences the generation-process and at worst makes it impossible (gross calorific value, ash, sulphur) Currency Currency-Risk of Europe-wide electricity-sales do not exist (transborder-capacity-risk is more evident) Fuels, with the exception of lignite, comprise currency-risk 1

6 Risks (IV): Counterpart Risk Credit-Risk Suppose that close-out-netting is possible the counterpartcredit-exposure should be limited to an amount of -3 months Position-Recovery-Risk No 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) 11 Forward-Prices Vergleich: [AV G - Jahr Base - Deutschland] (blau) und [AVG - Jahr Base - Deutschland] (rot) 5,45 5,5 5,5 4,85 Base-Prices of 3 and 4 4,65 4,45 4,5 4,5 3,85 3,65 3,45 3,5 3,5,85,65,45,5 Dez 1 Jan Feb Mrz Apr Mai Jun Jul Aug Sep Okt Nov D Peak-Prices of 3 and 4 39, Vergleich: [AV G - Jahr Peak - Deutschland] (blau) und [A VG - Jahr Peak - Deutschland] (rot) 38, 37, 36, 35, Best-Trading-Situations 34, 33, 3, 1 31, Dez 1 Jan Feb Mrz Apr Mai Jun Jul Aug Sep Okt Nov D

7 How to realise this trades In general it is nearly impossible to sell the energy at the highest price The only thing which is possible If the CHP-Operator is willing to take risk this might be useful if forward-price-volatility is high Check 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) 13 Exchange-Spot-Prices /M Wh 5 45 Volume LPX Phelix base Pric e GWh Jan Feb Mrz Apr Mai Jun Jul Aug Sep Okt Nov Dez 14 Beware of chances and risks of short-term-price-movements!

8 Case-Study: Coal fired condensing-extraction-turbine wholesale-electricity wholesale-ancillary-services fuel boiler transformer P [MW] turbine generator G condenser 15 heat-customer dq/dt fuel [MW] dq/dt heat [MW] Characteristics: Market environment, contracts Electricity-wholesale-prices given by the forward curve and an hourly volatility Secondary-reserve-prices given e.g. by RWE-history and an hourly volatility Fuel prices given by a long-term Take or Pay -Contract additional volumes are to be bought at the spot-market Heat-demand Heat-demand varies depending on the temperature 16

9 Expectation of EBITA Cash-flow [Mio. ] CHP-Electricity 15 CHP-KWKMG 9 Condensing- Electricity Peripheral Production Heat 16 Ancillary- Services 8-1 Fuel 3 Staff 3 Maintenance, Insurances,... 7 Depreciation Define your book-structure Heat Possible Limits: EBITA (PaR), VaR, ROCE,... Electricity Coal Possible Limits: EBITA, Net-Position-Energy, Net-Position- Power, VaR, ROCE,... Possible Limits: EBITA, Net-Position-Energy, VaR, Storage, ROCE,... Whole portfolio EBITA, VaR, ROCE,... 18

10 Take a look at your books Electricity Heat GWh Mio. GWh Mio Jan. Jul. Dez. Jan. Jul. Dez. Mio Portfolio Jan. Jul. Dez. Calculated via Stress testing, Monte Carlo Simulation, Analytic approach (difficult, because of the non-linearity's) Books after first hedge Electricity Heat GWh Mio. GWh Mio Jan. Jul. Dez. Jan. Jul. Dez. Hedging-Transactions: Mio. Electricity-Forward-Short Portfolio Coal-Forward-Long Temperature-Hedge (March, April, October, 1-1 Caused November) by volume-sensitivity based on the- small spread between coal and electricity! Jan. Jul. Dez.

11 Weather-Hedge Profit T Average Year Profit of portfolio * Derivative Product Over all Profit ,5,5 1 1,5 Temperature-Differance in K compaired to Long-Term-Average 1 * Evaluation against the market Portfolio after second hedge Summer-volatility could be hedged by Coal-Spark-Spread or by Electricity-Put and Coal-Call both linked with payments Put/Call realised and EBITA-Range between,9-x,x Mio. Additional small transactions necessary Mio Jan. Feb. Mrz. Apr. Mai. Jun. Jul. Aug. Sep. Okt. Nov. Dez.

12 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 bounded Hedging should be realised near to the front desk of Trading Risk should be reported every day Portfolio-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 besthedge-optimisation might be more interesting, even if to date the idea is unable to be carried out due to IT performance constraints. OSCOGEN-Project! 3 CHP - Mitte in Berlin Thank you for your interest. 4