The Transmission System Operator as Service Provider The Example of the Procurement of Grid Losses in Austria

Transcription

1 The Transmission System Operator as Service Provider The Example of the Procurement of Grid Losses in Austria Dr. Florian Leuthold, UMM / Market Management

2 Framework AUSTRIAN POWER GRID AG

3 The Regulated Business In Austria the ElWOG law stipulates the role of the transmission system operator Amongst these tasks are regulated activities that requires marketbased methods Primary control Secondary control (Tertiary control) (Flow-based) Allocation of cross-border capacities If this creates rents, the transmission system operator is obliged to use the rents for price decrease or investments AUSTRIAN POWER GRID AG

4 New Challenges and Opportunities Beginning with 2009, the Austrian regulator ECG evaluated whether the procurement of grid losses could be carried out centrally Coordinated procurement Procurement of standard products similar to those traded via exchanges or on the OTC market Daily clearing of residual positions via power exchanges Central clearing of balancing energy Loss forecast by the (distribution) system operators but monitoring by the APG Will be implemented if APG can gather 60% of Austrian s grid losses. Non-regulated activity! Incentive for APG to participate required! AUSTRIAN POWER GRID AG

5 Portfolio Management AUSTRIAN POWER GRID AG

6 Grid Losses in 2008 (APG) Last [MW] Load [MW] Zeit T AUSTRIAN POWER GRID AG Time T

7 Decomposition of net position ( Lastgangzerlegung ) MW MW Compare Borchert et al. (2006) standard products T residual position base product peak product In a derivatives market netposition will be separated in a marketable part as well as in a spot market part Standard products are marketable liquidly at derivatives market; residual position will be counterbalanced at the spot market AUSTRIAN POWER GRID AG

8 Load Decomposition: Minimizing Spot Market Quantities Objective: Minimizing the open spot quantity position Min: t (Load_forecast t -Hedge t ) 2 Pros: Easy to implement Market knowledge is not required Cons: Inter-temporal hedging options based on price-correlations are not taken into account Price gaps between futures and spot market cannot be exploited One-dimensional criterion Assessment: The open spot position itself is not a sufficient criterion in a liberalized electricity market Financial aspects and volatilities are more important than pure quantities AUSTRIAN POWER GRID AG

9 Load Decomposition: Minimizing Spot Market Values Objective: Minimizing the market value of the open spot quantity position Min: t ((HPFC t *(Load_forecast t -Hedge t )) 2 ) Pros: Market prices are included (price forecasts required) Easy to implement Cons: Risk is in price volatilities not in absolute price numbers Price gaps between futures and spot market cannot be exploited One-dimensional criterion Assessment: The market value is consider to be a deterministic parameter The optimization is based on deterministic future prices (HPFC, Hourly Price Forward Curve) This approach fulfills the minimal requirements regarding a liberalized electricity market AUSTRIAN POWER GRID AG

10 Load Decomposition: Minimizing Risk Measures Objective: Minimizing the market risk of the open spot quantity position Min: CVaR(Open_Position) See next slides Pros: Risk of spot market purchases is adequately taken into account Constraints due to risk attitudes can be included Market prices are included (price forecasts required) Reliable methodology Cons: Price gaps between futures and spot market cannot be exploited Assessment: The market value of the open position is treated as stochastic parameter State-of-the-art methodology for a liberalized electricity market Compatible with standard risk measures AUSTRIAN POWER GRID AG

11 Load Decomposition: CVaR Definition Risk definition (CVaR) for the purchasing cost taking into account volatilities Probability VaR CVaR Maximum loss 0 Probability 1-ß Portfolio loss AUSTRIAN POWER GRID AG

12 Load Decomposition: CVaR Minimization Based on Borchert and Schemm (2007) Min CVaR s. t. p _ fo VaR s t VaR p ( P _ 1 n * (1 ) H p * pm t, p s ) ( VaR P _ S t spot _ simu * P _ S ( P _ H * fp * pm ) VaR s t t, s t p p p t, p s t ) CVaR VaR VaR P_H p P_St p_fo t pm t,p fp p spot_simu t,s Variable for Conditional Value-at-Risk (objective value) Variable for Value-at-Risk Variable for values above Value-at-Risk Variable for hedge position per product p Variable for spot position in time increment t Parameter for load forecast in time increment t Parameter for product matrix describing which product p covers time increment t Parameter for futures (forward) price for product p Parameter for spot price in simulation s for time increment t n Scalar for number of simulations s Scalar for confidence level (e.g for 95%) s t Index for simulation Index for time increment AUSTRIAN POWER GRID AG

13 Parameter Preparation 1. Correction for spikes 2. Impact of holidays and weekends 3. Local regression for seasonal corrections 4. Principal Component Analysis (PCA) to explain remaining variances AUSTRIAN POWER GRID AG

14 Spot Price Simulations Stochastic processes First five factors of PCA explain 95% of the variance 1st factor loading: modeled by two processes ( Kalman filter) 2nd to 5th factor loading: modeled by one process each Jump diffusion process to model price spikes HPFC generation 1st step: Mean values of the processes 2nd step: Fitting to the observed forward prices ( arbitrage-free) Spot price simulations Monte-Carlo simulations of the factor loadings yield different HPFCs ( scenarios ) Spot price simulations not (yet!?) carried out by APG (external provider priceit) AUSTRIAN POWER GRID AG

15 Load Decomposition: Efficient Frontier Purchasing potential Minimum CVaR Additional purchasing potential Minimal Spot Market Value Minimal Spot 0 Quantities Risk Capital CVaR For a given risk attitude, the optimal expected purchasing cost can be realized AUSTRIAN POWER GRID AG

16 Risk Management AUSTRIAN POWER GRID AG

17 Procurement Path Price volatilities and market liquidity for forward products vary, i.e.: Long-term range (~ > 2 years): Low volatility, low liquidity Mid-term range (~ > 6 month): Medium volatility, medium liquidity Short-term range (~ < 6 month): High volatility, high liquidity S-strategy Procurement Path T - 2 year T Order strategy defines how much and when energy should be bought In the S-strategy, most of the quantities are within the mid-term rang AUSTRIAN POWER GRID AG

18 Quantity Limits: Example Order path Limit paths Upper limit path Actual order Procurement path T - 2 years Limit for open long position [MWh] Lower limit path Limit for open short position [MWh] AUSTRIAN POWER GRID AG

19 How to group that risks? Usually the energy business is subject to the following risk groups: Market Risk Credit Risk Operational Risk The spread risk of generation as well as the volumetric and weather risk associated with asset generation are borne by the generation companies. AUSTRIAN POWER GRID AG

20 Market Risk Market risk describes the risk resulting from changes in market parameters which affects all open positions at asset-, trading and wholesale transactions Drivers: Market prices, volatilities, exchange rates, spreads, interest rates, correlations, different basis Measures: Definition and monitoring of Value-at-Risk (VaR) limits, Stress Limits, stop loss limits, volumetric limits AUSTRIAN POWER GRID AG

21 Measure: Value at risk (VaR) The VaR decribes the maximum potential loss within a considered period (T) with a certain probability (confedence level) under the assumption of normally distibuted absolute daily market value changes ( MV). t 1 1 VaR a * T * T * MV t0 i t The Conditional Value-at-risk (CVaR) is the expected value of the losses that is greater than the VaR. i 0 CVaR ( a) * T 1 p * t 0 T * 1 t t 1 i 0 MV i AUSTRIAN POWER GRID AG

22 Credit Risk Credit risk describes the risk resulting from business partners non-compliance with contractual obligations (e.g. not able or not willing to pay, insolvency) Drivers: Drivers are credit worthiness of business partners, delivery period, Markto-Market of the deal and contractual terms like payment conditions, withdrawal clause, netting agreement Measures: Definition and supervision of limits per Counterpart (Scoring) Counterpart and exposure monitoring Management of securities Netting AUSTRIAN POWER GRID AG

23 Free credit limits per trade partner exposure Exposure and und limits Limit of der counterparties Handelspartner Limit Exposure Credit Kredite line Mio in Mio AUSTRIAN POWER GRID AG

24 Operational Risk Operational risk describes the risk that results from financial damage due to lacks within the internal organisation (processes, systems, human activities) respectively financial damage because of external events (natural catastrophe, man-made disaster) Drivers: Drivers are change, complexity, complacency, as well as capacity, capability, availability Measures: Monitoring of error rates and documentation of faults (risk diary) Documentation of business processes Access rights in IT systems Measures for business continuity and business recovery in case of disaster AUSTRIAN POWER GRID AG

25 Operational risk: A permanent beast Operational risk has some unfavourable characteristics: It forms a bundle of highly diverse risks It is inherent to business and therefore often taken unconsciously It may hit directly and indirectly, i.e. via a credit risk or a market risk Mostly, there is no reward for taking it Low frequency-high impact events play a very prominent role It is in most cases the operational risk that forms the second largest exposure of a bank! (e.g. internal fraud at Société Générale a couple of years ago) AUSTRIAN POWER GRID AG

26 Organizational Issues AUSTRIAN POWER GRID AG

27 Regulations and hierarchy of rules Public Bodies Laws, regulations, market rules etc. Board of Directors (group level) Executive orders e.g. organisation, authorisation, tasks Board or Responsible Board Member/Holding (competence area) Group policies e.g. rulebook, credit policy Managing Directors (inside trading company) Company policies e.g. risk management, documentation, archiving Departments (inside trading company) Working orders e.g. deal capture Collected in operations manual AUSTRIAN POWER GRID AG

28 Group directive Company Rulebook Covers all activities of power trading and wholesale including energy related activities like emission trading, fuel hedging, etc. Objectives & Principles of Risk Management Transaction Principles Basic Orders and Overall Mandates for Trading, Wholesale and Retail Roles and Responsibilities in Risk Management Approved Trading Counterparties, Markets and Products Market and Product Approval Process Risk Management Methodologies (VaR etc.) Compliance & Reporting & Escalation Procedure to Risk Management Committee AUSTRIAN POWER GRID AG

29 Conclusions AUSTRIAN POWER GRID AG

30 Conclusions New tasks of the transmission system operator as service provider for other system operators Challenges Higher orientation towards established market methodologies to cope with and control new risk factors New know-how has to be brought into the company Opportunities Returns that do not result from the regulated business AUSTRIAN POWER GRID AG

31 Further Developments / Challenges Building-up standard procedures regarding market data and analyzes Building-up knowledge in simulating market price developments HPFC Spot price simulations This is where the (research) action is! AUSTRIAN POWER GRID AG

32 References / Bibliography Borchert, Jörg, and Ralf Schemm (2007). Einsatz der Portfoliotheorie im Asset Allokations- Prozess am Beispiel eines fiktiven Anlageraumes von Windkraftstandorten. Zeitschrift für Energiewirtschaft, 31(4), Borchert, Jörg, Ralf Schemm, and Swen Korth (2006). Stromhandel eine quantitative Einführung in Institutionen, Marktmodelle, Pricing und Risikomanagement. Stuttgart: Schäffer- Poeschel Verlag. Müsgens, Felix and Burkhard Steinhausen (2010). Portfoliomanagement: Optimale Energiebeschaffung unter Berücksichtigung von Risiken. Zeitschrift für Energiewirtschaft, 34(2), Weigt, Hannes (2009): Modeling Competition and Investment in Liberalized Electricity Markets. Dissertation, Dresden University of Technology. Available: AUSTRIAN POWER GRID AG