hydro thermal optimization - fu-berlin.de
TRANSCRIPT
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
hydro thermal portfolio managementpresentation @ Schloss Leopoldskron
28 Sep 2004
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
contents1. thesis initiation2. context3. problem definition4. main milestones of the thesis5. milestones presentation6. résumé
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
1. thesis initiation■ Title: hydro-thermal portfolio management in a market environment
■ thesis is rising from a real case that is examined within the Electrabel company
■ based on a collaboration between Electrabel, EPFL and PSR institute■ motivation for the thesis (EPFL)
□ using a case study from an electricity utility□ responding to a real demand from a company□ achieving the thesis within a corporate context
■ motivation for the HTO-DSS project (Electrabel)□ need for a state of the art hydro portfolio management know-how□ introduce sophisticated approach of risk management
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
2. context■ deregulation of ancient monopoly■ presence of a liberalized market (from cost min to revenue max)■ presence of spot and financial markets (risk management tools)■ variety of production technologies (thermal, hydro, wind,…)■ presence in different countries (wide interconnected geographical
position)■ approaching the 2007 fully liberalized electricity market (one
market place widely interconnected)■ different market attitudes of the player (market maker, price taker)■ definition of a global risk policy and a asset portfolio specific policy
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
3. problem definition (1/2)asset optimization under specific risk framework
hydro plants
thermal plants
fuel contracts
FR BE.NE.LUX DEasset portfolio
electricity prices
fuel prices
inflows
r i s k f r a m e w o r k
revenues
maintenance
production
hedging
risk map
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
3. problem definition (2/2)■ this problem is formulated as follows:
we need to create a decision support system (DSS) in order to:□ optimize (maximize the value) the asset portfolio value□ exposed to electricity and fuel price and inflow availability uncertainty□ under risk constraints
■ the following sub-problems are identified:1. define a risk framework that has to be:
• Corporate wide• Asset specific
2. implement hydro-thermal optimization in a liberalized market under the above mentioned risk framework
3. analyze the interactions of player’s market attitude on each country and define the appropriate strategy
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
4. main milestones of the thesis1. consideration of a part of the portfolio were we will stretch the
issues of:■ development and calibration of the hydro-thermal optimization
algorithm■ development of the methodology for the risk framework definition■ development of the portfolio management methodology
2. consideration of the total portfolio were we will stretch the issues of:■ applicability of the above algorithm in the fuel contract portfolio■ implementation of the above methodologies to the total portfolio
3. analysis of the player's market attitude and the interaction between the markets
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestones presentation1. hydro-thermal portfolio consideration and development of risk and
portfolio management methodology
2. fuel contract consideration and implementation of the above methodologies to the total portfolio
3. player’s market attitude
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 1 (hydro-thermal portfolio) (1/10)■ the portfolio considered consists of:
□ 774 MW / 1777 GWh hydro reservoir and run-of-river assets□ 375 MW of nuclear asset (no modulation)
■ the combination of the assets formsan homogenous portfolio Eget
IC: 37 MWAP: 82 GWh
LouronIC: 49 MW
AP: 87 GWh
TetIC: 49 MW
AP: 171 GWh
CapdenacIC: 29 MW
AP: 87 GWh
MaregesIC: 302 MW
AP: 427 GWh
SoulomIC: 57 MW
AP: 267 GWh
LicqIC: 24 MW
AP: 93 GWh
ArtousteHouratIC: 227 MW
AP: 563 GWh
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 1 (hydro-thermal portfolio) (2/10)■ problem description
□ hydro assets□ stochastic inflows and prices ( = decision under uncertainty)□ revenue maximization□ in forward and spot market□ under risk constraints
■ time period definition□ long term → >1year□ medium term → 1week< , 1year>□ short term → <1week
■ markets available□ forward → derivatives market with physical delivery□ spot → day-ahead hourly auction□ balancing market→ real time market
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 1 (hydro-thermal portfolio) (3/10)■ risk management definition
we have hydro assets, with reservoirs, having high flexibility, that require dynamic portfolio management
■ risk types:□ inflow = available yearly production + intra-year distribution□ price = available yearly revenues + intra-year distribution
[m3]Or[EUR/MWh]
[weeks]
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 1 (hydro-thermal portfolio) (4/10)■ risk framework is derived from:
□ min revenues needed for the company in a CI (R@R approach)□ budget to attain based on the forecasts□ overall wish to risk exposure (risk appetite)
Rmin budget forecast riskMax0
[EUR]■ risk framework definition
□ corporate risk levels defining: Rmin□ portfolio mgt. risk levels defining: budget and risk appetite
■ risk reduction capacity□ production re-arrangement in order to concentrate in low price and
inflows distribution stages (auto-hedging capacity of the asset)□ use of financial instruments in order to “lock” a a certain price
■ the above options lead to the following trade-offs□ Rmin guaranteed vs. high risk short term revenues□ low risk mkts. vs. high risk/flex mkts.
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 1 (hydro-thermal portfolio) (5/10)■ we need to optimize the production of the assets in order to:
□ guarantee Rmin for the total portfolio□ perform asset backed arbitrage in the long term market in order to
profit from the forward market price distortions□ sell the high flexibility of the asset in the short term and real time market
[EUR]
Flexibility
Asset Backed Arbitrage
Minimum revenuestimePresent Future
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 1 (hydro-thermal portfolio) (6/10)■ main trade-off is:
use the water of the reservoir now (immediate benefit) or “tomorrow” (future benefit)
[EUR]
immediate operating
benefit
future operating benefit
final reservoir level
■ the algorithm used to solve this problem is based on the Stochastic Dual Dynamic Programming (SDDP) technique where:□ the sum of the immediate and future benefit is maximized□ for every stage (…, week, month, …)□ calculating a policy table (future benefit function) for every stage□ by approximating this function with lines (Bender’s cuts)
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 1 (hydro-thermal portfolio) (7/10)■ input
□ inflow scenarios qt
□ water level on reservoirs Vt
□ spot price scenarios Πd
□ minimum revenues guaranteed @ confidence interval Rmin_Rφ
■ output□ production schedule Ut□ allocation in the markets et, Ec□ risk view of the portfolio□ hedging strategy
HTO.SDDP ■ Input: Vt, qt, Πdt, Rmin_Rφ
■ Output: Ut, et, Ect
MaxRev Optfolio
HTO.SDDP ■ Input: Vt, qt-1, Πdt, Rmin_Rφ
■ A. Output: UtB. Output: et, Ect
OR
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 1 (hydro-thermal portfolio) (8/10)■ preliminary results
□ for the hydro system□ spot market (no derivatives market)□ no risk constraints (no minimum revenues guaranteed)
total production cdf total revenues cdf
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 1 (hydro-thermal portfolio) (9/10)■ preliminary results
weekly generation distribution
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 1 (hydro-thermal portfolio) (10/10)■ following steps
□ model calibration considering risk constraints and use of derivative products (forwards)
□ risk allocation on the assets defining the portfolio□ modeling of the short-term trade-off between spot and balancing
market
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestones presentation1. hydro-thermal portfolio consideration and development of risk and
portfolio management methodology
2. fuel contract consideration and implementation of the above methodologies to the total portfolio
3. player’s market attitude
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 2 (total portfolio) (1/2)■ the total portfolio will be considered
■ the following technologies will be considered within the portfolio:□ coal production plants□ gas production plants□ hydro production plants□ nuclear production plants
■ the following developed market structures will be considered:□ France□ Netherlands□ Germany
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 2 (total portfolio) (2/2)■ additional factors to be considered:
□ thermal plants with considerable flexibility□ fuel price uncertainty□ optimization of fuel contracts
■ the total portfolio will be optimized taking into consideration the synergies between:□ the interconnected countries (different price areas)□ the complementarities of the technologies□ the allocation of the risk in the total portfolio (cross-hedging capacity)
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestones presentation1. hydro-thermal portfolio consideration and development of risk and
portfolio management methodology
2. fuel contract consideration and implementation of the above methodologies to the total portfolio
3. player’s market attitude
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 3 (player’s market attitude) (1/2)■ we need to consider:
□ presence in 4 markets (Belgium, Netherlands, France and Germany)□ with fully developed market structure (not Belgium)□ having high degree of interconnection□ and different importance of the player’s presence at each market
■ we can identify 3 main market attitudes□ market maker offering both sides of the curve□ important player influence on prices□ price taker “takes” the price that the market defines
■ according to each attitude the player develops a different strategywhich applies to each market
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
5. milestone 3 (player’s market attitude) (2/2)■ we need to define:
□ the strategy of the player for each market□ the interaction of the markets according to the player’s action□ the synergies of the markets to the player’s strategy for:
• portfolio management• risk management
12
12
HYDRO THERMAL OPTIMIZATIONdecision support system
Niko A. ILIADIS
6. résumé■ new-coming factors:
□ liberalized electricity markets with a variety of products□ introduction of the electricity price uncertainty□ increase of interconnection degree within countries/markets
■ impose to the electricity asset industry a new approach concerning:□ the portfolio management
• optimization of the assets• synergies between assets
□ the risk management• exploiting the auto-hedging capacity of the assets• using financial products
□ the strategic position of a player at each market• bidding strategy in the market• optimal market share