the energy markets - ecmwfthe energy markets zmajor global player in metals, polymers, gas, oil and...
TRANSCRIPT
Use and interpretation of medium to extended Use and interpretation of medium to extended range productsrange products
ECMWF, Reading, 14th of November 2005
drs. Stefan Meulemans, MSc
Sempra Energy Europe Ltd.
London
The Energy Markets
Major global player in metals, polymers, gas, oil and electricity markets
Offices in New York, London, Houston, San Diego, Singapore, Geneva, Calgary and Toronto
Sempra Energy Europe Ltd.Sempra Energy Europe Ltd.
Speculative trading on gas, oil and electricity marketsUsing information to anticipate market movesWeather major fundamental
Energy marketsEnergy markets
Assessing the supply and demand of the main energy sourcesDetermining a price based on all available fundamentalsOften volatile markets compared with traditional markets
Futures and forwardsFutures and forwards
Day ahead (EC)Week ahead (EC)Month Ahead (EC)Cal ahead
Daily QENOYc1 [Candle]08/03/2005 - 07/06/2005 (GMT)[Professional]
14 21 31 07 14 21 28 06 13 24 31 07Mar 05 Apr 05 May 05
PriceEUR
27.3
27.6
27.9
28.2
28.5
28.8
29.1
29.4
29.7
30.3
30.6
30.9
31.2
31.5
31.8
32.1
32.4
32.7
27
30
33
QENOYc1, Last Trade, Candle06/06/2005 31.90 32.25 31.80 32.23
Supply and demandSupply and demand
Supply and demand determine the forward electricity pricesTraded contracts are day-ahead, week-ahead, month-ahead etc.Supply: wind and hydro Demand: temperature important
Nordic marketsNordic markets
Weather crucial due to very high hydro capacityMarket very dependent on ECMWF model
Hydro Hydro
ECMWF forecasts have to be transposed into a precipitation energy forecastWe also need an estimate of the snow cover and the expected melt, based on the temperatureAlps, Pyrenees and Scandinavia
Hydro Reservoirs ScandinaviaHydro Reservoirs Scandinavia
Example Q106 Nord PoolExample Q106 Nord PoolDaily QENOQc1 [Candle, MA 14, WMA 14, EMA 14, RSI 14, RSIMA 14,14]
13/06/2005 - 14/11/2005 (GMT)[Professional]
17 27 04 11 18 25 01 08 15 22 29 05 12 19 26 03 10 17 24 31 07 14Jun 05 Jul 05 Aug 05 Sep 05 Oct 05 Nov 05
PriceEUR
37
38
39
41
42
43
44
45
40
QENOQc1, Last Trade, Candle10/11/2005 39.00 39.15 38.70 39.10QENOQc1, C lose(Last Trade), MA 1410/11/2005 38.84QENOQc1, C lose(Last Trade), W MA 1410/11/2005 38.65QENOQc1, C lose(Last Trade), EMA 1410/11/2005 38.91
Dry weather in NordicDry weather in Nordic……Cal 03 in 2002
0.0050.00
100.00150.00200.00250.00300.00350.00400.00
02/0
1/20
02
02/0
2/20
02
02/0
3/20
02
02/0
4/20
02
02/0
5/20
02
02/0
6/20
02
02/0
7/20
02
02/0
8/20
02
02/0
9/20
02
02/1
0/20
02
02/1
1/20
02
02/1
2/20
02
Wet weather in NordicWet weather in Nordic……Cal 05 in 2004
150.00
170.00
190.00
210.00
230.00
250.00
270.00
290.00
02/0
1/20
04
02/0
2/20
04
02/0
3/20
04
02/0
4/20
04
02/0
5/20
04
02/0
6/20
04
02/0
7/20
04
02/0
8/20
04
02/0
9/20
04
02/1
0/20
04
02/1
1/20
04
02/1
2/20
04
ECMWF Nord PoolECMWF Nord Pool
Data is directly given in GWh. One run moves the market. Ensemble very important.
Countries around Pyrenees and Alps only influenced by major hydro events, as wind and non-renewable power production is more widely used
Example Point Carbon Example Point Carbon
Precipitation energy and date Histogram precipitation energy total
NAO outlook NAO outlook
Development of Nordic NAOECMWF data day 10 or beyond to calculate the NAOCurrent NAO value known, so not of interest
Nordic NAO day 10 based on EC ensemble (12Z and 00Z)
-2-1012345
19/1
0/20
05
22/1
0/20
05
25/1
0/20
05
28/1
0/20
05
31/1
0/20
05
03/1
1/20
05
06/1
1/20
05
09/1
1/20
05
ECMWF cluster outlookECMWF cluster outlook
WindWind
Short range deterministic –storms!Mid range ensemble ECMWF
Installed wind capacity
Wind production forecastsWind production forecasts
Short term models for day-ahead wind production. Error should be low.First days deterministic ECMWF modelFurther ahead ensemble ECMWFProbabilistic wind forecast?Germany, Denmark and SpainUnit MWh/h
Example Point CarbonExample Point Carbon
Wind production in MWh and date
TemperatureTemperature
Very well correlated to heating and cooling demandWater temperature forecasts with ECMWF data Development of demand outlooks
Point Carbon example
Cold spell and NBP gasCold spell and NBP gasDaily QGA2NB [Line, EMA 14, MA 14, WMA 14, RSI 14, RSIMA 14,14]
21/06/2004 - 21/11/2005 (GMT)[Professional]
Jul Sep Nov Jan Mar May Jul Sep Nov2004 2005
PriceGBp
25
35
45
55
65
75
85
95
105
20
30
40
50
60
70
80
90
100
110
QGA2NB, C lose(Last Trade), Line10/11/2005 46.00QGA2NB, C lose(Last Trade), EMA 1410/11/2005 39.97QGA2NB, C lose(Last Trade), MA 1410/11/2005 37.67QGA2NB, C lose(Last Trade), W MA 1410/11/2005 40.66
Day ahead German electricityDay ahead German electricityDaily QDE-B-1D=RWEE [Line]
21/12/2004 - 08/06/2005 (GMT)[Professional]
03 17 31 14 28 14 28 11 25 09 23 06Dec 04 Jan 05 Feb 05 Mar 05 Apr 05 May 05
PriceEUR
20
40
60
80
0
100
QDE-B-1D=RWEE, Close(Last Quote), Line06/06/2005 42.00
Demand modelsDemand models
Main variable temperature
Demand industry and basic load
Day of the week and holidays
In case of electricity hourly load calculation
SempraSempra’’ss gas modelgas model
223.5
0
221.0
9
234.8
0
207.5
0
220.0
3
226.3
5
197.4
8
188.1
0 191.5
8
207.6
4
216.6
0
217.3
0 220.5
9
219.8
4
170
180
190
200
210
220
230
240
250
11-Ju
n
12-Ju
n
13-Ju
n
14-Ju
n
DA - 15
-Jun
BOW -
16-Ju
nBOW
- 17
-Jun
WE - 1
8-Jun
WE - 1
9-Jun
WDNW
- 20-J
unW
DNW - 2
1-Jun
WDNW
- 22-J
unW
DNW - 2
3-Jun
WDNW
- 24-J
un
-40
-20
0
20
40
60
Oil marketsOil markets
ECMWF tropical model. New hurricane track forecast immediately moves the market.
Weekly inventories oil and natural gas make the market move. Weather data important.
Katrina and the GulfKatrina and the Gulf
Depending on track, certain oil product are influencedProbability outlook very important
Brent oil price since AprilBrent oil price since April
21 28 06 13 20 27 06 13 20 27 04 11 18 25 01 08 15 22 30 06 13 20 27 04 11 18 25 01 08 15Apr 05 May 05 Jun 05 Jul 05 Aug 05 Sep 05 Oct 05 Nov 05
PriceUScBbl
4950
5050
5150
5250
5350
5450
5550
5650
5750
5850
5950
6050
6150
6250
6350
6450
6550
6650
6750
4900
5000
5100
5200
5300
5400
5500
5600
5700
5800
5900
6000
6100
6200
6300
6400
6500
6600
6700
6800
QLCOZ5, Last Trade, Bar10/11/2005 5,651 5,675 5,566 5,583QLCOZ5, Close(Last Trade), EMA 1410/11/2005 5,832QLCOZ5, Close(Last Trade), MA 1410/11/2005 5,851QLCOZ5, Close(Last Trade), WMA 1410/11/2005 5,813
European gasoline contractEuropean gasoline contract
17 21 25 29 03 07 11 15 19 23 27 31 04 08 12 16 20 24 28 01 05 09 13 17 21 25 29 03 07 11 15 19 23 27 31 04 08Jun 05 Jul 05 Aug 05 Sep 05 Oct 05 Nov 05
PriceUSDT
510
520
530
540
550
560
570
580
590
610
620
630
640
650
660
670
680
690
710
720
730
740
750
760
770
780
790
810
500
600
700
800
QPU-1M-ARA, Last Quote, Bar08/11/2005 518.25 523.50 518.25 523.50QPU-1M-ARA, Close(Last Quote), EMA 1408/11/2005 547.06QPU-1M-ARA, Close(Last Quote), MA 1408/11/2005 541.98QPU-1M-ARA, Close(Last Quote), WMA 1408/11/2005 538.22
Emissions marketEmissions market
Emission markets originated from Kyoto agreementEach country has a maximum allowance to emit CO2
If country emits more than allowed, it has to buy allowances, and vice versa
Emissions marketEmissions market
Weather also important to anticipate emissions output
ECMWF data can be translated in expected C02 output from power stations
Emissions marketEmissions marketDaily QCFIZ5 [Line, EMA 14, MA 14, WMA 14, RSI 14, RSIMA 14,14]
27/04/2005 - 14/11/2005 (GMT)[Professional]
04 11 18 25 02 09 16 23 30 07 14 21 28 04 11 18 25 02 09 16 23 30 07 14 21 28 04 11May 05 Jun 05 Jul 05 Aug 05 Sep 05 Oct 05 Nov 05
PriceEUc
1350
1450
1550
1650
1750
1850
1950
2050
2150
2250
2350
2450
2550
2650
2750
2850
2950
3050
1300
1400
1500
1600
1700
1800
1900
2000
2100
2200
2300
2400
2500
2600
2700
2800
2900
3000
3100
QCFIZ5, Close(Last Trade), Line10/11/2005 2,265QCFIZ5, Close(Last Trade), EMA 1410/11/2005 2,202QCFIZ5, Close(Last Trade), MA 1410/11/2005 2,178QCFIZ5, Close(Last Trade), WMA 1410/11/2005 2,189
Weather derivativesWeather derivatives
Directly linked to weather outlook. Trading HDD, CAT and precipitation indices.
Weather markets about to develop significantly
Weather derivatives also important to hedge other energy contracts
Converting data in HDDConverting data in HDD
Sempra directly converts the model data in different possible scenario’s for HDD and CAT.
Mid- and long-range forecasts all needed
Risk management Risk management Use of long-term probabilistic outlooks
Assess risk of certain energy scenario’s
Try to have view on weeks- and months-ahead
Probabilistic longProbabilistic long--range outlookrange outlook
Reduced risk on mid-range positionsNow particularly for temperature and precipitation, but wind would be interesting tooWhen signal is strong, it makes sense to take significant long or short positions
SummarySummary
Mid- to long-range model data very relevant to different energy commodities
Importance of also considering the energyindustry when models would be enhanced. E.g. probabilistic data
Development of 30-days ensembles wouldinteresting