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Optimising Power Trading
Figure1: GenerationFrom7DaysPower–Germany:05.05.09–11.05.09
Source: Deutsche Börse Energy Facts: Shows a seven days power generation history for Germany by fuel type
consumer networks (as well as wind energy output and comparing the price difference between two exchanges e.g.
consumption forecast). This type of data can be classified in: theGerman(EEX)andFrench(Powernext)spotmarketprices

Vertical load of all TSOs in one country separated by TSO tothecapacitypriceoftheday-aheadcross-borderauctionin
and as a total. For instance, Germany has four TSOs while anhourlyresolution.Datashouldbeupdateddaily.
others (e.g. The Netherlands) have only one.

Inaddition,thesumoftheproducedwindenergywithinthe Cross-borderdataneedstobecollectedandaggregatedfrom
grid zones of all control area operators can be added to the many different sources and needs to be analysed in single as
total vertical load that indicates total consumption. Data well as in a compound format (Figure 3).
needs to be updated in real-time and it is most relevant to Next to relevant non-modelled fundamental power market
have an intra-day picture of current power production. data, fundamental modelled data is equally important
becausesimplehumanforecastthinkingisnoteffectivedueto
Cross-Border multi parameter influences. Hence, the focus here is on
Analysis of European power market cross-border fundamental data models and not on price forecasts. The
transmission is extremely important. Capacities and transfer following fundamental model-based forecasting data are
prices at coupling points is available so that cross-border relevant for power analysts and traders:
fundamental data can be sorted as follows:

Temperature forecasts: pure fundamental models e.g.

Dataonavailable,requestedandallocatedcapacityaswell HIRLAM, MOS.
asthecapacitypriceinEUR/MWhfortherelevantborderon

Wind energy forecasts: fundamental model with output in
aday-aheadbasisinanhourlyresolution.Itisimportantto MW/h.
aggregate all data for cross-border.

Power consumption forecast: statistical multi-factor and

Separately for each country border e.g. France-Germany, fundamental model with output in MW/h.
France-Belgium, etc.

CO
2
consumption prognosis: statistical and fundamental

Separately for both directions e.g. France-Germany and model.
Germany-France.

Data on short, mid and long term net transfer capacity TemperatureForecast
(NTC) as well as available transport capacity (ATC) for: Most power traders and analysts define temperature as the
day+1, day+2, month, year. key demand-side fundamental parameter. Temperature

Day ahead cross-border arbitrage opportunities by forecasts are model-based and should be defined as follows:
Figure2: VerticalLoadForAll4GermanTSOs–90Days,12.02.09–12.05.09
Source: Deutsche Börse Energy Facts:
worldPower2009 25
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