This page contains a Flash digital edition of a book.
Optimising Power Trading
... with Actual & Model-Based Fundamental Data from the
European Power Market
By Dr. Albert Jürgen Enders & Mario Michael Schultz
T
he development and growth of financial markets has Power Generation
gone hand in hand with the need for ever improved Generation refers to the net production in terms of the level
news and data related services. Speed and provision of of power fed into the public grid. Hence, data frequently does
reliablereal-timemarketdataandanalyticshaveturnedinto not include the likes of auto-producers who operate their own
akeysuccessfactorfortradersandothermarketparticipants. power plants. Power generation data can be categorised into
In addition, information and analysis products contribute three dimensions of information depth:
decisively to more transparency in the financial markets and

Actual and historical power generation per country by type
make them more decipherable. The same applies to of fuel.Mostrelevantfueltypesincludecoal,lignite,nuclear,
commoditymarkets,wheretheneedforsophisticatedandup- gas, oil, CCGT, water, and wind.
to-date data has grown with the sophistication of the market

Actualandhistoricalpowergenerationper country per plant.
itself. A good example is the deregulation and development Datadepthtakentothenextlevelallowspowertradersand
of power markets over the last 10-15 years, with ever more analysts to fully understand the actual supply side
complexfundamentalfactorsinfluencingmarketsandprices. including the mix and costs of power production. Data
The challenge is to master the information for better should be available classified in total MW as well as
forecasting and trading performance. utilisation rate of the specific power plant; in addition it
Optimising power trading based on economic factors both should also cover the delta of change within defined time
in the spot and future markets depends on a host of periods e.g. 5 minutes, one hour and 24 hours changes.
fundamental factors. Usually, these factors can be broken

UMMs (Urgent Market Messages) power plant specific. Power
down into supply-related and demand-related parameters, plant specific data is essential for short term spot market
all of which have a different impact on pricing. trading because any changes in the current power
Fundamental power trading market data includes all production due to any incident or breakdown of a specific
relevant data and information that have a direct or indirect power plant immediately affects the volume of supplied
impactonanypricequotesregardlesswhethertradedOTCor power and its price. Urgent market messages are usually
on-exchange. With power being a unique, essentially non- published by TSOs and power producers.
storable commodity, fundamental data on generation
(supply) and consumption (demand) becomes essential. Power generation data, if available intra-day and as an
Collecting and modelling such fundamental data is historical time series, are a great base for trend analysis. Data
extremely time consuming. Nonetheless, it’s an essential should be real data hence not have a model-based source.
determining factor in the price decision-making process for
powertradersandanalysts.Therealchallenge,however,isto Power Availability
receive and analyse all relevant data in real-time. With a Availability defines obtainable capacity in terms of the net
number of ongoing transparency initiatives in several powerproductionavailableforfeed-intothepublicgrid.Data
Europeancountries,so-called TransmissionSystemOperators isusuallyrequiredforgenerationpertypeoffuel,aswellasfor
(TSOs) and power producers publish large amounts of data. selected time series. Additionally, deviation data should show
Unfortunately, there is no common format – and even the the difference to the latest (previous day) report. An intra-day
type of data published is not directly comparable. update frequency can be classified into:
In an effort to consolidate and structure available

Forecast by all fuels (coal, lignite, nuclear, gas, Oil, CCGT)
European power data and to overcome the existing forshortandlong-termupto12months.Forecastsforwind
information gap Deutsche Börse’s Market Data & Analytics and water production should be separate due to external
division has recently launched a new service; Energy Facts, weather influence rather than power plant maintenance.
which allows power traders and analysts to focus on the

Forecast by plants based on current available revision and
development of pricing and risk models, together with maintenance schedules.
trading strategies based on actual and model-based
fundamental data. Load
The following section provides a general overview of some Load shows vertical load defined in terms of the total
main non-model-based fundamental data which influences amount of power flows out of the transmission network of the
power markets and is fundamental to increase performance. control area operator’s country into distribution and large
24 worldPower2009
Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78  |  Page 79  |  Page 80  |  Page 81  |  Page 82  |  Page 83  |  Page 84  |  Page 85  |  Page 86  |  Page 87  |  Page 88  |  Page 89  |  Page 90  |  Page 91  |  Page 92  |  Page 93  |  Page 94  |  Page 95  |  Page 96  |  Page 97  |  Page 98  |  Page 99  |  Page 100  |  Page 101  |  Page 102  |  Page 103  |  Page 104  |  Page 105  |  Page 106  |  Page 107  |  Page 108  |  Page 109  |  Page 110  |  Page 111  |  Page 112  |  Page 113  |  Page 114  |  Page 115  |  Page 116  |  Page 117  |  Page 118  |  Page 119  |  Page 120  |  Page 121  |  Page 122  |  Page 123  |  Page 124  |  Page 125  |  Page 126  |  Page 127  |  Page 128  |  Page 129  |  Page 130  |  Page 131  |  Page 132  |  Page 133  |  Page 134  |  Page 135  |  Page 136  |  Page 137  |  Page 138  |  Page 139  |  Page 140  |  Page 141  |  Page 142  |  Page 143  |  Page 144  |  Page 145  |  Page 146  |  Page 147  |  Page 148  |  Page 149  |  Page 150  |  Page 151  |  Page 152  |  Page 153  |  Page 154  |  Page 155  |  Page 156  |  Page 157  |  Page 158  |  Page 159  |  Page 160  |  Page 161  |  Page 162  |  Page 163  |  Page 164
Produced with Yudu - www.yudu.com