Barbara Tolić, HEP Trgovina d.o.o. SEECOFF-10 20.-21.11.2013., Belgrade.

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Presentation transcript:

Barbara Tolić, HEP Trgovina d.o.o. SEECOFF , Belgrade

HEP Group

HEP Trade Ltd Optimization of power plants operation and trading intermediation in the domestic and international market Midterm planning – a week up to a year ahead Short term planning – day ahead up to a week ahead Intraday planning – hourly re-planning Electricity trading Goal – profit maximization of entire HEP Group in consideration with power system needs

Users of meteo and hydro data in HEP Group Temperatures (°C) Cloud cover (%) Precipitation(mm) Wind direction(°) Wind speed (m/s) Humidity (%) Dew point (°C) Fog (%) Low clouds (%) Middle clouds (%) High clouds (%) Pressure (hPa) Inflow (m³/s) Hourly forecasts and hourly historical data Evaporation (m³/s) Satellite maps Radar maps Lightning maps

Installed generation capacities in Croatia Hydro power plants

Energy balance in Croatian power system GWh

Renewables in Croatia Generation capacity Wind205,95 MW Other31,05 MW Total237 MW

Midterm planning Very deterministic Seasonal planning Weekly and monthly planning

Midterm planning - seasons Energy consumption forecasts Large reservoirs management strategy – depending on long term precipitation forecasts Fuel purchase and management (coal, natural gas and oil) Guidelines for maintenance planning Generation (hydro and thermal power plants) Transmission system Long term trade

Weather forecast - seasonal Input data for planning Temperature trends (normal, unusualy hot/cold) Forecasts for regional capitals Zagreb, Split, Rijeka and Osijek Precipitation (normal, dry or wet year/season) Regional capitals and river basins

Midterm planning – weekly and monthly Electric energy consumption curves – very dependant on weather Smaller reservoirs management strategy All but two of our reservoirs fall into this category Torrential rivers – reservoirs have a high risk of overflow Run-of-river power plants – daily reservoirs Renewables planning (wind farms and solar power plants) Short term electricity trading plan

Weather forcasts – weekly and monthly days ahead meteograms Daily temperature (average, high, low) Precipitation (quantity and type) Clouds and fog (big influence on energy consumption) Relative moisture Wind speed and direction Regional capitals (especialy on the Adriatic coast) Wind farm locations Extreme weather conditions (storms, floods)

Forecast interpretation Our planning – very deterministic Weather forecasts – probabilistic Problem – we need quantitative input data How to interpret probabilistic weather forecasts? {probability, interval, quantity}  {quantity, reliability}?

Thank you!