Das heutige Leben ist ohne Elektrizität nicht mehr vorstellbar. Fossile Brennstoffe auf unserer Erde gehen spätestens mittelfristig zur Neige. Und noch immer steigt der jährlich Energiebedarf in den Industrie- und Schwellenländern. Kohlekraftwerke produzieren den billigsten Strom, auf Kosten der Umwelt. Die Popularität der Kohle- und Kernkraftwerke in der Bevölkerung schwindet. Solar- und Windenergie ist in aller Munde. Es mangelt jedoch an intelligenter Regelung der verschiedenen Energieerzeuger, um Über- und Unterkapazitäten in der Elektrizitätsversorgung abzufangen.

Übersetzung folgt...

Germany is said to produce almost 25% of its total electricity from wind and sun. Knowing that especially wind is only available at random times during the day, the resulting power generation peaks and lows are challenging German power distributors. Fossil and nuclear power plants have limited capabilities to regulate their electricity output quickly, so that often wind and solar power plants are taken offline. New strategies are needed to cope with these challenges. 

With the liberalization of the European energy markets, stock prices vary greatly depending on current demand and energy production. During high productivity of wind power, stock prices may drop below production costs so that power generators effectively loose money.

{modal images/green-orca/energy/electricity_prod_stockprice_jan2014.png|title=German Electricity Production by resource plus corresponding stock prices (Source: Fraunhofer ISE, 2014) }{/modal}

New strategies are needed to cope with these challenges. Green-ORCA has developed a model of configurable electricity production and real-world energy consumption. The following electricity provider types are supported:

1. hydro and pumped storage hydroelectricity
2. wind plants
3. solar power plants
4. fossil and gas power plants
5. nuclear power plants

For each provider type, the number of plants can be set, as well as the amount of households cunsuming the electricity.

Productivity and controlability per provider is based on typical data, so that wind plants produce electricity at random times and solar plants only during daytime etc. Seasonal changes of daylight, productivity and consumption have been incorporated.

Our model includes various economical figures, such as end user price or production price per provider type. Market prices are predicted by demand and availability. Based on this, the profit for each provider type can be estimated for the simulated time frame.

Using this model, you can optimize the number and types of power plants required to meet the actual demand for a region or a country. Several charts display the temporal utilization of each resource type, the stock prices.

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Todo:

incorporate plant availability, desaster scenarios etc...