The tool simulates the hourly production for up to 11 years based on a merit order list. It requires four main inputs. These are electricity gross consumption, Wind and PV output, dispatchable capacity and commodity prices. The hourly variations are based on time series for consumption, wind power and photovoltaic (PV).

A residual load is created by subtracting wind and PV from the consumption.

The residual load has a rather irregular variation which is smoothed by available pumping storage capacity.

The dispatchable capacity is used for covering the resulting residual load in accordance with the merit order list.

Extreme cases with electricity overflow or shortage may occur. Such cases are assumed balanced by export and import. The model does not identify or analyze congestion problems in the grid.

Several Data Sources
Comprehensive analyses on the German power system have been published such as the BMU 'Lead Study 2010' (Federal Ministry for the Environment, Nature Conservation and Nuclear Safety), the BMWI 'Energy Scenarios 2011' (Federal Ministry of Economics and Technology) and the ENTSO-E System Adequacy Forecast 2012-2025. Several other studies and data sources have been used.

It has been a time consuming puzzle to evaluate all these sources and to extract a consistent set of data for use in the model. The different sources reflect an increased uncertainty due to the German energy transition.

Selecting Main Results
The tool simulates up to 11 years between 2010 and 2050. After a simulation a large amount of data is available. Some characteristic data have been selected as standard output.

For each year a mean marginal cost indicates the electricity price level. Price volatility is indicated by a standard deviation.

Other results for each year are:

-	The energy balance including pump storage losses
-	Average capacity factor for dispatchable production
-	Total CO2 emission in million tons and in kg per MWh consumed
-	Overflow and shortage specification

For each category of dispatchable capacity the output tables include:

-	Annual production
-	Annual capacity factor
-	Installed capacity
-	Marginal cost depending on fuel prices, carbon prices and other variables cost
-	Contribution margin
-	Total contribution
-	Price setting hours
-	Fuel consumption

For each type of fuel the output tables include:

-	Annual production
-	Annual capacity factor
-	Consumption
-	CO2 emission

Selected charts are shown on a separate sheet. The purpose is to help understanding the results. The residual load density function demonstrates the influence of wind and PV. The residual load density function can be combined with the merit order curve for dispatchable production:

The charts above tell a story about a power system facing new challenges. The maximum residual load is at the same level, but the result of negative loads is overflow from the power system concerned. Simultaneous overflow in interconnected countries may create negative market prices. This has been observed in Germany.

Most power systems must maintain a certain minimum of dispatchable capacity connected to the grid. Reasons can be operational constraints for certain power plants (nuclear and biomass fired units) or reserve requirements to secure grid stability. It is possible to specify a minimum dispatchable capacity in the model. The overflow will increase correspondingly.

Other charts are capacity factors, duration curves and a detailed output hour by hour for a selected day.

Opportunities for further Development
Due to the data uncertainty there are very good reasons for observing the development in Germany in the next few years. The observations can be used for regular data adjustments.

The model itself has interesting potentials for improvements and extensions which will be considered as needed.