7 April 2013:
 
New Simulation Tool Developed

There is a great interest in following the German power sector. The current changes in Germany ("Die Energiewende") require special tools for the evaluation of the prospects for the next few years.

A Dispatch Model of German Power Production
The model covers the years 2010 to 2020. The tool simulates the hourly production 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 pump 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 a series of years between 2010 and 2020. 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 following tables have been selected:
 -  Annual production
 -  Annual capacity factor
 -  Installed capacity
 -  Marginal cost depending on fuel prices, carbon prices and other variables cost
 -  Contribution margin
 -  Price setting hours

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 discussed with the client in due course.

Opdateret d. 8.4.2013