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In order to find decisions in finance, regulations, politics including long term strategies for the electricity system and strategic planning on the industrial side, a holistic view on the overall energy system and markets is required at different levels of detail. These include mainly aggregated regional views of:

  • power production units (differentiated according to technologies)
  • electricity networks (AC/DC)
  • weather predictions and renewable feed in
  • demand forecasts (industry, trade sector, households)

and in different representations of markets (long term, spot, intraday, balancing) and participants producers (including productions of renewables)

  • network operators
  • consumers including demand side management
  • policy and regulations
  • traders and aggregators

The aim of a system modelling approach is to investigate the development of the system with respect to different time levels and corresponding questions.

Strategic (10-50 years):

On the strategic side problems of interest are:

for policy makers

  • development of long term pathways to energy transition
  • defining long term targets of the electricity system depending on e.g. climate, emission and renewable targets
  • sensitivity analysis and system security aspects
  • investiagtions of different policy designs on their impact on the system

for producers

  • the perspective of long term market and general technology development
  • the effects of support schemes on the profitability of (renewable) production
  • the influence of political regulations and targets on the energy system
  • long term strategic portfolio effects

Tactical (1-10 years):

for policy makers and regulators:

  • system security  and reserve capacities

for producers

  • influence of regulations and market rules on dispatch
  • influence on the political debate and market design issues

for traders and industries

  • medium term portfolio effects including long term bilateral contracts

Operational:

network operators and regulators:

  • influence of balancing of uncertainties in renewable feed-in and demand

producers:

  • predictions of market development and revenues depending on weather and demand forecasts
  • support of optimal dispatch decisions
  • assesment of uncertainies and risks

marketeers:

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