Realising Transition Pathways

Wedge C

Systems and network modelling and evaluation

Wedge C will develop a set of interacting tools to enable optimisation of electricity network infrastructure investment and operational decisions, under the different pathways.

Separate tools developed in phase 1 to evaluate future energy pathways in the distribution and transmission networks produced valuable results.However there is a need for detailed evaluation across the broad range of interactions, at different spatial and temporal scales.

The high level analysis of 'branching points' also revealed the requirement to integrate these tools to enable a more holistic analysis of future energy systems of transmission, distribution and hybrid energy networks.

Through a second and complementary set of tools the consortium will model decisions to invest in the range of fossil and low carbon generation, taking into account market design, different subsidy mechanisms and  alternative pricing arrangements that may impact plant location.

The proposed method will jointly optimise investment decisions and conduct an hourly chronological dispatch of installed generation capacity. This feature ensures 'incentive compatibility', so that all generators selected by the model to come onto the system (or remain on it) will earn sufficient revenues to cover their costs.

WP C1: Integrated energy networks modelling and evaluation

WP C1 will further develop the engineering analysis tools and techniques for energy network issues, and apply them in a number of ways:

  • Stress testing the pathways and branching points
  • More deeply understanding the interactions of the technologies, actors, key societal drivers and governance approaches with the required network developments
  • Exploring alternative business models and the resilience of the pathways.

Work will be carried out by Strathclyde University.

WP C2: Realising Transition Pathways within alternative market and policy contexts 

WP C2 will model decisions to invest in fossil fuel, renewables and other low carbon generation, taking into account market design, different types of subsidy mechanisms and alternative forms of network pricing arrangements that may impact plant location.

The Consortium will also model investment decisions in the presence of particular risk profiles associated with different renewable generation technologies, taking account of resource potential, build rate constraints, location and costs.

To accurately reflect private investors' decision-making rules for generation assets, account will also be taken for  the time horizon over which they will expect to operate, and earn  a return on their upfront investments.

Monte Carlo simulation will be applid to assess the uncertainty in earnings of plants of different technologies.

Work will be carried out by Imperial College London.