Offshore wind auction simulation

Lead Research Organisation: University of Edinburgh
Department Name: Sch of Engineering


The aim of this EngD is to develop a tool underpinned by a novel modelling approach which can be used by strategy teams to simulate CfD auctions under a range of scenarios and inputs. The outputs from the model will allow for the dynamics of the auction to be studied, allowing for an optimum bidding strategy to be determined. The model will be accompanied by a supporting document which will include details / definitions of each strategy and explain the various modelling assumptions. This overriding aim can be achieved through completion of three main objectives.
The first objective is to build on existing methodologies which utilise EDF's Offshore Wind Cost Analysis Tool (OWCAT) to assess the expected electricity prices of major competing auction participants and their potential yields. Since there are a variety of sources of uncertainty affecting the model inputs, stochastic cost modelling is required. This will be used to create a probability distribution of LCOE estimates for each of the major projects competing at CfD auction.
The second objective is to develop a methodology which can simulate a competitor's behaviour at auction. Separate competitors can be categorised into different 'auction types' through assessing their likely behaviour (e.g. considering how cultural differences may affect bidding strategies). The methodology will make use of game theory and auction theory to simulate auction dynamics.
Work achieved through the first two objectives will be combined to develop a comprehensive model, which can model the auction under a range of different scenarios. The model will make use of Monte Carlo simulation to run the auction many times, using the probability distribution of competitors predicted bid price as different data points in each simulation. The final objective is to implement the created model into a live project to assist in decision making at EDF.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S023933/1 30/09/2019 30/03/2028
2274617 Studentship EP/S023933/1 31/08/2019 30/08/2023 Nicholas Kell