This paper presents a novel agent-based, stochastic model, which uses game-theoretic principles to simulate Contract for Difference (CfD) auctions. The framework has use cases and implications for policymakers and renewable generators alike. The model is demonstrated by replicating the CfD Allocation Round 3 (AR3) held in 2019. The ...
This paper presents a novel agent-based, stochastic model, which uses game-theoretic principles to simulate Contract for Difference (CfD) auctions. The framework has use cases and implications for policymakers and renewable generators alike. The model is demonstrated by replicating the CfD Allocation Round 3 (AR3) held in 2019. The simulation shows that the strike prices agreed at auction could have been predicted with reasonable confidence by developers (within a 5% margin). The award of subsidies in this auction do not strictly follow the estimated merit order of projects. This may highlight potential auction inefficiencies as some players may have successfully won through strategic bidding. Results show that the transmission network and grid connection charges are a significant barrier for projects in some geographical regions to be awarded a CfD contract, potentially hindering renewable deployment in those areas. Moreover, the model shows that players can attempt to optimise their bids based on expected profit. Results show that a 1200 MW wind farm development can increase potential profits by £135 million over the CfD contract length in exchange for a 25 p.p. chance reduction in being awarded a subsidy.
