Simulating Bidding Behaviour on Offshore Wind Farm Tenders
A.W. Noteboom (TU Delft - Technology, Policy and Management)
Yilin Huang – Mentor (TU Delft - System Engineering)
Z. Roosenboom-Kwee – Graduation committee member (TU Delft - Economics of Technology and Innovation)
I Nikolic – Coach (TU Delft - System Engineering)
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Abstract
Over the past decade, renewable power generation through wind power has increased significantly. Especially the installation of offshore wind energy is expected to skyrocket to a total of 2000 GW by 2050. The majority of rights to develop and operate offshore wind farms are allocated through tendering procedures.
In tender procedures, interested parties issue a bid, which includes a subsidy price called strike price at which the party would be willing to accept to develop and operate the wind farm. Lower strike prices increase the chance of winning the tender. In principle, this should lead to the cost-effective deployment of wind energy. However, current wind farm tender designs have been found to cause multiple undesirable results. Understanding the behaviour of the bidding parties that leads to these flaws will help policy makers improve the design of offshore
wind farm tenders to counteract this.
Current modelling methods have failed to incorporate the influence of bounded rationality in the bidding procedure together with a realistic representation of the economic valuation of the tenders, which all bidding organisations conduct. This knowledge gap is addressed in this thesis. This thesis has performed a careful sensitivity analysis on a valuation model provided by the industry to find its influential parameters, developed a coupled model by designing an agent based model and connecting it to an economic valuation model, and conducted exploratory experimentation with the coupled model.
The work presented in this thesis is a proof of concept for using coupled modelling for socio-economic processes with a strategic component. The work contributed to the usage of model coupling in cross-disciplinary studies and encourages the research community to use coupled modelling for socio-economic processes in other domains as well.