Offshore wind auction simulation

该EngD的目的是开发一个以新的建模方法为基础的工具，战略团队可以使用该方法在一系列场景和投入下模拟CfD拍卖。该模型的输出将允许对拍卖的动态进行研究，从而确定最优的投标策略。该模型将附有一份辅助文件，其中将包括每项战略的细节/定义，并解释各种建模假设。这一首要目标可以通过完成三个主要目标来实现。第一个目标是在现有方法的基础上，利用法国电力公司的离岸风电成本分析工具(OWCAT)来评估主要竞争竞价参与者的预期电价及其潜在收益。由于影响模型输入的不确定性来源多种多样，因此需要建立随机成本模型。这将被用来为在CfD拍卖中竞争的每个主要项目创建LCOE估计的概率分布。第二个目标是开发一种能够模拟竞争对手在拍卖中的行为的方法。不同的竞争者可以通过评估他们可能的行为(例如，考虑文化差异可能如何影响竞价策略)而被归类为不同的“拍卖类型”。该方法将利用博弈论和拍卖理论来模拟拍卖动态，通过前两个目标实现的工作将结合起来开发一个综合模型，该模型可以模拟一系列不同场景下的拍卖。该模型将利用蒙特卡罗模拟进行多次拍卖，将竞争对手预测的竞价价格的概率分布作为每次模拟中不同的数据点。最终目标是将创建的模型应用到实际项目中，以帮助EDF制定决策。

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.