Spot electricity markets are considered under a Game-Theoretic framework, where risk averse players submit orders to the market clearing mechanism to maximise their own utility. Consistent with the current practice in Europe, the market clearing mechanism is modelled as a Social Welfare Maximisation problem, with zonal pricing, and we consider inflexible demand, physical constraints of the electricity grid, and capacity-constrained producers. A novel type of non-parametric risk aversion based on a defined worst case scenario is introduced, and this reduces the dimensionality of the strategy variables and ensures boundedness of prices. By leveraging these properties we devise Jacobi and Gauss-Seidel iterative schemes for computation of approximate global Nash Equilibria, which are in contrast to derivative based local equilibria. Our methodology is applied to the real world data of Central Western European (CWE) Spot Market during the 2019-2020 period, and offers a good representation of the historical time series of prices. By also solving for the assumption of truthful bidding, we devise a simple method based on hypothesis testing to infer if and when producers are bidding strategically (instead of truthfully), and we find evidence suggesting that strategic bidding may be fairly pronounced in the CWE region.
翻译:根据游戏理论框架考虑点电市场,风险偏好者向市场清理机制提交订单,以最大限度地发挥其自身的效用。根据欧洲目前的做法,市场清理机制仿照社会福利最大化问题,采用地区定价,我们考虑不灵活的需求、电力网的有形限制以及能力限制的生产商。引入了一种新型的非参数风险规避,基于界定的最坏情况假设,这降低了战略变量的维度,确保了价格的界限。我们利用这些属性设计了Jacobi和Gaus-Seidel迭接机制,用于计算全球近似Nash Equilibria的近似 Nash Equilibria,这与基于衍生品的本地均衡形成对照。我们的方法适用于2019-2020年期间中欧(CWE)光市场的真实世界数据,并很好地反映了历史时序的价格。通过解决假设真实性投标,我们根据假证测试设计了一个简单的方法,用以推断生产者是否和何时进行战略招标(而不是真实的),我们发现战略招标可能正确无误的证据。