For the case of inflexible demand and considering network constraints, we introduce a Cost Minimisation (CM) based market clearing mechanism, and a model representing the standard Social Welfare Maximisation mechanism used in European Day Ahead Electricity Markets. Since the CM model corresponds to a more challenging optimisation problem, we propose four numerical algorithms that leverage the problem structure, each with different trade-offs between computational cost and convergence guarantees. These algorithms are evaluated on synthetic data to provide some intuition of their performance. We also provide strong (but partial) analytical results to facilitate efficient solution of the CM problem, which call for the introduction of a new concept: optimal zonal stack curves, and these results are used to devise one of the four solution algorithms. An evaluation of the CM and SWM models and their comparison is performed, under the assumption of truthful bidding, on the real world data of Central Western European Day Ahead Power Market during the period of 2019-2020. We show that the SWM model we introduce gives a good representation of the historical time series of the real prices. Further, the CM reduces the market power of producers, as generally this results in decreased zonal prices and always decreases the total cost of electricity procurement when compared to the currently employed SWM.
翻译:对于不灵活的需求和网络制约,我们引入基于成本最小化的市场清算机制(CM)基于成本最小化(CM)的市场清算机制,以及代表欧洲日头电力市场使用的标准社会福利最大化机制的模式。由于CM模式与更具挑战性的优化问题相对应,我们提议四种数字算法,利用问题结构,在计算成本和趋同保证之间作出不同的权衡。这些算法根据合成数据进行评估,以提供其性能的一些直觉。我们还提供了强有力的(但部分的)分析结果,以促进有效解决CM问题,这要求引入一个新的概念:最佳区堆曲线,这些结果用于设计四种解决方案中的一种。根据真实的招标,对CM和SWM模式及其比较进行了评估。根据2019-2020年期间中西欧日头电力市场的真实世界数据进行了评估,我们介绍的SWM模式很好地反映了实际价格的历史时间序列。此外,CM将目前生产者的市场实力降低到目前的市场总价格,因为总体而言,在SWM采购中,电价不断下降。