With the increasing integration of power plants into the frequency-regulation markets, the importance of optimal trading has grown substantially. This paper conducts an in-depth analysis of their optimal trading behavior in sequential day-ahead, intraday, and frequency-regulation markets. We introduce a probabilistic multi-product optimization model, derived through a series of transformation techniques. Additionally, we present two reformulations that re-frame the problem as a mixed-integer linear programming problem with uncertain parameters. Various aspects of the model are thoroughly examined to observe the optimal multi-product trading behavior of hydro power plant assets, along with numerous case studies. Leveraging historical data from Nordic electricity markets, we construct realistic scenarios for the uncertain parameters. Furthermore, we then proposed an algorithm based on the No-U-Turn sampler to provide probability distribution functions of cleared prices in frequency-regulation and day-ahead markets. These distribution functions offer valuable statistical insights into temporal price risks for informed multi-product optimal-trading decisions.

翻译：随着发电厂日益融入频率调节市场，优化交易的重要性显著提升。本文对发电厂在序贯日前、日内及频率调节市场中的最优交易行为进行了深入分析。我们通过一系列变换技术推导出一种概率化多产品优化模型，并提出了两种将问题重构为含不确定参数的混合整数线性规划的重构形式。通过全面检验模型的多维度特性，结合大量案例研究，观察了水力发电资产的最优多产品交易行为。利用北欧电力市场的历史数据，我们为不确定参数构建了实际场景。此外，基于无U型采样器提出一种算法，用于生成频率调节与日前市场出清价格的概率分布函数。这些分布函数为明智的多产品最优交易决策提供了关于时间价格风险的宝贵统计洞察。