The increasing integration of renewable energy sources has led to greater volatility and unpredictability in electricity generation, posing challenges to grid stability. Ancillary service markets, such as the German control reserve market, allow industrial consumers and producers to offer flexibility in their power consumption or generation, contributing to grid stability while earning additional income. However, many participants use simple bidding strategies that may not maximize their revenues. This paper presents a methodology for forecasting bidding prices in pay-as-bid ancillary service markets, focusing on the German control reserve market. We evaluate various machine learning models, including Support Vector Regression, Decision Trees, and k-Nearest Neighbors, and compare their performance against benchmark models. To address the asymmetry in the revenue function of pay-as-bid markets, we introduce an offset adjustment technique that enhances the practical applicability of the forecasting models. Our analysis demonstrates that the proposed approach improves potential revenues by 27.43 % to 37.31 % compared to baseline models. When analyzing the relationship between the model forecasting errors and the revenue, a negative correlation is measured for three markets; according to the results, a reduction of 1 EUR/MW model price forecasting error (MAE) statistically leads to a yearly revenue increase between 483 EUR/MW and 3,631 EUR/MW. The proposed methodology enables industrial participants to optimize their bidding strategies, leading to increased earnings and contributing to the efficiency and stability of the electrical grid.

翻译：可再生能源并网比例不断提高导致发电波动性和不可预测性加剧，对电网稳定性构成挑战。辅助服务市场（如德国控制储备市场）允许工业消费者和生产者通过调节用电或发电提供灵活性，在获取额外收益的同时支撑电网稳定。然而，多数参与者采用简单的竞价策略，未能实现收益最大化。本文提出一种针对按报价支付型辅助服务市场的竞价预测方法，聚焦德国控制储备市场。我们评估了包括支持向量回归、决策树和k近邻算法在内的多种机器学习模型，并与基准模型进行性能对比。针对按报价支付市场收益函数的非对称特性，我们引入偏移调整技术以提升预测模型的实际适用性。分析表明，相较于基准模型，所提方法可使潜在收益提升27.43%至37.31%。通过分析模型预测误差与收益的关联性，发现三个市场均呈现负相关关系：模型价格预测误差（平均绝对误差）每降低1欧元/兆瓦，统计上可实现年收益增长483欧元/兆瓦至3,631欧元/兆瓦。该方法能够帮助工业参与者优化竞价策略，在提升经济效益的同时促进电网运行效率与稳定性。