标题： 利用异步跨境市场数据改进欧洲市场的日前电力价格预测 显示英文标题

标题： Leveraging Asynchronous Cross-border Market Data for Improved Day-Ahead Electricity Price Forecasting in European Markets

摘要： 准确的短期电价预测对于在日前市场中战略性地安排需求和发电投标至关重要。 尽管数据驱动的技术近年来在实现高预测准确性方面表现出色，但它们严重依赖输入协变量的质量。 在本文中，我们研究了由于某些投标区域不同的闸门关闭时间（GCT）而异步发布的电价，是否可以提高其他具有较晚GCT市场的预测准确性。 使用最先进的模型集成，我们发现在包含具有较早GCT的互联市场（德国-卢森堡、奥地利和瑞士）的电价数据时，比利时（BE）和瑞典投标区域（SE3）的预测准确性分别提高了22%和9%。 这种改进在一般和极端市场条件下都成立。 我们的分析还提供了进一步的重要见解：频繁的模型重新校准对于最大准确性是必要的，但会带来显著的额外计算成本，而且使用更多市场的数据并不总能带来更好的性能——我们通过预测模型的可解释性分析深入探讨了这一事实。 总体而言，这些发现为旨在优化日益互联和波动的欧洲能源市场中的投标策略的市场参与者和决策者提供了有价值的指导。 显示英文摘要

摘要： Accurate short-term electricity price forecasting is crucial for strategically scheduling demand and generation bids in day-ahead markets. While data-driven techniques have shown considerable prowess in achieving high forecast accuracy in recent years, they rely heavily on the quality of input covariates. In this paper, we investigate whether asynchronously published prices as a result of differing gate closure times (GCTs) in some bidding zones can improve forecasting accuracy in other markets with later GCTs. Using a state-of-the-art ensemble of models, we show significant improvements of 22% and 9% in forecast accuracy in the Belgian (BE) and Swedish bidding zones (SE3) respectively, when including price data from interconnected markets with earlier GCT (Germany-Luxembourg, Austria, and Switzerland). This improvement holds for both general as well as extreme market conditions. Our analysis also yields further important insights: frequent model recalibration is necessary for maximum accuracy but comes at substantial additional computational costs, and using data from more markets does not always lead to better performance - a fact we delve deeper into with interpretability analysis of the forecast models. Overall, these findings provide valuable guidance for market participants and decision-makers aiming to optimize bidding strategies within increasingly interconnected and volatile European energy markets.