研究人员开发并评估了八种不同的预测模型，包括LightGBM和深度学习架构，以预测挪威五个出价区域的电价。该研究使用了2019年至2025年的多模态小时数据集，并采用了严格的回测和特征消融技术。LightGBM在所有区域中表现最佳，而依赖滞后价格和日历变量的简单模型也显示出较高的准确性。然而，研究发现，诸如水库水位和天然气价格等外部因素对于提高预测准确性至关重要，尤其是在市场压力期间。 AI
影响 为能源市场提供了基准预测模型，强调了在市场压力期间外部因素的重要性。
排序理由 关于具有基准结果的预测模型的学术论文。
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arXiv:2604.26634v1 Announce Type: new Abstract: Norway's electricity market is heavily dominated by hydropower, but the 2021--2022 energy crisis and stronger integration with Continental Europe have fundamentally altered price formation, reducing the reliability of forecasting mo…
Norway's electricity market is heavily dominated by hydropower, but the 2021--2022 energy crisis and stronger integration with Continental Europe have fundamentally altered price formation, reducing the reliability of forecasting models calibrated on historical data. Despite the …
Norway's electricity market is heavily dominated by hydropower, but the 2021--2022 energy crisis and stronger integration with Continental Europe have fundamentally altered price formation, reducing the reliability of forecasting models calibrated on historical data. Despite the …