爱尔兰电网最大单一馈入/馈出的提前一天预测：一种生成式人工智能方法
Day-Ahead Forecasting of Largest Single Infeed/Outfeed on the Irish Power Grid: A Generative Artificial Intelligence Approach
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中文总结 AI 辅助
研究利用生成式人工智能方法提前一天预测爱尔兰电网最大单一馈入和馈出，通过与EirGrid合作开发，借助有限数据实现高精度预测，有望降低备用采购成本，展现了TSO基于人工智能的资源规划的实用性与可扩展性。
中文摘要 AI 辅助
本文提出一种生成式人工智能（Gen AI）方法，用于提前一天预测爱尔兰电力系统的最大单一馈入（LSI）和最大单一馈出（LSO），以辅助备用容量规划。该系统由爱尔兰输电系统运营商EirGrid与某平台合作开发，利用日前和日内能源市场关闭时间前的有限数据，能提前38小时进行准确预测。初始性能表明，平均绝对百分比误差（MAPE）仅比使用全部市场数据（提前8小时）的结果高1.1%。若该方法集成到运营系统并保持高精度，可显著降低备用采购成本，结果还证明了TSO基于人工智能的资源规划的实用性和可扩展性。
英文摘要
This paper presents a generative artificial intelligence (Gen AI) approach for forecasting, at a day-ahead stage, the largest single infeed (LSI) and largest single outfeed (LSO) on the Irish power system to assist in reserve dimensioning. Developed collaboratively between EirGrid, the electric transmission system operator (TSO) for Ireland, and GridZero.ai using the GridZero.ai platform, the system delivers accurate forecasts up to 38 hours ahead of real-time using limited data available before the day-ahead and intra-day energy market gate closure timings. Initial performance demonstrates an accuracy with a mean absolute percentage error (MAPE) that is only 1.1\% higher than the results possible using full market data (8-hours ahead). Thus, if this approach is integrated into operational systems and such high levels of accuracy are maintained, reserve procurement costs could be significantly reduced. The results also demonstrate the practicality and extensibility of AI-powered resource planning for TSOs.
