Battery energy storage systems (BESS) participating in multi-market electricity trading require price forecasts to optimize dispatch decisions. A widely held assumption is that forecast accuracy, measured by standard metrics such as mean absolute error (MAE), drives trading performance. We challenge this assumption using a hierarchical three-layer optimization system trading simultaneously on frequency containment reserve (FCR), automatic frequency restoration reserve (aFRR), day-ahead, and continuous intraday (XBID) markets in Germany and Switzerland over 2020-2025, with real market data from Regelleistung.net and Swissgrid. We find that rank correlation (Kendall tau), rather than MAE, is the primary predictor of intraday dispatch value: forecasts above an empirical threshold of tau approximately 0.85-0.95 capture up to 97-100% of perfect-foresight revenue, while persistence forecasts with near-zero tau capture only 33%. This threshold is stable across market regimes and volatility levels, and reflects the ordinal structure of the dispatch problem. Furthermore, under reserve market constraints, FCR capacity revenue exceeds XBID by 6.5x per MW, making capacity allocation -- not forecast accuracy -- the primary driver of total revenue. In the Swiss market, hydrological surplus anomalies are significantly associated with balancing market revenue (p = 0.0005), a mechanism absent from existing German-focused literature. These findings reframe forecast evaluation for BESS operators: the relevant question is not what the MAE is, but whether the forecast achieves tau-sufficiency.

翻译：电池储能系统（BESS）参与多市场电力交易时，需要价格预测来优化调度决策。一个普遍假设是，以平均绝对误差（MAE）等标准指标衡量的预测准确性驱动交易绩效。我们利用2020-2025年间德国和瑞士市场上同时参与频率 containment 备用（FCR）、自动频率恢复备用（aFRR）、日前交易及连续日内交易（XBID）的三层分级优化系统，基于来自Regelleistung.net和Swissgrid的真实市场数据对这一假设提出挑战。研究发现，预测日内调度价值的主要指标是秩相关（Kendall tau）而非MAE：当预测的tau值超过约0.85-0.95的经验阈值时，可实现完美预见收益的97-100%；而tau值趋近于零的持续性预测仅能捕获33%的收益。该阈值在不同市场机制和波动水平下保持稳定，反映了调度问题的序数结构。此外，在备用市场约束下，FCR容量收益每兆瓦超过XBID收益6.5倍，使得容量分配——而非预测准确性——成为总收益的主要驱动因素。在瑞士市场，水文盈余异常与平衡市场收益显著相关（p = 0.0005），这一机制在现有以德国为中心的研究文献中尚未涉及。这些发现重新定义了BESS运营商的预测评估框架：关键问题不在于MAE值的高低，而在于预测是否达到tau充分性。