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：参与多市场电力交易的电池储能系统（BESS）需要价格预测来优化调度决策。一个广泛接受的假设是，由平均绝对误差（MAE）等标准指标衡量的预测精度驱动交易性能。我们使用一个分层三层优化系统挑战这一假设，该系统在2020-2025年期间同时参与德国和瑞士的频率 containment 备用（FCR）、自动频率恢复备用（aFRR）、日前和连续日内（XBID）市场交易，并使用来自Regelleistung.net和Swissgrid的真实市场数据。我们发现秩相关（Kendall tau）而非MAE是日内调度价值的主要预测指标：超过经验阈值tau≈0.85-0.95的预测可捕获完美预见收益的97-100%，而趋于零tau的持久性预测仅捕获33%。该阈值在不同市场机制和波动水平下保持稳定，并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达6.5倍，使得容量分配而非预测精度成为总收益的主要驱动力。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重点的文献中缺失。这些发现重塑了BESS运营商的预测评估框架：相关问题不在于MAE是多少，而在于预测是否达到tau充分性。