本文研究了预测不确定性对储热系统预测最优控制器的成本节约性能的影响。具体而言，本研究分析了四种不确定性模型，以预测冷负荷、天气变量和电价的未来值。考虑的不确定性模型包括无偏高斯噪声、相关高斯噪声、无偏均匀噪声和有偏均匀噪声。本文总结的分析结果表明，预测最优控制器具有鲁棒性，并且在预测冷负荷和实际负荷时不需要高精度- 时间定价（RTP）费率。单位:I-PCITION:研讨会，ASHRAE交易，第105卷，pt。1999年2月2日，西雅图

In this paper an investigation is presented to determine the effect of forecasting uncertainty on the cost savings performance of a predictive optimal controller for thermal energy storage (TES) systems. Specifically, this investigation analyzed four uncertainty models to predict future values for cooling loads, weather variables, and electrical rates. The uncertainty models considered are unbiased Gaussian noise, correlated Gaussian noise, unbiased uniform noise, and biased uniform noise. The results of the analysis summarized in this paper show that the predictive optimal controller is robust and does not require high levels of accuracy in predicting the cooling loads and the real-time pricing (RTP) rates.Units: I-P