保持冷量：面向工业制冷的保留感知库存控制
Holding the Cold: Retention-Aware Inventory Control for Industrial Refrigeration
- University of California, Santa Barbara（加州大学圣塔芭芭拉分校）
- CrossnoKaye®（CrossnoKaye）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对工业制冷压缩机满负荷运行与冷量损耗的权衡，提出保留因子建模的随机库存控制策略，证明考虑损耗的简单策略可接近最优节能效果。
AI中文摘要：
工业制冷消耗大量电力，压缩机是这些系统中的主要能耗设备，因此其运行方式对提高能源效率至关重要。压缩机在满负荷运行时效率最高，但满负荷运行所提供的冷量可能超过设施的即时需求。这促使了预冷却技术的应用，即压缩机满负荷运行，将多余的冷量以热库存的形式储存起来，以应对未来的热负荷。然而，储存的冷量本质上是有损耗的：较冷的空间会从周围环境吸引额外的热量，从而在最大化压缩机效率与避免冷量在使用前消散之间产生权衡。我们通过一个保留因子来研究这一权衡，该因子定义为一分钟后仍存留的热库存比例，目标是理解保留因子如何影响预冷却的价值，并设计能够考虑这种损耗性的有效控制策略。我们将压缩机控制建模为随机库存问题，通过动态规划求解最优策略，并同时提出两种更简单的替代策略，使用从真实工业制冷设施数据拟合的模型来评估这些策略的性能。我们的结果表明：（i）当热库存具有足够的持续性时，预冷却可以带来显著的节能效果，但若不考虑保留因子，随着损耗的增加，激进的预冷却策略会变得越来越昂贵；（ii）考虑损耗性的结构简单策略仍能在有损耗系统中实现接近最优的性能。
英文摘要：
Industrial refrigeration consumes substantial electricity, and compressors are the dominant energy consumers in these systems, making their operation central to improving energy efficiency. Compressors are most efficient when operated at full capacity, but the cooling they provide at full capacity can exceed the facility's immediate needs. This motivates pre-cooling, where compressors operate at full capacity and the excess cooling is stored as thermal inventory for future heat loads. However, stored cooling is inherently lossy: colder spaces attract additional heat from their surroundings, creating a tradeoff between maximizing compressor efficiency and avoiding cooling that dissipates before it can be used. We study this tradeoff through a retention factor, defined as the fraction of thermal inventory that survives after one minute, with the goals of understanding how retention affects the value of pre-cooling and designing effective control policies that account for this lossiness. We formulate compressor control as a stochastic inventory problem, solve for an optimal policy via dynamic programming alongside two simpler alternatives, and evaluate the performance of these policies using models fit from real industrial refrigeration facility data. Our results show that (i) pre-cooling can provide substantial energy savings when thermal inventory is sufficiently persistent, but that failing to account for retention can make aggressive pre-cooling increasingly costly as losses grow, and (ii) structurally simple policies that account for lossiness can still achieve near-optimal performance in lossy systems.
