This paper presents a near-optimal control algorithm for minimizing energy costs in hybrid cooling plants in response to cooling loads. The approach is based upon an approximate solution to the partial differential equations involved in minimizing the cost of energy consumed by the plant with respect to two control variables: cooling tower airflow and condenser water flow. The parameters of the algorithm can be determined with design information of the chillers and cooling towers, along with some measurements of total condenser water flow and pump power consumption. In addition to reducing plant operating costs, the algorithm simplifies tower control and is more stable compared with conventional tower control strategies such as constant condenser water supply temperature or constant approach to wet-bulb. A large-scale cooling plant model was utilized to evaluate the performance of the approach compared with optimal control and two heuristic control strategies over six months. The difference between the energy costs associated with the near-optimal control approach and optimal control was 1.7%. Comparison with the heuristic control strategies shows that significant energy savings can be achieved with the proposed algorithm.

本文提出了一种接近最优的控制算法，可将混合制冷设备中的能源成本降至最低，以响应制冷负荷。该方法基于偏微分方程的近似解，该偏微分方程涉及在两个控制变量（冷却塔气流和冷凝器水流）方面将工厂消耗的能源成本降至最低。该算法的参数可以通过冷却器和冷却塔的设计信息以及总冷凝器水流量和泵功率消耗的一些测量值来确定。除了降低工厂的运营成本外，该算法还简化了塔的控制，并且与常规塔控制策略（例如恒定的冷凝器供水温度或恒定的湿球方法）相比更加稳定。在六个月内，与最佳控制和两种启发式控制策略相比，利用大型冷却设备模型来评估该方法的性能。与最佳控制方法和最佳控制方法相关的能源成本之差为1.7％。与启发式控制策略的比较表明，使用所提出的算法可以节省大量能源。