Simulation Assessment of a Near-Optimal Control Algorithm for Central Cooling Plants with Chilled Water Storage

摘要

This paper presents the development and evaluation of a rule-based control algorithm for minimizing energy costs in cooling plants with chilled water storage subject to dynamic electricity rates combined with demand charges. The control approach requires very little plant information, is relatively simple, and ensures that the storage will not be prematurely depleted. The control algorithm was evaluated using a model of an existing chiller plant with significant complexity built in a simulation testbed for different combinations of storage sizes, load profiles and RTP electricity rates. The performance of the near-optimal algorithm was compared with three different approaches: optimal control (baseline), and two heuristic control strategies commonly used for thermal energy storage: chiller priority and storage-priority load-limiting. The energy costs obtained with the near-optimal control algorithm were within 3.5% of the costs associated with optimal control. Comparison with other common heuristic control strategies shows that significant energy savings can be achieved with the proposed control method.