A near-optimal control algorithm for central cooling plants with electric and/or gas-driven chillers

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.