# A Decentralized, Flat-Structured Control System for Chiller Plants +
## 1 Introduction  
Heating, ventilation, and air conditioning (HVAC) systems usually are the largest energy use systems in commercial buildings. For a generic office building, more than 60% of total energy use can be generated by HVAC system [1]. Within the HVAC system itself, the most energy-consuming part is the chiller plant system, which consists of chillers, pumps, cooling towers and some other electromechanical equipment. In most practical applications, considering standby capacity, operational flexibility and, most importantly, high energy efficiency under partial load, multiple devices of the same type are usually connected in parallel to a group or station. Therefore, the group operation of the pump, chiller and cooling tower systems come to be a significant topic in the optimal control of a chiller plant system, where the key points and difficulties are how to determine loading/unloading and matching speed or part load ratio (PLR) of all running equipment. Considerable studies have been undertaken to regulate the optimal group operation of the pump, cooling tower and chiller systems, to mainly realize the energy conservation [2] and thermal comfort goal [3]. Most researchers have focused on employing various numerical algorithms to resolve such an optimization problem. Some researchers have adopted genetic algorithm [4], dynamic programming algorithm [5], evolutionary algorithm [6], extreme value analysis algorithm [7], and mixer integer nonlinear programming (MINLP) algorithm [8] to optimize the group operation of variable speed pumps (VSPs). For the chillers' optimal group operation, evolutionary algorithm [9], generalized reduced gradient algorithm [10], branch and bound algorithm [11], particle swarm algorithm [12], and simulated annealing algorithm [13] has been adopted for the optimal chiller load (OCL). The optimization algorithms for the group operation of cooling tower include constrained inverse optimization [14], mixed-integer nonlinear programming (MINLP) algorithm [15], artificial bee colony algorithm [16], particle swarm algorithm [17]. However, these algorithms are not straightforward and usually need either the input of abundant data for the algorithm training or case-by-case development for unequal systems. Unfortunately, high computation and implementation cost make it difficult for these algorithms to be widely adopted in real applications [18]. Some researchers have tried to find analytical solutions to solve this optimization problem for assisting with the straightforward control algorithm design. An analytical solution for speed optimization has been derived [18; 19; 20]. One basic rule is to maintain the same speed ratio for identical parallel connected pumps, which has been verified by experimental studies [21; 22]. Typical principles of chiller sequencing control, commonly used in practical applications, include direct power-based control, bypass flow-based control, return chilled-water temperature-based control, and total cooling load-based control [23]. In the current practical applications, whatever optimal group operation is used, the system structure has remained unchanged for almost 30 years [24]. It uses a hierarchical tree topology, as shown in Figure 1, with a centralized controller (PLC or DDC) to complete control tasks. The centralized controller firstly collect data from each unit of equipment and then perform calculations. After that, it make decisions based on a centralized control algorithm and send out control instructions to each unit of equipment. With this centralized control structure, when the system configuration changes, the control algorithm or strategy needs to be adjusted or reprogrammed accordingly. These works which include onsite measuring, wiring, configuring, commissioning, and secondary development mean that each control system is unique and case-by-case developing. Therefore, the development of a centralized chiller plant control system leads to a high labor cost. Figure 1: Typical control system structure for chiller plant system.