| Energy saving is imperative because serious energy problems are associated with central air-conditioning while it supplies man comfort environment. Among so many factors that influence the energy exhaust, the control issue is an important aspect. Modern Building Automation System (BAS) has made it possible to integrate the central air conditioning into the whole building system and implement optimal control. While the system works under part load condition, for an online optimal supervisory controller, how to specify the reliable set points for each local loop controller? How to give the reasonable operation modes for each component? Such problems can affect greatly the total energy requirement. Especially in a central chilled water system with complicated pipeline and many control variables, even a small improvement can cause significant reductions in energy use. Now the key issue to improve the level of HVAC systems is to improve its controls, i.e., to develop the optimal strategies for its controls.The aim of the paper is to study the optimal control based on system simulation of typical VWV chilled water system. The content of the paper is to develop and analyze the effect of the sets of local controls and some optimal control strategies in system performance and control performance.For VWV system, due to its characteristics of more control variables and more complicated system structure, conventional strategy of system control and management which the sets are reset by skillful operators becomes unsuitable and will lose the energy-saving potential of VWV system.The simulation of typical VWV system is set up first in the paper, which is based on TRNSYS platform. In order to speed the calculation, an un-physical model is set up and incorporated in to simulation which separating pressure and flow from all the physical models. The tests of simulation show that the simulation can well simulate the overall performance of system and its controls. And it can be used to develop, test and validate the optimal control strategies.Based on analyzing simulation tests, five online control strategies are developed: the optimal control of supply head of chilled water, the optimal control of supply temperature of chilled water, the optimal control of supply head and temperature of chilled water in series, COP based optimal operation for multi-chillers system, and online predictiveoptimal control strategy for system.The supply head and temperature of chilled water are two key control variables for the performance of system. Improper sets will result in insufficient cooling supply or energy waste. Due to interrelated relationship between these two variables, the optimal strategy of supply head and temperature of chilled water in series is developed to extend the range of control. It is validated by simulation tests and results also show that the strategy can save energy.Chillers'energy consumption is a very large portion of total energy consumption in HVAC water system. It is closely related with PLR (Part Load Ratio) of chillers. For the system using several chillers in parallel, esp. for system using different rated-capacity chillers, they usually operating in part load in most of time. An effective of energy-saving is to optimize on/off of chillers and optimal load supplies among operating chillers, which will increase the PLR of chillers and therefore improve the overall COP of chillers. The paper adopts offline and online methods to get chillers'COP vs. PLR relationships respectively. Total energy consumption of chillers is selected as the objective function and SWIFT (Sequential Unconstrained Minimization Technique) method is used to get the optimal solution: optimal load supplies among operating chillers. The optimal control is implemented through resetting the supply temperatures of chilled water for every operating chiller. Simulation results show that the optimal load supplies control strategy can well meet consumers'load and save energy.Finally, online predictive optimal control strategy for system is developed. The strategy based on mathematic models with simple physical properties and online parameters identification with adaptive control technique takes the total system energy as the objective function. Within the coming period of time, it can real time forecast the operating and control characteristics of the overall system with a self-tuning method and can quickly solve the optimal set points of different control variables with a genetic algorithm. The strategy is tested and evaluated on the simulator. The results show that it can minimize the system total energy while still keep the control stability with optimizing the sets of supply head and supply temperature of chilled water simultaneously. |
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