|Title:||Online supervisory and optimal control of complex building central chilling systems|
|Subject:||Hong Kong Polytechnic University -- Dissertations.|
Air conditioning -- Control.
|Department:||Department of Building Services Engineering|
|Pages:||xxv, 267 leaves : ill. ; 30 cm.|
|Abstract:||Building Heating, Ventilation, and Air-conditioning (HVAC) systems are the major energy consumers in buildings. Operation and control of HVAC systems have significant impacts on energy or cost efficiency of buildings besides proper system designs and selection and maintenance of individual components. Although a great deal of research has been carried out on the proper control of HVAC systems and various cost effective control strategies have been developed for individual components in HVAC systems, not much research has concentrated on the online supervisory and optimal control of the overall building HVAC systems, and the research on developing online supervisory and optimal control strategies for complex building HVAC systems, still seems missing. This thesis presents the online supervisory and optimal control strategies for complex building central chilling systems to enhance their energy efficiency. The software tools and implementation guidelines for applying these strategies for energy efficient control and operation of complex building central chilling systems are provided as well. The online supervisory and optimal control strategies developed in this thesis consist of the strategies for variable speed pumps, an optimal control strategy for complex condenser cooling water systems and an optimal control strategy for complex chilled water systems. The optimal control strategies for condenser cooling water systems and chilled water systems were formulated using a systematic approach by considering the system level and subsystem level characteristics and interactions among all components and their associated variables, as well as the requirements and constraints of practical applications, i.e., control performance, computational cost, memory demand, etc. In order to test and analyze the control performances and economic feasibilities of different control strategies under dynamic working conditions to determine the most promising strategy that can be used in practice, prior to site implementation, a dynamic simulation platform for complex building central chilling systems was developed. Three energy performance tests associated with the optimization of major control variables (i.e., the chilled water supply temperature set-point, the condenser water supply temperature set-point and the number of chillers operating) were conducted based on this simulation platform to evaluate the energy saving potentials in complex central chilling systems. The results obtained from these tests were carefully considered during the development of the online supervisory and optimal control strategies for condenser cooling water systems and chilled water systems. To formulate the online supervisory and optimal control strategies, simplified models of major chilling system components (i.e., chillers, cooling towers, heat exchangers, pumps, etc.) were developed or selected in this thesis. The performances of these models were validated using the field measurement data, and/or the factory performance test data, and/or the catalogue data provided by the manufacturers. To design the optimal control strategy for chilled water systems, the speed and sequence control strategies for variable speed pumps with different configurations in complex central air-conditioning systems were developed and presented. The performances of these strategies were tested and evaluated using a simulation-assisted test method in which the control strategies were tested in a simulated virtual environment similar to the situation when they are actually implemented in practice. Based on the simplified chiller model and cooling tower model developed, an optimal control strategy for complex condenser cooling water systems is developed. This strategy consists of the model-based performance predictor, cost estimator (i.e., cost function), optimization technique and supervisory strategy. The control and computation performances of this strategy were evaluated by comparing with that of a model-based control strategy using the same models but using a GA (genetic algorithm) as the optimization tool, while the energy performance of this strategy was evaluated by comparing with that of the conventional control strategies for condenser cooling water systems. The results show that this optimal control strategy has satisfactory performance and is suitable for online control applications. An optimal control strategy for complex chilled water systems is also developed and presented. This strategy consists of the model-based performance predictor, cost estimator, optimization algorithm, supervisory strategy and a number of local control strategies. The local control strategies were used to ensure the robust operation and keep track of the control settings considering the dynamic characteristics of the local process environment. The performance of this strategy was evaluated using the simulation-assisted test method by comparing it with that of other control strategies. The results show that about 1.28%~2.63% energy in the system under investigation can be saved thanks to the use of this optimal control strategy as compared with that using a conventional control strategy. Lastly, the software tools and implementation guidelines for applying these online supervisory and optimal control strategies in practice are presented.|
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