Optimization of energy efficiency of air-cooled chillers using water mist pre-cooling

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Optimization of energy efficiency of air-cooled chillers using water mist pre-cooling

 

Author: Yang, Jia
Title: Optimization of energy efficiency of air-cooled chillers using water mist pre-cooling
Degree: Ph.D.
Year: 2013
Subject: Air conditioning -- Equipment and supplies -- Energy consumption.
Hong Kong Polytechnic University -- Dissertations
Department: Dept. of Building Services Engineering
Pages: xxi, 285 p. : ill. (some col.) ; 30 cm.
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b2616028
URI: http://theses.lib.polyu.edu.hk/handle/200/6999
Abstract: Air-cooled chillers are widely used to provide space cooling in air-conditioned buildings due to their flexibility. The operation of chillers usually takes up the highest proportion of the total electricity consumption of buildings. Low operational efficiency and undesirable control are part of the reasons for such high energy consumption. The deficient performance of air-cooled chillers is mainly due to the traditional head pressure control (HPC) under which the condensing temperature is kept high. To improve energy efficiency, chiller systems should be properly operated to meet the cooling load under external and internal conditions with the least energy consumption. This research focuses on the optimal operation of water mist assisted air-cooled chillers under variable condensing temperature control (CTC), using numerical simulation, artificial neural network (ANN) and genetic algorithm (GA). The optimization problem is formulated and solved to find the optimal set point of condensing temperature and optimal water mist generation rate under various conditions with least chiller energy consumption. To achieve this objective, a combination of field investigation, experimentation and system simulation was conducted. Field investigation was conducted to identify the operating characteristics and energy performance of two existing chiller plants with and without water mist pre-cooling. With the operating characteristics of the studied chillers, the thermodynamic models for the air-cooled chillers with twin refrigeration circuits with and without water mist system were developed using TRNSYS and validated using a wide range of operating data. With the validated model, simulation analyses were carried out to determine viable energy saving measures for the chiller plant, including optimal circuit loading sequence (CLS), CTC, variable speed condenser fans (VSF) and water mist pre-cooling of the entering condenser air stream. In order to study the year-round energy consumption, representative office and hotel buildings and their air-conditioning systems were modeled using EnergyPlus. With the chiller models and the building models, the load-frequency and weather-load profiles of the buildings were established, and the energy savings potentials of individual and mixed uses of the measures were assessed.
Due to the complex nonlinear characteristics of chiller systems, this research presents an intelligent control technique, including neural networks and genetic algorithms, for the optimal control of the air-cooled chillers under various operating conditions. This control involves identifying the optimal set points of condensing temperature, condenser fans operation and the optimal water mist generation rate, which results in the least electricity consumption by the compressors and condenser fans. ANN is used to model the operation of air-cooled chillers, and GA is adopted in searching optimal set points of condensing temperature and optimal water mist generation rate based on the predicted fitness values. The results show that this control technique enabled optimal condensing temperature control successfully, and the chiller performance could be improved considerably, and its control performance is superior to the conventional control. The main contribution to knowledge of this research is the development of an optimal operation method for water mist assisted air-cooled chillers under variable condensing temperature control, which is applicable to improve the energy efficiency of air-cooled chillers. This research also develops an artificial intelligent system based on the ANN and GA to simulate the chiller operation and find the optimal solution for the optimal control of air-cooled chillers, aiming to provide a practical control technique for the chiller operation. Building services engineers will benefit from the results of this research on how to design and efficiently operate multiple air-cooled chillers with water mist system to cut down electricity bills. The results of this study will also be helpful for chiller manufacturers to apply variable condensing temperature control and artificial intelligent control in their development of more efficient chiller products.

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