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This paper presents the online optimal control strategies for multiple-chiller plants in large buildings with enhanced robustness and cost efficiency, including optimization of chilled water supply temperature set-point, chiller sequencing control, optimal start control and electrical demand limiting control. The chilled water supply temperature set-point optimization aims to minimize the total energy consumption of chillers and chilled water distribution pumps. In the chiller sequencing control, three schemes are used to enhance its control robustness, including a data fusion scheme for improved reliability of building cooling load measurement, a simplified adaptive model of maximum chiller cooling capacity, and an online sensor fault detection and diagnosis(FDD). In the chiller optimal start control, a model-based strategy is proposed for minimizing the energy consumption in the morning start period. The model-based optimal start control strategy considers both the recovery ability and the pre-cooling lead time as its optimizing variables. The peak demand limiting control strategy minimizes the monthly electricity bill by predicting a suitable monthly peak demand threshold and restraining the daily peak demand to the threshold. These control strategies are validated using the dynamic simulation of the central chiller plant in a high-rising building in Hong Kong. © All Rights Reserved.

The article discusses the proposed alternative control strategy to test and simulate chilled water pumps energy in the building. The chilled water pipelines and terminal units are associated with condenser water pump and primary chilled water pump to transfer the cooling energy from low zones to high zones to avoid high water static pressure. Moreover, the original control strategy generates 12.02% to 16.01% of energy to heat exchangers and improve control strategy in practical applications. "Two control strategies for variable speed pumps were tested in a super high-rise building in Hong Kong. (1) The 1,608 ft (490 m) high building has a floor area of 3.4 million [ft.sup.2] (321 000 [m.sup.2]). The basement is four floors, a block building is six floors and a tower building is 98 floors."

The use of phase change materials (PCM) to enhance the building energy performance has attracted increasing attention of researchers and practitioners over the last few years. Thermodynamic models of building structures using PCMs are essential for analyzing their impacts on building energy performance at different conditions and using different control strategies. There are few PCM models of detailed physics providing good accuracy in simulating thermodynamic behavior of building structures integrated with PCM layers. However, simplified models with acceptable accuracy and good reliability are preferable in many practical applications concerning computation speed and program size particularly when involving large buildings or models are used for online applications. A simplified physical dynamic model of building structures integrated with SSPCM (shaped-stabilized phase change material) is developed and validated in this study. The simplified physical model represents the wall by 3 resistances and 2 capacitances and the PCM layer by 4 resistances and 2 capacitances respectively while the key issue is the parameter identification of the model. The parameters of the simplified model are identified using genetic algorithm (GA) on the basis of the basic physical properties of the wall and PCM layer. Two GA-based preprocessors are developed to identify the optimal parameters (resistances and capacitances) of the model by frequency-domain regression and time-domain regression respectively. Validation results show that the simplified model can represent light walls and median walls integrated with SSPCM with good accuracy.

This paper presents an optimization strategy for optimal control and operation of building central chilling systems in order to minimize their energy consumption and provide improved control performance. The strategy is formulated using a systematic approach, in which the characteristics and interactions among the components and subsystems in the central chilling system are considered. The simplified models of major components are used in the strategy as the performance predictors to estimate the system energy performance and responses to the changes of control settings and working conditions. To ensure the models to provide reliable estimates when the working condition changes, the model parameters are updated online using the recursive least squares (RLS) estimation technique. A genetic algorithm (GA) is used to solve the optimization problem and search for globally optimal control settings on the basis of a cost function estimator defined. The performance of this strategy was tested and evaluated in a simulated virtual system representing the complex central chilling system in a super high-rise building under various working conditions. The model parameter identification and performance validation as well as the performance evaluation of the optimization strategy are presented.

This paper presents the optimal control strategies for variable speed pumps with different configurations in complex building air-conditioning systems to enhance their energy efficiencies. Through a detailed analysis of the system characteristics, the pressure drop models for different water networks in complex air-conditioning systems are developed and then used to formulate an optimal pump sequence control strategy. This sequence control strategy determines the optimal number of pumps in operation taking into account their power consumptions and maintenance costs. The variable speed pumps in complex air-conditioning systems can be classified into two groups: the pumps distributing water to terminal units and pumps distributing water to heat exchanges. The speeds of pumps distributing water to terminal units are controlled by resetting the pressure differential set-point using the online opening signals of water control valves. The speeds of pumps distributing water to heat exchanges are controlled using a water flow controller. The performances of these strategies are tested and evaluated in a simulated virtual environment representing the complex air-conditioning system in a super high-rise building by comparing with that of other reference strategies. The results showed that about 12–32% of pump energy could be saved by using these optimal control strategies.

This paper presents the optimal control strategies for variable speed pumps with different configurations in complex building air-conditioning systems to enhance their energy efficiencies. Through a detailed analysis of the system characteristics, the pressure drop models for different water networks in complex air-conditioning systems are developed and then used to formulate an optimal pump sequence control strategy. This sequence control strategy determines the optimal number of pumps in operation taking into account their power consumptions and maintenance costs. The variable speed pumps in complex air-conditioning systems can be classified into two groups: the pumps distributing water to terminal units and pumps distributing water to heat exchanges. The speeds of pumps distributing water to terminal units are controlled by resetting the pressure differential set-point using the online opening signals of water control valves. The speeds of pumps distributing water to heat exchanges are controlled using a water flow controller. The performances of these strategies are tested and evaluated in a simulated virtual environment representing the complex air-conditioning system in a super high-rise building by comparing with that of other reference strategies. The results showed that about 12–32% of pump energy could be saved by using these optimal control strategies.

This paper presents the online test and evaluation of the performance of five practical control strategies (fixed set-point control method, fixed approach control method, two near optimal strategies and one optimal strategy) for building cooling water systems to identify the best strategy for future field validation. All of these strategies were tested and evaluated in a simulated virtual environment similar to the situation when they are actually implemented in practice. A virtual building system representing the real building and its central chilling system was developed and used to test the operational performance of the system controlled by different strategies. The packages of each control strategy are separately computed by the application program of Matlab, as the control optimizers to identify the necessary control settings for the given condition based on the collected operation data. The data exchanger between the virtual building system and the control optimizer was managed by a software platform through a communication interface. The results showed that the optimal control strategy is more energy efficient and cost effective than the other strategies, and its computational cost is manageable and can satisfy the requirements of practical applications. This strategy is being implemented in a super high-rise building for field validation.

This paper presents the online test and evaluation of the performance of five practical control strategies (fixed set-point control method, fixed approach control method, two near optimal strategies and one optimal strategy) for building cooling water systems to identify the best strategy for future field validation. All of these strategies were tested and evaluated in a simulated virtual environment similar to the situation when they are actually implemented in practice. A virtual building system representing the real building and its central chilling system was developed and used to test the operational performance of the system controlled by different strategies. The packages of each control strategy are separately computed by the application program of Matlab, as the control optimizers to identify the necessary control settings for the given condition based on the collected operation data. The data exchanger between the virtual building system and the control optimizer was managed by a software platform through a communication interface. The results showed that the optimal control strategy is more energy efficient and cost effective than the other strategies, and its computational cost is manageable and can satisfy the requirements of practical applications. This strategy is being implemented in a super high-rise building for field validation.

This paper presents the optimal control strategies for variable speed pumps with different configurations in complex building air-conditioning systems to enhance their energy efficiencies. Through a detailed analysis of the system characteristics, the pressure drop models for different water networks in complex air-conditioning systems are developed and then used to formulate an optimal pump sequence control strategy. This sequence control strategy determines the optimal number of pumps in operation taking into account their power consumptions and maintenance costs. The variable speed pumps in complex air-conditioning systems can be classified into two groups: the pumps distributing water to terminal units and pumps distributing water to heat exchanges. The speeds of pumps distributing water to terminal units are controlled by resetting the pressure differential set-point using the online opening signals of water control valves. The speeds of pumps distributing water to heat exchanges are controlled using a water flow controller. The performances of these strategies are tested and evaluated in a simulated virtual environment representing the complex air-conditioning system in a super high-rise building by comparing with that of other reference strategies. The results showed that about 12–32% of pump energy could be saved by using these optimal control strategies.

This paper presents the online test and evaluation of the performance of five practical control strategies (fixed set-point control method, fixed approach control method, two near optimal strategies and one optimal strategy) for building cooling water systems to identify the best strategy for future field validation. All of these strategies were tested and evaluated in a simulated virtual environment similar to the situation when they are actually implemented in practice. A virtual building system representing the real building and its central chilling system was developed and used to test the operational performance of the system controlled by different strategies. The packages of each control strategy are separately computed by the application program of Matlab, as the control optimizers to identify the necessary control settings for the given condition based on the collected operation data. The data exchanger between the virtual building system and the control optimizer was managed by a software platform through a communication interface. The results showed that the optimal control strategy is more energy efficient and cost effective than the other strategies, and its computational cost is manageable and can satisfy the requirements of practical applications. This strategy is being implemented in a super high-rise building for field validation.

A strategy of fault detection and diagnosis (FDD) for HVAC sub-systems at the system level is presented in this paper. In the strategy, performance indices (PIs) are proposed to indicate the health condition of different sub-systems including cooling tower system, chiller system, secondary pump systems before heat exchangers, heat exchanger system and secondary pump system after heat exchangers. The regression models are used to estimate the PIs as benchmarks for comparison with monitored PIs. The online adaptive threshold determined by training data and monitored data is used to determine whether the PI residuals between the estimation and calculation or monitoring are in the normal working range. A dynamic simulation platform is used to simulate the faults of different sub-systems and generate data for training and validation. The proposed FDD strategy is validated using the simulation data and proven to be effective in the FDD of heating, ventilating and air-conditioning (HVAC) sub-systems.

Thermal energy storage (TES) systems using phase change material (PCM) have been recognized as one of advanced energy technologies in enhancing energy efficiency and sustainability of buildings. The use of PCMs in buildings provides the potential for a better indoor thermal comfort for occupants due to the reduced indoor temperature fluctuations, and lower global energy consumption due to the load reduction/shifting. A good knowledge on dynamic characteristics and energy performance of buildings using PCMs is essential for building researchers and practitioners to better understand building temperature response characteristics and economic feasibility of using PCMs and take further proper actions to fully utilize PCMs to enhance indoor environmental quality and overall energy efficiency of buildings. This paper presents an overview of the previous research work on dynamic characteristics and energy performance of buildings due to the integration of PCMs. The research work on dynamic characteristics and energy performance of active and passive building applications is reviewed, respectively. Since the particular interest in using PCMs for free cooling and peak load shifting, the specific research efforts on both subjects are reviewed separately. A few useful conclusive remarks and recommendations for future work are presented.

This paper presents an optimal control strategy for online control of central chilled water systems in complex building air-conditioning systems to enhance their energy efficiency. The optimal control strategy is formulated using a systematic approach by considering the system level and subsystem level characteristics and interactions among the overall system. The requirements and constraints of practical applications are also carefully considered during the development of this strategy. This optimal control strategy consists of the model-based performance predictor (i.e., simplified models), cost estimator (i.e., cost function), optimization technique, supervisory strategy and a number of local control strategies. The local control strategies are used to ensure the robust operation and keep track of control settings considering the dynamic characteristics of the local process environment. The performance of this strategy is tested and evaluated in a simulated virtual environment representing the complex central chilling system in a super high-rise building by comparing it with that of other control strategies. The results showed that this strategy is more energy efficient and cost effective than the other strategies for online applications. This strategy is being implemented in the super high-rise building under study for field application and validation.

Thermal energy storage (TES) systems using phase change material (PCM) have been recognized as one of advanced energy technologies in enhancing energy efficiency and sustainability of buildings. The use of PCMs in buildings provides the potential for a better indoor thermal comfort for occupants due to the reduced indoor temperature fluctuations, and lower global energy consumption due to the load reduction/shifting. A good knowledge on dynamic characteristics and energy performance of buildings using PCMs is essential for building researchers and practitioners to better understand building temperature response characteristics and economic feasibility of using PCMs and take further proper actions to fully utilize PCMs to enhance indoor environmental quality and overall energy efficiency of buildings. This paper presents an overview of the previous research work on dynamic characteristics and energy performance of buildings due to the integration of PCMs. The research work on dynamic characteristics and energy performance of active and passive building applications is reviewed, respectively. Since the particular interest in using PCMs for free cooling and peak load shifting, the specific research efforts on both subjects are reviewed separately. A few useful conclusive remarks and recommendations for future work are presented.

This paper presents an optimal control strategy for online control of central chilled water systems in complex building air-conditioning systems to enhance their energy efficiency. The optimal control strategy is formulated using a systematic approach by considering the system level and subsystem level characteristics and interactions among the overall system. The requirements and constraints of practical applications are also carefully considered during the development of this strategy. This optimal control strategy consists of the model-based performance predictor (i.e., simplified models), cost estimator (i.e., cost function), optimization technique, supervisory strategy and a number of local control strategies. The local control strategies are used to ensure the robust operation and keep track of control settings considering the dynamic characteristics of the local process environment. The performance of this strategy is tested and evaluated in a simulated virtual environment representing the complex central chilling system in a super high-rise building by comparing it with that of other control strategies. The results showed that this strategy is more energy efficient and cost effective than the other strategies for online applications. This strategy is being implemented in the super high-rise building under study for field application and validation.

A strategy of fault detection and diagnosis (FDD) for HVAC sub-systems at the system level is presented in this paper. In the strategy, performance indices (PIs) are proposed to indicate the health condition of different sub-systems including cooling tower system, chiller system, secondary pump systems before heat exchangers, heat exchanger system and secondary pump system after heat exchangers. The regression models are used to estimate the PIs as benchmarks for comparison with monitored PIs. The online adaptive threshold determined by training data and monitored data is used to determine whether the PI residuals between the estimation and calculation or monitoring are in the normal working range. A dynamic simulation platform is used to simulate the faults of different sub-systems and generate data for training and validation. The proposed FDD strategy is validated using the simulation data and proven to be effective in the FDD of heating, ventilating and air-conditioning (HVAC) sub-systems.

This paper presents an optimal control strategy for online control of central chilled water systems in complex building air-conditioning systems to enhance their energy efficiency. The optimal control strategy is formulated using a systematic approach by considering the system level and subsystem level characteristics and interactions among the overall system. The requirements and constraints of practical applications are also carefully considered during the development of this strategy. This optimal control strategy consists of the model-based performance predictor (i.e., simplified models), cost estimator (i.e., cost function), optimization technique, supervisory strategy and a number of local control strategies. The local control strategies are used to ensure the robust operation and keep track of control settings considering the dynamic characteristics of the local process environment. The performance of this strategy is tested and evaluated in a simulated virtual environment representing the complex central chilling system in a super high-rise building by comparing it with that of other control strategies. The results showed that this strategy is more energy efficient and cost effective than the other strategies for online applications. This strategy is being implemented in the super high-rise building under study for field application and validation.

Thermal energy storage (TES) systems using phase change material (PCM) have been recognized as one of advanced energy technologies in enhancing energy efficiency and sustainability of buildings. The use of PCMs in buildings provides the potential for a better indoor thermal comfort for occupants due to the reduced indoor temperature fluctuations, and lower global energy consumption due to the load reduction/shifting. A good knowledge on dynamic characteristics and energy performance of buildings using PCMs is essential for building researchers and practitioners to better understand building temperature response characteristics and economic feasibility of using PCMs and take further proper actions to fully utilize PCMs to enhance indoor environmental quality and overall energy efficiency of buildings. This paper presents an overview of the previous research work on dynamic characteristics and energy performance of buildings due to the integration of PCMs. The research work on dynamic characteristics and energy performance of active and passive building applications is reviewed, respectively. Since the particular interest in using PCMs for free cooling and peak load shifting, the specific research efforts on both subjects are reviewed separately. A few useful conclusive remarks and recommendations for future work are presented.

A strategy of fault detection and diagnosis (FDD) for HVAC sub-systems at the system level is presented in this paper. In the strategy, performance indices (PIs) are proposed to indicate the health condition of different sub-systems including cooling tower system, chiller system, secondary pump systems before heat exchangers, heat exchanger system and secondary pump system after heat exchangers. The regression models are used to estimate the PIs as benchmarks for comparison with monitored PIs. The online adaptive threshold determined by training data and monitored data is used to determine whether the PI residuals between the estimation and calculation or monitoring are in the normal working range. A dynamic simulation platform is used to simulate the faults of different sub-systems and generate data for training and validation. The proposed FDD strategy is validated using the simulation data and proven to be effective in the FDD of heating, ventilating and air-conditioning (HVAC) sub-systems.

A strategy of fault detection and diagnosis (FDD) for HVAC sub-systems at the system level is presented in this paper. In the strategy, performance indices (PIs) are proposed to indicate the health condition of different sub-systems including cooling tower system, chiller system, secondary pump systems before heat exchangers, heat exchanger system and secondary pump system after heat exchangers. The regression models are used to estimate the PIs as benchmarks for comparison with monitored PIs. The online adaptive threshold determined by training data and monitored data is used to determine whether the PI residuals between the estimation and calculation or monitoring are in the normal working range. A dynamic simulation platform is used to simulate the faults of different sub-systems and generate data for training and validation. The proposed FDD strategy is validated using the simulation data and proven to be effective in the FDD of heating, ventilating and air-conditioning (HVAC) sub-systems.

This paper presents an optimal control strategy for online control of central chilled water systems in complex building air-conditioning systems to enhance their energy efficiency. The optimal control strategy is formulated using a systematic approach by considering the system level and subsystem level characteristics and interactions among the overall system. The requirements and constraints of practical applications are also carefully considered during the development of this strategy. This optimal control strategy consists of the model-based performance predictor (i.e., simplified models), cost estimator (i.e., cost function), optimization technique, supervisory strategy and a number of local control strategies. The local control strategies are used to ensure the robust operation and keep track of control settings considering the dynamic characteristics of the local process environment. The performance of this strategy is tested and evaluated in a simulated virtual environment representing the complex central chilling system in a super high-rise building by comparing it with that of other control strategies. The results showed that this strategy is more energy efficient and cost effective than the other strategies for online applications. This strategy is being implemented in the super high-rise building under study for field application and validation.

Thermal energy storage (TES) systems using phase change material (PCM) have been recognized as one of advanced energy technologies in enhancing energy efficiency and sustainability of buildings. The use of PCMs in buildings provides the potential for a better indoor thermal comfort for occupants due to the reduced indoor temperature fluctuations, and lower global energy consumption due to the load reduction/shifting. A good knowledge on dynamic characteristics and energy performance of buildings using PCMs is essential for building researchers and practitioners to better understand building temperature response characteristics and economic feasibility of using PCMs and take further proper actions to fully utilize PCMs to enhance indoor environmental quality and overall energy efficiency of buildings. This paper presents an overview of the previous research work on dynamic characteristics and energy performance of buildings due to the integration of PCMs. The research work on dynamic characteristics and energy performance of active and passive building applications is reviewed, respectively. Since the particular interest in using PCMs for free cooling and peak load shifting, the specific research efforts on both subjects are reviewed separately. A few useful conclusive remarks and recommendations for future work are presented.

This paper presents the optimal control strategies for variable speed pumps with different configurations in complex building air-conditioning systems to enhance their energy efficiencies. Through a detailed analysis of the system characteristics, the pressure drop models for different water networks in complex air-conditioning systems are developed and then used to formulate an optimal pump sequence control strategy. This sequence control strategy determines the optimal number of pumps in operation taking into account their power consumptions and maintenance costs. The variable speed pumps in complex air-conditioning systems can be classified into two groups: the pumps distributing water to terminal units and pumps distributing water to heat exchanges. The speeds of pumps distributing water to terminal units are controlled by resetting the pressure differential set-point using the online opening signals of water control valves. The speeds of pumps distributing water to heat exchanges are controlled using a water flow controller. The performances of these strategies are tested and evaluated in a simulated virtual environment representing the complex air-conditioning system in a super high-rise building by comparing with that of other reference strategies. The results showed that about 12–32% of pump energy could be saved by using these optimal control strategies.

This paper presents the online test and evaluation of the performance of five practical control strategies (fixed set-point control method, fixed approach control method, two near optimal strategies and one optimal strategy) for building cooling water systems to identify the best strategy for future field validation. All of these strategies were tested and evaluated in a simulated virtual environment similar to the situation when they are actually implemented in practice. A virtual building system representing the real building and its central chilling system was developed and used to test the operational performance of the system controlled by different strategies. The packages of each control strategy are separately computed by the application program of Matlab, as the control optimizers to identify the necessary control settings for the given condition based on the collected operation data. The data exchanger between the virtual building system and the control optimizer was managed by a software platform through a communication interface. The results showed that the optimal control strategy is more energy efficient and cost effective than the other strategies, and its computational cost is manageable and can satisfy the requirements of practical applications. This strategy is being implemented in a super high-rise building for field validation.

HVAC systems are the major energy consumers in buildings. Operation and control of HVAC systems have significant impacts on the energy or cost efficiency of buildings besides their designs. Buildings nowadays are mostly equipped with comprehensive building automation systems (BASs) and building energy management control systems (EMCSs) that allow the possibility of enhancing and optimizing the operation and control of HVAC systems. Supervisory and optimal control, which addresses the energy or cost-efficient control of HVAC systems while providing the desired indoor comfort and healthy environment under the dynamic working conditions, is attracting more attention of the building professionals and the society and provides incentives to make more efforts in developing more extensive and robust control methods for HVAC systems. This paper provides a framework for categorizing the main supervisory and optimal control methods and optimization techniques developed and/or utilized in the HVAC field. The application characteristics of each control method and optimization technique are also identified and compared. A comprehensive overall review of the state of the art of the research and development, as well as application of supervisory and optimal control, in HVAC systems is also presented.

This paper presents a model based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. The supervisory control strategy seeks the minimum energy input to provide adequate cooling energy for buildings, taking into account the characteristics and interactions of central cooling water systems as well as the requirements and constraints of practical application. Simplified semi-physical chiller and cooling tower models are used to predict the system energy performance and environment quality as well as the system response to changes of control settings. A hybrid optimization technique, namely the PMES (performance map and exhaustive search) based method, is developed and utilized to seek optimal solutions to the optimization problem. The control performance and energy performance of this model based supervisory control strategy are evaluated on the central cooling water system of a high rise commercial office building by comparing with that of the model based supervisory control strategy using a genetic algorithm (GA) as the optimization tool, and the performance map based near optimal control strategy as well as other conventional control strategies for cooling water systems in terms of energy efficiency, control accuracy, computational cost etc. The results showed that this strategy is more energy efficient and computational cost effective than other methods for online practical application.

This article presents two design configurations for the secondary chilled water system in a super high-rise building being constructed in Hong Kong. Both configurations are implemented in this building to test and evaluate their operational performance.

HVAC systems are the major energy consumers in buildings. Operation and control of HVAC systems have significant impacts on the energy or cost efficiency of buildings besides their designs. Buildings nowadays are mostly equipped with comprehensive building automation systems (BASs) and building energy management control systems (EMCSs) that allow the possibility of enhancing and optimizing the operation and control of HVAC systems. Supervisory and optimal control, which addresses the energy or cost-efficient control of HVAC systems while providing the desired indoor comfort and healthy environment under the dynamic working conditions, is attracting more attention of the building professionals and the society and provides incentives to make more efforts in developing more extensive and robust control methods for HVAC systems. This paper provides a framework for categorizing the main supervisory and optimal control methods and optimization techniques developed and/or utilized in the HVAC field. The application characteristics of each control method and optimization technique are also identified and compared. A comprehensive overall review of the state of the art of the research and development, as well as application of supervisory and optimal control, in HVAC systems is also presented.

This paper presents a model based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. The supervisory control strategy seeks the minimum energy input to provide adequate cooling energy for buildings, taking into account the characteristics and interactions of central cooling water systems as well as the requirements and constraints of practical application. Simplified semi-physical chiller and cooling tower models are used to predict the system energy performance and environment quality as well as the system response to changes of control settings. A hybrid optimization technique, namely the PMES (performance map and exhaustive search) based method, is developed and utilized to seek optimal solutions to the optimization problem. The control performance and energy performance of this model based supervisory control strategy are evaluated on the central cooling water system of a high rise commercial office building by comparing with that of the model based supervisory control strategy using a genetic algorithm (GA) as the optimization tool, and the performance map based near optimal control strategy as well as other conventional control strategies for cooling water systems in terms of energy efficiency, control accuracy, computational cost etc. The results showed that this strategy is more energy efficient and computational cost effective than other methods for online practical application.

This article presents two design configurations for the secondary chilled water system in a super high-rise building being constructed in Hong Kong. Both configurations are implemented in this building to test and evaluate their operational performance.

This paper presents the online optimal control strategies of the central chilling system in a super high-rise building in Hong Kong. The work presented aims at developing a package of optimal control strategies and evaluating their energy saving potentials and finally implementing these strategies in the building to enhance its energy efficiency. Based on testing the effects of interactions within the cooling water system and chilled water system on the system operation performance, the optimal control strategies for the cooling water system and variable speed pumps with different installations in the secondary chilled water system are developed. These strategies are tested and validated in a virtual environment representing the real building system and its central chilling system prior to site implementation. The implementation issues the online control strategies for practical application are also addressed.

This article presents two design configurations for the secondary chilled water system in a super high-rise building being constructed in Hong Kong. Both configurations are implemented in this building to test and evaluate their operational performance.

HVAC systems are the major energy consumers in buildings. Operation and control of HVAC systems have significant impacts on the energy or cost efficiency of buildings besides their designs. Buildings nowadays are mostly equipped with comprehensive building automation systems (BASs) and building energy management control systems (EMCSs) that allow the possibility of enhancing and optimizing the operation and control of HVAC systems. Supervisory and optimal control, which addresses the energy or cost-efficient control of HVAC systems while providing the desired indoor comfort and healthy environment under the dynamic working conditions, is attracting more attention of the building professionals and the society and provides incentives to make more efforts in developing more extensive and robust control methods for HVAC systems. This paper provides a framework for categorizing the main supervisory and optimal control methods and optimization techniques developed and/or utilized in the HVAC field. The application characteristics of each control method and optimization technique are also identified and compared. A comprehensive overall review of the state of the art of the research and development, as well as application of supervisory and optimal control, in HVAC systems is also presented.

This paper presents a model based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. The supervisory control strategy seeks the minimum energy input to provide adequate cooling energy for buildings, taking into account the characteristics and interactions of central cooling water systems as well as the requirements and constraints of practical application. Simplified semi-physical chiller and cooling tower models are used to predict the system energy performance and environment quality as well as the system response to changes of control settings. A hybrid optimization technique, namely the PMES (performance map and exhaustive search) based method, is developed and utilized to seek optimal solutions to the optimization problem. The control performance and energy performance of this model based supervisory control strategy are evaluated on the central cooling water system of a high rise commercial office building by comparing with that of the model based supervisory control strategy using a genetic algorithm (GA) as the optimization tool, and the performance map based near optimal control strategy as well as other conventional control strategies for cooling water systems in terms of energy efficiency, control accuracy, computational cost etc. The results showed that this strategy is more energy efficient and computational cost effective than other methods for online practical application.

This paper presents the online optimal control strategies of the central chilling system in a super high-rise building in Hong Kong. The work presented aims at developing a package of optimal control strategies and evaluating their energy saving potentials and finally implementing these strategies in the building to enhance its energy efficiency. Based on testing the effects of interactions within the cooling water system and chilled water system on the system operation performance, the optimal control strategies for the cooling water system and variable speed pumps with different installations in the secondary chilled water system are developed. These strategies are tested and validated in a virtual environment representing the real building system and its central chilling system prior to site implementation. The implementation issues the online control strategies for practical application are also addressed.

Hong Kong is a typical subtropical region with frequently high humidity in late spring and summer seasons. Plume from evaporative cooling towers, which service air-conditioning systems of civil buildings, has aroused public concerns since 2000 when the fresh water evaporative cooling towers were allowed to be used for high energy efficiency and environmental issues. This paper presents the evaluation of the plume potential and its effect on the sizing of the plume abatement system in a large commercial office building in Hong Kong for practical application. This evaluation was conducted based on a dynamic simulation platform using the typical meteorological year of Hong Kong since the occurrence of the plume heavily depends on the state conditions of the exhaust air from cooling towers and the ambient air, while the state condition of the exhaust air is determined by the total building cooling load and the control strategies of cooling towers employed mainly for improving energy efficiency. The results show that the control strategies have a significant effect on the plume potential and further affect the system design and sizing of the plume abatement system.

Hong Kong is a typical subtropical region with frequently high humidity in late spring and summer seasons. Plume from evaporative cooling towers, which service air-conditioning systems of civil buildings, has aroused public concerns since 2000 when the fresh water evaporative cooling towers were allowed to be used for high energy efficiency and environmental issues. This paper presents the evaluation of the plume potential and its effect on the sizing of the plume abatement system in a large commercial office building in Hong Kong for practical application. This evaluation was conducted based on a dynamic simulation platform using the typical meteorological year of Hong Kong since the occurrence of the plume heavily depends on the state conditions of the exhaust air from cooling towers and the ambient air, while the state condition of the exhaust air is determined by the total building cooling load and the control strategies of cooling towers employed mainly for improving energy efficiency. The results show that the control strategies have a significant effect on the plume potential and further affect the system design and sizing of the plume abatement system.

Hong Kong is a typical subtropical region with frequently high humidity in late spring and summer seasons. Plume from evaporative cooling towers, which service air-conditioning systems of civil buildings, has aroused public concerns since 2000 when the fresh water evaporative cooling towers were allowed to be used for high energy efficiency and environmental issues. This paper presents the evaluation of the plume potential and its effect on the sizing of the plume abatement system in a large commercial office building in Hong Kong for practical application. This evaluation was conducted based on a dynamic simulation platform using the typical meteorological year of Hong Kong since the occurrence of the plume heavily depends on the state conditions of the exhaust air from cooling towers and the ambient air, while the state condition of the exhaust air is determined by the total building cooling load and the control strategies of cooling towers employed mainly for improving energy efficiency. The results show that the control strategies have a significant effect on the plume potential and further affect the system design and sizing of the plume abatement system.

This paper presents the online optimal control strategies of the central chilling system in a super high-rise building in Hong Kong. The work presented aims at developing a package of optimal control strategies and evaluating their energy saving potentials and finally implementing these strategies in the building to enhance its energy efficiency. Based on testing the effects of interactions within the cooling water system and chilled water system on the system operation performance, the optimal control strategies for the cooling water system and variable speed pumps with different installations in the secondary chilled water system are developed. These strategies are tested and validated in a virtual environment representing the real building system and its central chilling system prior to site implementation. The implementation issues the online control strategies for practical application are also addressed.

This paper presents a model based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. The supervisory control strategy seeks the minimum energy input to provide adequate cooling energy for buildings, taking into account the characteristics and interactions of central cooling water systems as well as the requirements and constraints of practical application. Simplified semi-physical chiller and cooling tower models are used to predict the system energy performance and environment quality as well as the system response to changes of control settings. A hybrid optimization technique, namely the PMES (performance map and exhaustive search) based method, is developed and utilized to seek optimal solutions to the optimization problem. The control performance and energy performance of this model based supervisory control strategy are evaluated on the central cooling water system of a high rise commercial office building by comparing with that of the model based supervisory control strategy using a genetic algorithm (GA) as the optimization tool, and the performance map based near optimal control strategy as well as other conventional control strategies for cooling water systems in terms of energy efficiency, control accuracy, computational cost etc. The results showed that this strategy is more energy efficient and computational cost effective than other methods for online practical application.

Hong Kong is a typical subtropical region with frequently high humidity in late spring and summer seasons. Plume from evaporative cooling towers, which service air-conditioning systems of civil buildings, has aroused public concerns since 2000 when the fresh water evaporative cooling towers were allowed to be used for high energy efficiency and environmental issues. This paper presents the evaluation of the plume potential and its effect on the sizing of the plume abatement system in a large commercial office building in Hong Kong for practical application. This evaluation was conducted based on a dynamic simulation platform using the typical meteorological year of Hong Kong since the occurrence of the plume heavily depends on the state conditions of the exhaust air from cooling towers and the ambient air, while the state condition of the exhaust air is determined by the total building cooling load and the control strategies of cooling towers employed mainly for improving energy efficiency. The results show that the control strategies have a significant effect on the plume potential and further affect the system design and sizing of the plume abatement system.