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Significant energy mismatch exists in solar water heating systems as the time and amount of solar energy supply are usually different from that of hot water demand. Using a hot water storage tank can reduce or eliminate such mismatch in short term while it is difficult to avoid this mismatch in long term. In many optimal design and life-cycle analysis methods, the energy mismatch is ignored which causes the system performance to be overestimated and also misleads the optimal design of the system. This paper presents a simplified method for optimizing the key parameters of solar water heating systems based on life-cycle energy analysis. This optimal method considering the energy mismatch phenomenon can be implemented through two steps. In the first step, a simplified energy model based hourly energy matching different components of the system, is developed for determining the operating performance of system with different solar collector areas and water storage volumes. In the second step, the law of diminishing marginal utility is employed to determine the optimum size of the system. The optimum size is identified when the maximal life-cycle net energy saving is achieved. A case study on the application of the proposed method in a building is presented as well.

Significant energy mismatch exists in solar water heating systems as the time and amount of solar energy supply are usually different from that of hot water demand. Using a hot water storage tank can reduce or eliminate such mismatch in short term while it is difficult to avoid this mismatch in long term. In many optimal design and life-cycle analysis methods, the energy mismatch is ignored which causes the system performance to be overestimated and also misleads the optimal design of the system. This paper presents a simplified method for optimizing the key parameters of solar water heating systems based on life-cycle energy analysis. This optimal method considering the energy mismatch phenomenon can be implemented through two steps. In the first step, a simplified energy model based hourly energy matching different components of the system, is developed for determining the operating performance of system with different solar collector areas and water storage volumes. In the second step, the law of diminishing marginal utility is employed to determine the optimum size of the system. The optimum size is identified when the maximal life-cycle net energy saving is achieved. A case study on the application of the proposed method in a building is presented as well.

Significant energy mismatch exists in solar water heating systems as the time and amount of solar energy supply are usually different from that of hot water demand. Using a hot water storage tank can reduce or eliminate such mismatch in short term while it is difficult to avoid this mismatch in long term. In many optimal design and life-cycle analysis methods, the energy mismatch is ignored which causes the system performance to be overestimated and also misleads the optimal design of the system. This paper presents a simplified method for optimizing the key parameters of solar water heating systems based on life-cycle energy analysis. This optimal method considering the energy mismatch phenomenon can be implemented through two steps. In the first step, a simplified energy model based hourly energy matching different components of the system, is developed for determining the operating performance of system with different solar collector areas and water storage volumes. In the second step, the law of diminishing marginal utility is employed to determine the optimum size of the system. The optimum size is identified when the maximal life-cycle net energy saving is achieved. A case study on the application of the proposed method in a building is presented as well.

Significant energy mismatch exists in solar water heating systems as the time and amount of solar energy supply are usually different from that of hot water demand. Using a hot water storage tank can reduce or eliminate such mismatch in short term while it is difficult to avoid this mismatch in long term. In many optimal design and life-cycle analysis methods, the energy mismatch is ignored which causes the system performance to be overestimated and also misleads the optimal design of the system. This paper presents a simplified method for optimizing the key parameters of solar water heating systems based on life-cycle energy analysis. This optimal method considering the energy mismatch phenomenon can be implemented through two steps. In the first step, a simplified energy model based hourly energy matching different components of the system, is developed for determining the operating performance of system with different solar collector areas and water storage volumes. In the second step, the law of diminishing marginal utility is employed to determine the optimum size of the system. The optimum size is identified when the maximal life-cycle net energy saving is achieved. A case study on the application of the proposed method in a building is presented as well.

This article presents a new fault detection and diagnosis strategy for centrifugal chillers of building air-conditioning systems. The strategy adopts a simplified physical chiller model calibrated using chiller operation data, which is convenient for practical application. Four schemes are developed to identify chiller model parameters based on available information and data from tests or manufacturers. A new semi-physical subcooling model is adopted by the chiller model. The overall heat transfer coefficient of the condenser is assumed to consist of two parts: one presenting the condensing section and the other presenting the subcooling section. By analyzing the changing trends of two proposed performance indexes (i.e., the normalized heat transfer coefficient and the fictitious subcooling temperature), the patterns in fault conditions can be obtained. The proposed method could therefore be used without the need of any fault data. It provides good applicability and convenience for actual applications. A comparison is also made with four typical existing fault detection and diagnosis methods. The results show that the proposed method has much higher detection and diagnosis ratios. © 2013 Taylor and Francis Group, LLC.

This article presents a new fault detection and diagnosis strategy for centrifugal chillers of building air-conditioning systems. The strategy adopts a simplified physical chiller model calibrated using chiller operation data, which is convenient for practical application. Four schemes are developed to identify chiller model parameters based on available information and data from tests or manufacturers. A new semi-physical subcooling model is adopted by the chiller model. The overall heat transfer coefficient of the condenser is assumed to consist of two parts: one presenting the condensing section and the other presenting the subcooling section. By analyzing the changing trends of two proposed performance indexes (i.e., the normalized heat transfer coefficient and the fictitious subcooling temperature), the patterns in fault conditions can be obtained. The proposed method could therefore be used without the need of any fault data. It provides good applicability and convenience for actual applications. A comparison is also made with four typical existing fault detection and diagnosis methods. The results show that the proposed method has much higher detection and diagnosis ratios. © 2013 Taylor and Francis Group, LLC.

This article presents a new fault detection and diagnosis strategy for centrifugal chillers of building air-conditioning systems. The strategy adopts a simplified physical chiller model calibrated using chiller operation data, which is convenient for practical application. Four schemes are developed to identify chiller model parameters based on available information and data from tests or manufacturers. A new semi-physical subcooling model is adopted by the chiller model. The overall heat transfer coefficient of the condenser is assumed to consist of two parts: one presenting the condensing section and the other presenting the subcooling section. By analyzing the changing trends of two proposed performance indexes (i.e., the normalized heat transfer coefficient and the fictitious subcooling temperature), the patterns in fault conditions can be obtained. The proposed method could therefore be used without the need of any fault data. It provides good applicability and convenience for actual applications. A comparison is also made with four typical existing fault detection and diagnosis methods. The results show that the proposed method has much higher detection and diagnosis ratios. © 2013 Taylor and Francis Group, LLC.

This paper presents a systematic methodology for optimizing the key design parameters of a solar water heating (SWH) system with multiple heating purposes in low energy buildings. The methodology is achieved through two steps. In the first step, a simplified energy model of the SWH system is developed and used to estimate system dynamic characteristics and annual energy performance, which is implemented in a spreadsheet. The behavior of the system with different collector areas and storage volumes can be determined realistically through matching multiple heating loads with the solar heat gains. In the second step, the law of diminishing marginal utility is employed to optimize the sizes of the system in order to maximize the life cycle net energy saving. The law describes that the marginal energy saving of the system decreases with the increase of the system size. Therefore, the optimum values of the system size can be determined in an easy-to-understand way, i.e.: the optimization objective (the maximal net energy saving of a SWH system) is achieved when the marginal operating energy saving equals to the marginal embodied energy. A case study on the application of the proposed method in a low-energy building is presented as well.

This article presents a new fault detection and diagnosis strategy for centrifugal chillers of building air-conditioning systems. The strategy adopts a simplified physical chiller model calibrated using chiller operation data, which is convenient for practical application. Four schemes are developed to identify chiller model parameters based on available information and data from tests or manufacturers. A new semi-physical subcooling model is adopted by the chiller model. The overall heat transfer coefficient of the condenser is assumed to consist of two parts: one presenting the condensing section and the other presenting the subcooling section. By analyzing the changing trends of two proposed performance indexes (i.e., the normalized heat transfer coefficient and the fictitious subcooling temperature), the patterns in fault conditions can be obtained. The proposed method could therefore be used without the need of any fault data. It provides good applicability and convenience for actual applications. A comparison is also made with four typical existing fault detection and diagnosis methods. The results show that the proposed method has much higher detection and diagnosis ratios. © 2013 Taylor and Francis Group, LLC.

Studies are conducted to investigate the impacts of shape-stabilized phase change material (SSPCM) and different control strategies on the energy consumption and peak load demand as well as electricity cost of building air-conditioning systems at typical summer conditions in two climates (subtropical and dry continental climates). An office building using a typical variable air volume (VAV) air-conditioning system was selected and simulated as the reference building in this study. Its envelopes were enhanced by integrating the SSPCM layers into its walls while the air-conditioning system and other configurations of the building remained unchanged. The building system was tested under two typical weather conditions and two typical electricity pricing policies (i.e. time-based pricing and energy-plus-demand-based pricing).Test results show that the use of SSPCM in the building could reduce the building electricity cost significantly (over 11% in electricity cost reduction and over 20% in peak load reduction), under two pricing policies by using load shifting control and demand limiting control respectively. This paper presents the test results and the evaluation on the energy performance and the optimal control strategies of air-conditioned commercial buildings with envelopes enhanced by SSPCM.

This article presents the test and evaluation of energy saving potentials of complex building central chilling systems using genetic algorithm (GA). The evaluation was conducted based on a simulated virtual system representing the actual complex central chilling system in a super high-rise building in Hong Kong. GA was used as the optimisation tool to search for globally optimal control settings. The simulated virtual system was used as the test platform and acted as the performance predictor in estimating the overall system performance and responses to the changes of control settings. The test results show that about 4.54—5.06% daily energy in the system studied can be saved by using optimal control settings, as compared to that using the conventional control settings. The results also show that the evaluation process by using the simulated virtual system and the GA optimiser is time costly due to strong dynamic effects of the simulated virtual system and the optimisation principle of GA. Practical applications: This article presents an approach for evaluating energy saving potentials of complex central chilling systems using GA. This approach can be used to identify maximum energy saving potentials in air-conditioning systems by optimising the major control variables simultaneously. The results can be used to guide the development of advanced control and optimisation strategies suitable for practical applications.

This paper presents a fault-tolerant supervisory control strategy for building condenser cooling water systems. The proposed strategy mainly consists of a model-based predictive control (MPC) scheme, a fault detection and diagnosis (FDD) scheme and a fault accommodation and tolerant (FAT) scheme. The MPC scheme using systematic optimization is employed to identify optimal control settings for the local process controllers. The FDD scheme is utilized to detect and diagnose major possible faults that may happen in the routine operation of condenser cooling water systems. The faults considered mainly include critical sensor faults, physical component performance degradations and malfunctions of control logics. According to the types of faults happened, the FAT scheme is then used to handle the faults in order to regain the control as far as possible. The performance of this strategy is tested and evaluated in a simulated virtual system representing the actual condenser cooling water system in a super high-rise building. The results show that the proposed strategy is capable of maintaining acceptable control performance and can help save about 0.18%~5.23% total energy of the chillers and cooling towers when the operation of condenser cooling water systems suffers from some faults, as compared to that using the same control strategy but without using the FAT scheme.

This paper presents the in-situ implementation and validation of a CO2-based adaptive demand-controlled ventilation (DCV) strategy in a super high-rise building in Hong Kong. The adaptive DCV strategy employs a dynamic multi-zone ventilation equation for multi-zone air-conditioning systems, in which a CO2-based dynamic occupancy detection scheme is used for online occupancy detection. This strategy is implemented in an independent Intelligent Building Management and Integration platform (IBmanager), which communicates with the main station of the Building Management System (BMS) through a communication protocol and interface. The performance of this DCV strategy is practically tested and validated by comparing with that of the original fixed outdoor air flow rate control strategy used in site. The implementation architecture and test results including energy and environmental performances represented. Since the accuracy and reliability of the major measurement instrumentations affect the actual performance of the DCV strategy significantly, the commissioning and calibration of major measurement instrumentations are presented as well.

This paper presents a model-based supervisory and optimal control strategy for central chiller plants to enhance their energy efficiency and control performance. The optimal strategy is formulated using simplified models of major components and the genetic algorithm (GA). The simplified models are used as the performance predictors to estimate the system energy performance and response to the changes of control settings and working conditions. Since the accuracy of the models has significant impacts on the overall prediction results, the models used are linear in the parameters and the recursive least squares (RLS) estimation technique with exponential forgetting is used to identify and update the model parameters online. That is to ensure that the linear models can provide reliable and accurate estimates when working condition changes. The GA, as a global optimization tool, is used to solve the optimization problem and search for globally optimal control settings. The performance of this strategy is tested and evaluated in a simulated virtual system representing the actual central chiller plant in a super high-rise building under various working conditions. The results showed that this strategy can save about 0.73–2.55% daily energy of the system studied, as compared to a reference strategy using conventional settings.

This paper presents a robust strategy for online fault detection and optimal control of condenser cooling water systems. The optimal control strategy is formulated using a model-based approach, in which simplified models and a hybrid quick search (HQS) method are used to optimize the performance of the overall system by changing the settings of the local process controllers. A system level online fault detection scheme is embedded into the control system and used to monitor whether the system operates in a healthy condition. The faults considered are mainly the component performance degradations. When a fault is detected, the control system will be reconstructed to regain the control through using robust schemes. The performance of the proposed strategy is tested and evaluated against on a simulated virtual system representing the actual condenser cooling water system in a super high-rise building. The results show that the fault detection scheme is effective in identifying system performance degradations and the fault-tolerant control strategy with online fault detection and optimal control can enhance the overall system performance significantly when the operation of condenser cooling water systems suffers from performance degradations, as compared to that using optimal control only.

Studies are conducted to investigate the impacts of shape-stabilized phase change material (SSPCM) and different control strategies on the energy consumption and peak load demand as well as electricity cost of building air-conditioning systems at typical summer conditions in two climates (subtropical and dry continental climates). An office building using a typical variable air volume (VAV) air-conditioning system was selected and simulated as the reference building in this study. Its envelopes were enhanced by integrating the SSPCM layers into its walls while the air-conditioning system and other configurations of the building remained unchanged. The building system was tested under two typical weather conditions and two typical electricity pricing policies (i.e. time-based pricing and energy-plus-demand-based pricing).Test results show that the use of SSPCM in the building could reduce the building electricity cost significantly (over 11% in electricity cost reduction and over 20% in peak load reduction), under two pricing policies by using load shifting control and demand limiting control respectively. This paper presents the test results and the evaluation on the energy performance and the optimal control strategies of air-conditioned commercial buildings with envelopes enhanced by SSPCM.

This article presents the test and evaluation of energy saving potentials of complex building central chilling systems using genetic algorithm (GA). The evaluation was conducted based on a simulated virtual system representing the actual complex central chilling system in a super high-rise building in Hong Kong. GA was used as the optimisation tool to search for globally optimal control settings. The simulated virtual system was used as the test platform and acted as the performance predictor in estimating the overall system performance and responses to the changes of control settings. The test results show that about 4.54—5.06% daily energy in the system studied can be saved by using optimal control settings, as compared to that using the conventional control settings. The results also show that the evaluation process by using the simulated virtual system and the GA optimiser is time costly due to strong dynamic effects of the simulated virtual system and the optimisation principle of GA. Practical applications: This article presents an approach for evaluating energy saving potentials of complex central chilling systems using GA. This approach can be used to identify maximum energy saving potentials in air-conditioning systems by optimising the major control variables simultaneously. The results can be used to guide the development of advanced control and optimisation strategies suitable for practical applications.

This paper presents a fault-tolerant supervisory control strategy for building condenser cooling water systems. The proposed strategy mainly consists of a model-based predictive control (MPC) scheme, a fault detection and diagnosis (FDD) scheme and a fault accommodation and tolerant (FAT) scheme. The MPC scheme using systematic optimization is employed to identify optimal control settings for the local process controllers. The FDD scheme is utilized to detect and diagnose major possible faults that may happen in the routine operation of condenser cooling water systems. The faults considered mainly include critical sensor faults, physical component performance degradations and malfunctions of control logics. According to the types of faults happened, the FAT scheme is then used to handle the faults in order to regain the control as far as possible. The performance of this strategy is tested and evaluated in a simulated virtual system representing the actual condenser cooling water system in a super high-rise building. The results show that the proposed strategy is capable of maintaining acceptable control performance and can help save about 0.18%~5.23% total energy of the chillers and cooling towers when the operation of condenser cooling water systems suffers from some faults, as compared to that using the same control strategy but without using the FAT scheme.

This paper presents the in-situ implementation and validation of a CO2-based adaptive demand-controlled ventilation (DCV) strategy in a super high-rise building in Hong Kong. The adaptive DCV strategy employs a dynamic multi-zone ventilation equation for multi-zone air-conditioning systems, in which a CO2-based dynamic occupancy detection scheme is used for online occupancy detection. This strategy is implemented in an independent Intelligent Building Management and Integration platform (IBmanager), which communicates with the main station of the Building Management System (BMS) through a communication protocol and interface. The performance of this DCV strategy is practically tested and validated by comparing with that of the original fixed outdoor air flow rate control strategy used in site. The implementation architecture and test results including energy and environmental performances represented. Since the accuracy and reliability of the major measurement instrumentations affect the actual performance of the DCV strategy significantly, the commissioning and calibration of major measurement instrumentations are presented as well.

This paper presents a model-based supervisory and optimal control strategy for central chiller plants to enhance their energy efficiency and control performance. The optimal strategy is formulated using simplified models of major components and the genetic algorithm (GA). The simplified models are used as the performance predictors to estimate the system energy performance and response to the changes of control settings and working conditions. Since the accuracy of the models has significant impacts on the overall prediction results, the models used are linear in the parameters and the recursive least squares (RLS) estimation technique with exponential forgetting is used to identify and update the model parameters online. That is to ensure that the linear models can provide reliable and accurate estimates when working condition changes. The GA, as a global optimization tool, is used to solve the optimization problem and search for globally optimal control settings. The performance of this strategy is tested and evaluated in a simulated virtual system representing the actual central chiller plant in a super high-rise building under various working conditions. The results showed that this strategy can save about 0.73–2.55% daily energy of the system studied, as compared to a reference strategy using conventional settings.

This paper presents a robust strategy for online fault detection and optimal control of condenser cooling water systems. The optimal control strategy is formulated using a model-based approach, in which simplified models and a hybrid quick search (HQS) method are used to optimize the performance of the overall system by changing the settings of the local process controllers. A system level online fault detection scheme is embedded into the control system and used to monitor whether the system operates in a healthy condition. The faults considered are mainly the component performance degradations. When a fault is detected, the control system will be reconstructed to regain the control through using robust schemes. The performance of the proposed strategy is tested and evaluated against on a simulated virtual system representing the actual condenser cooling water system in a super high-rise building. The results show that the fault detection scheme is effective in identifying system performance degradations and the fault-tolerant control strategy with online fault detection and optimal control can enhance the overall system performance significantly when the operation of condenser cooling water systems suffers from performance degradations, as compared to that using optimal control only.

Studies are conducted to investigate the impacts of shape-stabilized phase change material (SSPCM) and different control strategies on the energy consumption and peak load demand as well as electricity cost of building air-conditioning systems at typical summer conditions in two climates (subtropical and dry continental climates). An office building using a typical variable air volume (VAV) air-conditioning system was selected and simulated as the reference building in this study. Its envelopes were enhanced by integrating the SSPCM layers into its walls while the air-conditioning system and other configurations of the building remained unchanged. The building system was tested under two typical weather conditions and two typical electricity pricing policies (i.e. time-based pricing and energy-plus-demand-based pricing).Test results show that the use of SSPCM in the building could reduce the building electricity cost significantly (over 11% in electricity cost reduction and over 20% in peak load reduction), under two pricing policies by using load shifting control and demand limiting control respectively. This paper presents the test results and the evaluation on the energy performance and the optimal control strategies of air-conditioned commercial buildings with envelopes enhanced by SSPCM.

This article presents the test and evaluation of energy saving potentials of complex building central chilling systems using genetic algorithm (GA). The evaluation was conducted based on a simulated virtual system representing the actual complex central chilling system in a super high-rise building in Hong Kong. GA was used as the optimisation tool to search for globally optimal control settings. The simulated virtual system was used as the test platform and acted as the performance predictor in estimating the overall system performance and responses to the changes of control settings. The test results show that about 4.54—5.06% daily energy in the system studied can be saved by using optimal control settings, as compared to that using the conventional control settings. The results also show that the evaluation process by using the simulated virtual system and the GA optimiser is time costly due to strong dynamic effects of the simulated virtual system and the optimisation principle of GA. Practical applications: This article presents an approach for evaluating energy saving potentials of complex central chilling systems using GA. This approach can be used to identify maximum energy saving potentials in air-conditioning systems by optimising the major control variables simultaneously. The results can be used to guide the development of advanced control and optimisation strategies suitable for practical applications.

This paper presents a fault-tolerant supervisory control strategy for building condenser cooling water systems. The proposed strategy mainly consists of a model-based predictive control (MPC) scheme, a fault detection and diagnosis (FDD) scheme and a fault accommodation and tolerant (FAT) scheme. The MPC scheme using systematic optimization is employed to identify optimal control settings for the local process controllers. The FDD scheme is utilized to detect and diagnose major possible faults that may happen in the routine operation of condenser cooling water systems. The faults considered mainly include critical sensor faults, physical component performance degradations and malfunctions of control logics. According to the types of faults happened, the FAT scheme is then used to handle the faults in order to regain the control as far as possible. The performance of this strategy is tested and evaluated in a simulated virtual system representing the actual condenser cooling water system in a super high-rise building. The results show that the proposed strategy is capable of maintaining acceptable control performance and can help save about 0.18%~5.23% total energy of the chillers and cooling towers when the operation of condenser cooling water systems suffers from some faults, as compared to that using the same control strategy but without using the FAT scheme.

This paper presents the in-situ implementation and validation of a CO2-based adaptive demand-controlled ventilation (DCV) strategy in a super high-rise building in Hong Kong. The adaptive DCV strategy employs a dynamic multi-zone ventilation equation for multi-zone air-conditioning systems, in which a CO2-based dynamic occupancy detection scheme is used for online occupancy detection. This strategy is implemented in an independent Intelligent Building Management and Integration platform (IBmanager), which communicates with the main station of the Building Management System (BMS) through a communication protocol and interface. The performance of this DCV strategy is practically tested and validated by comparing with that of the original fixed outdoor air flow rate control strategy used in site. The implementation architecture and test results including energy and environmental performances represented. Since the accuracy and reliability of the major measurement instrumentations affect the actual performance of the DCV strategy significantly, the commissioning and calibration of major measurement instrumentations are presented as well.

This paper presents a model-based supervisory and optimal control strategy for central chiller plants to enhance their energy efficiency and control performance. The optimal strategy is formulated using simplified models of major components and the genetic algorithm (GA). The simplified models are used as the performance predictors to estimate the system energy performance and response to the changes of control settings and working conditions. Since the accuracy of the models has significant impacts on the overall prediction results, the models used are linear in the parameters and the recursive least squares (RLS) estimation technique with exponential forgetting is used to identify and update the model parameters online. That is to ensure that the linear models can provide reliable and accurate estimates when working condition changes. The GA, as a global optimization tool, is used to solve the optimization problem and search for globally optimal control settings. The performance of this strategy is tested and evaluated in a simulated virtual system representing the actual central chiller plant in a super high-rise building under various working conditions. The results showed that this strategy can save about 0.73–2.55% daily energy of the system studied, as compared to a reference strategy using conventional settings.

This paper presents a robust strategy for online fault detection and optimal control of condenser cooling water systems. The optimal control strategy is formulated using a model-based approach, in which simplified models and a hybrid quick search (HQS) method are used to optimize the performance of the overall system by changing the settings of the local process controllers. A system level online fault detection scheme is embedded into the control system and used to monitor whether the system operates in a healthy condition. The faults considered are mainly the component performance degradations. When a fault is detected, the control system will be reconstructed to regain the control through using robust schemes. The performance of the proposed strategy is tested and evaluated against on a simulated virtual system representing the actual condenser cooling water system in a super high-rise building. The results show that the fault detection scheme is effective in identifying system performance degradations and the fault-tolerant control strategy with online fault detection and optimal control can enhance the overall system performance significantly when the operation of condenser cooling water systems suffers from performance degradations, as compared to that using optimal control only.

Large primary-secondary chilled water systems often suffer from low chilled water temperature difference (i.e., known as low delta-T central plant syndrome) during operation. This paper presents a detailed study to investigate the feasibility and potential benefits related to the use of a bypass check valve in the chiller decouple line to solve this operational problem and hence, to improve the overall system operating efficiency. The objective of this study is to provide some guidance and necessary confidence as well as the awareness of potential problems that may arise when a bypass check valve is considered to handle the low delta-T syndrome. Based on testing the effects of the low delta-T syndrome, the performances of the systems with and without the bypass check valve are then evaluated by using a simulated virtual system. In the tests, the low delta-T syndrome was introduced through air-side fouling by changing the air-side thermal resistance coefficient in the cooling coil model. The results show that, if the chilled water system suffered from 20% air-side fouling, about 6.77% total energy of the chilled water system studied can be saved when a bypass check valve is used, as compared to that without the bypass check valve.

Large primary-secondary chilled water systems often suffer from low chilled water temperature difference (i.e., known as low delta-T central plant syndrome) during operation. This paper presents a detailed study to investigate the feasibility and potential benefits related to the use of a bypass check valve in the chiller decouple line to solve this operational problem and hence, to improve the overall system operating efficiency. The objective of this study is to provide some guidance and necessary confidence as well as the awareness of potential problems that may arise when a bypass check valve is considered to handle the low delta-T syndrome. Based on testing the effects of the low delta-T syndrome, the performances of the systems with and without the bypass check valve are then evaluated by using a simulated virtual system. In the tests, the low delta-T syndrome was introduced through air-side fouling by changing the air-side thermal resistance coefficient in the cooling coil model. The results show that, if the chilled water system suffered from 20% air-side fouling, about 6.77% total energy of the chilled water system studied can be saved when a bypass check valve is used, as compared to that without the bypass check valve.

Large primary-secondary chilled water systems often suffer from low chilled water temperature difference (i.e., known as low delta-T central plant syndrome) during operation. This paper presents a detailed study to investigate the feasibility and potential benefits related to the use of a bypass check valve in the chiller decouple line to solve this operational problem and hence, to improve the overall system operating efficiency. The objective of this study is to provide some guidance and necessary confidence as well as the awareness of potential problems that may arise when a bypass check valve is considered to handle the low delta-T syndrome. Based on testing the effects of the low delta-T syndrome, the performances of the systems with and without the bypass check valve are then evaluated by using a simulated virtual system. In the tests, the low delta-T syndrome was introduced through air-side fouling by changing the air-side thermal resistance coefficient in the cooling coil model. The results show that, if the chilled water system suffered from 20% air-side fouling, about 6.77% total energy of the chilled water system studied can be saved when a bypass check valve is used, as compared to that without the bypass check valve.

Studies are conducted to investigate the impacts of shape-stabilized phase change material (SSPCM) and different control strategies on the energy consumption and peak load demand as well as electricity cost of building air-conditioning systems at typical summer conditions in two climates (subtropical and dry continental climates). An office building using a typical variable air volume (VAV) air-conditioning system was selected and simulated as the reference building in this study. Its envelopes were enhanced by integrating the SSPCM layers into its walls while the air-conditioning system and other configurations of the building remained unchanged. The building system was tested under two typical weather conditions and two typical electricity pricing policies (i.e. time-based pricing and energy-plus-demand-based pricing).Test results show that the use of SSPCM in the building could reduce the building electricity cost significantly (over 11% in electricity cost reduction and over 20% in peak load reduction), under two pricing policies by using load shifting control and demand limiting control respectively. This paper presents the test results and the evaluation on the energy performance and the optimal control strategies of air-conditioned commercial buildings with envelopes enhanced by SSPCM.

Large primary-secondary chilled water systems often suffer from low chilled water temperature difference (i.e., known as low delta-T central plant syndrome) during operation. This paper presents a detailed study to investigate the feasibility and potential benefits related to the use of a bypass check valve in the chiller decouple line to solve this operational problem and hence, to improve the overall system operating efficiency. The objective of this study is to provide some guidance and necessary confidence as well as the awareness of potential problems that may arise when a bypass check valve is considered to handle the low delta-T syndrome. Based on testing the effects of the low delta-T syndrome, the performances of the systems with and without the bypass check valve are then evaluated by using a simulated virtual system. In the tests, the low delta-T syndrome was introduced through air-side fouling by changing the air-side thermal resistance coefficient in the cooling coil model. The results show that, if the chilled water system suffered from 20% air-side fouling, about 6.77% total energy of the chilled water system studied can be saved when a bypass check valve is used, as compared to that without the bypass check valve.

This article presents the test and evaluation of energy saving potentials of complex building central chilling systems using genetic algorithm (GA). The evaluation was conducted based on a simulated virtual system representing the actual complex central chilling system in a super high-rise building in Hong Kong. GA was used as the optimisation tool to search for globally optimal control settings. The simulated virtual system was used as the test platform and acted as the performance predictor in estimating the overall system performance and responses to the changes of control settings. The test results show that about 4.54—5.06% daily energy in the system studied can be saved by using optimal control settings, as compared to that using the conventional control settings. The results also show that the evaluation process by using the simulated virtual system and the GA optimiser is time costly due to strong dynamic effects of the simulated virtual system and the optimisation principle of GA. Practical applications: This article presents an approach for evaluating energy saving potentials of complex central chilling systems using GA. This approach can be used to identify maximum energy saving potentials in air-conditioning systems by optimising the major control variables simultaneously. The results can be used to guide the development of advanced control and optimisation strategies suitable for practical applications.

This paper presents a fault-tolerant supervisory control strategy for building condenser cooling water systems. The proposed strategy mainly consists of a model-based predictive control (MPC) scheme, a fault detection and diagnosis (FDD) scheme and a fault accommodation and tolerant (FAT) scheme. The MPC scheme using systematic optimization is employed to identify optimal control settings for the local process controllers. The FDD scheme is utilized to detect and diagnose major possible faults that may happen in the routine operation of condenser cooling water systems. The faults considered mainly include critical sensor faults, physical component performance degradations and malfunctions of control logics. According to the types of faults happened, the FAT scheme is then used to handle the faults in order to regain the control as far as possible. The performance of this strategy is tested and evaluated in a simulated virtual system representing the actual condenser cooling water system in a super high-rise building. The results show that the proposed strategy is capable of maintaining acceptable control performance and can help save about 0.18%~5.23% total energy of the chillers and cooling towers when the operation of condenser cooling water systems suffers from some faults, as compared to that using the same control strategy but without using the FAT scheme.

This paper presents a model-based supervisory and optimal control strategy for central chiller plants to enhance their energy efficiency and control performance. The optimal strategy is formulated using simplified models of major components and the genetic algorithm (GA). The simplified models are used as the performance predictors to estimate the system energy performance and response to the changes of control settings and working conditions. Since the accuracy of the models has significant impacts on the overall prediction results, the models used are linear in the parameters and the recursive least squares (RLS) estimation technique with exponential forgetting is used to identify and update the model parameters online. That is to ensure that the linear models can provide reliable and accurate estimates when working condition changes. The GA, as a global optimization tool, is used to solve the optimization problem and search for globally optimal control settings. The performance of this strategy is tested and evaluated in a simulated virtual system representing the actual central chiller plant in a super high-rise building under various working conditions. The results showed that this strategy can save about 0.73–2.55% daily energy of the system studied, as compared to a reference strategy using conventional settings.

This paper presents the in-situ implementation and validation of a CO2-based adaptive demand-controlled ventilation (DCV) strategy in a super high-rise building in Hong Kong. The adaptive DCV strategy employs a dynamic multi-zone ventilation equation for multi-zone air-conditioning systems, in which a CO2-based dynamic occupancy detection scheme is used for online occupancy detection. This strategy is implemented in an independent Intelligent Building Management and Integration platform (IBmanager), which communicates with the main station of the Building Management System (BMS) through a communication protocol and interface. The performance of this DCV strategy is practically tested and validated by comparing with that of the original fixed outdoor air flow rate control strategy used in site. The implementation architecture and test results including energy and environmental performances represented. Since the accuracy and reliability of the major measurement instrumentations affect the actual performance of the DCV strategy significantly, the commissioning and calibration of major measurement instrumentations are presented as well.

This paper presents a robust strategy for online fault detection and optimal control of condenser cooling water systems. The optimal control strategy is formulated using a model-based approach, in which simplified models and a hybrid quick search (HQS) method are used to optimize the performance of the overall system by changing the settings of the local process controllers. A system level online fault detection scheme is embedded into the control system and used to monitor whether the system operates in a healthy condition. The faults considered are mainly the component performance degradations. When a fault is detected, the control system will be reconstructed to regain the control through using robust schemes. The performance of the proposed strategy is tested and evaluated against on a simulated virtual system representing the actual condenser cooling water system in a super high-rise building. The results show that the fault detection scheme is effective in identifying system performance degradations and the fault-tolerant control strategy with online fault detection and optimal control can enhance the overall system performance significantly when the operation of condenser cooling water systems suffers from performance degradations, as compared to that using optimal control only.

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.

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.

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 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 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.