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The lessons learned from the COVID-19 pandemic emphasize the need for building HVAC systems to be adaptable and prepared to adjust their operation for infection risk mitigation for future pandemics. Most guidelines suggest increasing outdoor air fraction in HVAC systems during pandemics. However, this approach is not energy-efficient due to the conditioning of additional outdoor air, and many practical systems face limitations in introducing more outdoor air than normal due to capacity or design constraints. Therefore, there is an urgent need for an alternative solution for HVAC system operation during pandemics that is energy-efficient, can effectively mitigate infection risks and does not require extensive retrofits to existing systems. To meet this need, this study proposes a practical real-time control strategy for high-performance HVAC operation in response to potential pandemic outbreaks. First, a supply air temperature (SAT) reset scheme for infection risk mitigation is proposed based on Mamdani fuzzy inference theory. Then, a coordinated control scheme is proposed to coordinate SAT reset with chilled water temperature adjustment for energy-efficiency enhancement. This strategy does not require system equipment retrofits but only changes in control logic to transition to pandemic operation. The effectiveness of the proposed strategy is validated in a high-fidelity Modelica-based simulation environment under various weather conditions. Results show that, compared to normal operation, the proposed strategy can significantly reduce new infection cases by 32∼46 % without increasing energy use, and may even achieve slight energy savings of 9∼13 %, while maintaining expected occupant comfort. • Develop a practical control strategy for HVAC operation in post-pandemic era. • Propose a supply air temperature (SAT) reset scheme for infection risk mitigation. • Propose a scheme to coordinate SAT reset with water-side control for energy saving. • Effective infection control, energy efficiency and occupant comfort are achieved. • The strategy only requires changes to system control logic for pandemic operation. [ABSTRACT FROM AUTHOR]

The large data center electricity consumption is a growing global concern. To be environment-friendly and to enhance energy efficiency in operation, data center cooling systems adopt a variety of advanced cooling and renewable energy technologies such as free cooling. However, these free cooling systems are not optimally designed in field practices, and their energy efficiencies are much lower than that of the ideal case. In this study, optimal designs in water piping, pumps and equipment sequencing control are introduced to maximize the cooling efficiency of free cooling systems. It finds that the use of distribution headers around cooling towers and pumps, the maximization of the number of operating cooling towers, the minimization of the number of operating pumps and the mixed use of large and small single-speed pumps can reduce the system's power consumption by 60% under certain operating conditions. The results also show that the designs can reduce the annual energy consumption by 3–15% depending on the climate conditions. • Introduce an optimal design of free cooling systems in data centers. • Operate more cooling towers and fewer pumps to improve efficiency. • Design with a mix of small and large single-speed pumps for better efficiency. • Reduce cooling system power consumption by 60% under specific conditions. • Reduce annual energy consumption by 3–15% in different climates. [ABSTRACT FROM AUTHOR]

The recent COVID-19 pandemic has highlighted the need to adapt the control of building HVAC systems to limit disease transmission in indoor environments. However, such operational adjustments may significantly increase energy use, creating a complex trade-off problem between infection risk mitigation and energy efficiency. Moreover, practical constraints, such as maintaining comfortable temperature and humidity levels for occupants and limited system equipment capacity, can limit the flexibility of operational adjustments, further exacerbating the challenge of finding optimal operational solutions. This paper therefore proposes an optimal control strategy for multi-zone VAV systems that adapts to switching between normal and pandemic modes. The strategy considers dual optimization objectives: minimizing system energy use and disease transmission risk, while also considering all practical constraints. Optimal operational parameters can be determined to achieve the best trade-off between these objectives based on pandemic conditions. Additionally, a new metric called "effective fresh air factor" is proposed to quantify the impact of multi-zone VAV systems on disease transmission in building zones. The effectiveness of the proposed strategy is evaluated in a simulated building and air-conditioning environment. Results show that the VAV system has superior ability to reduce transmission risk through operational adjustments, achieving a decrease in disease transmission risk by 25%–75% compared to normal operation. [Display omitted] • A multi-objective optimal control strategy is proposed for multi-zone VAV systems. • This strategy can adapt to switching between normal and pandemic modes. • Best trade-off between minimizing energy use and infection risk can be achieved. • A metric is proposed to quantify the impact of VAV systems on disease transmission. • The potential of VAV systems in reducing infection risk is quantitatively explored. [ABSTRACT FROM AUTHOR]

Highlights • A new approach for design optimization of zero/low energy buildings is proposed. • The approach integrates multi-stage sensitivity analysis and design optimization. • An optimization method for buildings without heating in subtropics is developed. • Concern of winter thermal discomfort affects the selection of key design parameters. • Such concern affects the optimal design of buildings without heating in subtropics. Abstract To reduce building energy use and mitigate CO 2 emissions, zero/low energy buildings have attracted increasing attention. However, the impacts of the main design parameters and optimal design for zero/low energy buildings only provided with cooling in subtropical regions are seldom studied, and the objectives for building performance assessment and design optimization in such particular situations are not addressed sufficiently. In this study, the impacts of the main design parameters and optimal design for zero/low energy buildings in subtropical regions are studied. A holistic approach integrating sensitivity analysis and design optimization is developed for zero/low energy buildings. A new optimization objective is proposed, which considers annual energy consumption and winter thermal discomfort, for buildings without heating provision. A multi-stage sensitivity analysis approach is proposed to identify the key design parameters for design optimization. The key building design parameters are optimized to minimize the optimization objective using the genetic algorithm. A case study is conducted, using the zero carbon building (ZCB) in Hong Kong as a reference building, to illustrate the implementation steps and effectiveness of the proposed approach. This paper presents the identification of the key influential design parameters in the subtropical climate and the design optimization method of zero/low energy buildings as well as the procedures and the results of the case study. [ABSTRACT FROM AUTHOR]

Due to the rapid rise of power consumption of data centers in recent years, much work has been done to develop energy-efficient design, controls and diagnosis of their cooling systems, while the energy system simulation is used as an effective tool. However, existing models of information technology (IT) equipment of data centers cannot well represent the effects of IT equipment design and operation status on the data center cooling demand, and this hinders the development of the energy saving cooling technologies of data centers. To address this issue, this paper introduces a power consumption model of IT equipment in data centers with coefficients and modeling script provided for immediate use in data center energy system simulation. This energy model can be used to simulate energy performance of typical IT equipment in data centers under real-time dynamic operation conditions conveniently and effectively without the need of data other than the specifications of a data center design and IT equipment manuals. Its use with a commonly used building simulation program is demonstrated with a building model of a typical large office in a subtropical area. The results show that the model can represent the change of power consumption of data centers with different IT equipment designs and operation appropriately. [ABSTRACT FROM AUTHOR]

Conventional design of chiller plant is typically based on the peak cooling loads of buildings, while the cooling load reaches its peak level for only a small proportion of time in a year. This results in that even a perfectly designed chiller plant could be very significantly oversized in actual operation and it thus causes significant energy wastes. In this paper, an uncertainty-based optimal design based on probabilistic approach is proposed to optimize the chiller plant design. It ensures that the chiller plant operate at a high efficiency and the minimum annual total cost (including annual operational cost and annual capital cost) could be achieved under various possible cooling load conditions, considering the uncertain variables in cooling load calculation (i.e., weather conditions). On the premise of determining the minimum sufficient number of Monte Carlo simulation, this method maximizes the operating COP (coefficient of performance) and minimizing the annual total cost. A case study on the chiller plant of a building in Hong Kong is conducted to demonstrate the design process and validate the uncertainty-based optimal design method. [ABSTRACT FROM AUTHOR]

Abstract: 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. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a strategy for improving the reliability and the energy efficiency of chiller sequencing control based on the total cooling load measurement of centralized multiple centrifugal chiller plants. The improvement is achieved as follows. Firstly, a fused measurement of building cooling load is used to replace the direct/indirect measurement. Secondly, the maximum cooling capacity of individual chillers is computed online using a simplified centrifugal chiller model. Thirdly, the online computed maximum cooling capacity is calibrated according to the quality of the fused measurement in order to deal with the possible misbehaviours in measurement instruments. A simplified model for computing the maximum cooling capacity is developed and validated using field data. The performance of the proposed chiller sequencing control strategy is tested and compared with a conventional chiller sequencing control algorithm. Test results are presented showing that the proposed strategy can effectively improve the reliability of chiller sequencing control and reduce the energy consumption of chiller plants. [Copyright &y& Elsevier]

Abstract: Hong Kong is located in a typical subtropical region. The buildings in Hong Kong are subjected to high cooling demands for their air-conditioning systems throughout most of the year, and their contribution toward the total energy consumption is about 40%. Therefore, energy efficiency in buildings is essential to reduce the global energy use and improve the local environmental sustainability. This paper provides an overall review of the building energy research and efforts in Hong Kong over the last decade. Various aspects and energy saving measures, including energy policy, energy audit, design, control, diagnosis, building performance evaluation and renewable energy systems, studied or used to enhance the energy efficiency in buildings are reviewed. A brief introduction of the Hong Kong Building Energy Codes (BEC) and Hong Kong Building Environmental Assessment Method (HK-BEAM) are also provided to present the efforts of the local government and community on energy efficiency in buildings. This review aims at providing building researchers and practitioners a better understanding of buildings energy saving opportunities and approaches in cities particularly in subtropical regions and taking further proper actions to promote buildings energy efficiency and conservation. [Copyright &y& Elsevier]

Abstract: Heat pumps could be used to produce hot water for hybrid cooling towers for preventing the occurrence of plume in subtropical regions. The evaporative side of the heat pump system could be arranged either at the inlet side or at the outlet side of these cooling towers for cooling down the cooling water temperature. Alternatively, the evaporative side of the heat pump system could also be arranged at the evaporative side of chillers to reduce return chilled water temperature and therefore to reduce the cooling load of chillers. This study presents the evaluation of the impacts of these three arrangements of the heat pump system on the plume control performance and the energy performance in a large-scale chiller plant in Hong Kong. The performance prediction and evaluation of the chiller plant and the plume abatement system were conducted on a dynamic simulation platform. The results show that these three arrangements have almost the same plume control performance with sufficient plume control capability. The results also show that the arrangement of the evaporative side of the heat pump system for cooling down return chilled water temperature has much better performance that the other two arrangements for improving the overall energy efficiency. [Copyright &y& Elsevier]

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. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

Abstract: This paper reports the evaluations of energy efficiency, plume potential as well as plume control of a huge chiller plant using water-evaporative cooling towers for heat rejection for a super high-rising commercial office building in a subtropical region of Hong Kong. The evaluations were carried out in a dynamic Transient Simulation Program (TRNSYS)-based simulation platform using alternative control strategies including set-point control logics of the supply cooling water temperature and cooling tower fan modulation control methods as well as different number control means of cooling towers. The results show that different control strategies have significant effects on the energy efficiency of the chiller plant. The quantification of the energy efficiency demonstrates significant energy-saving potential by using advanced technologies for implementing optimal control strategies in this cooling system. The results also reveal that the plume may occur frequently in spring and summer seasons and occasionally in other months due to the odd subtropical weather conditions. Control strategies also have significant effects on the frequency of the plume occurrence. The effective energy efficiency control and effective plume control using wet–dry (i.e., hybrid) cooling towers are also discussed. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

Combining demand-controlled ventilation (DCV) and economizer control can achieve adequate and even better indoor air quality with minimum cooling/heating energy consumption in buildings. The control instability during the transition processes between different control modes is among the major difficulties faced when combining DCV control with economizer control in applications. The practical energy benefit is another concern when using free cooling in the subtropical climate like Hong Kong. A robust control strategy, using “freezing”, gain scheduling, I-term reset and feedback transition control for different transition processes, is developed addressing the instability problems. The energy benefit of using economizer control is evaluated by over one year''s comparison tests on two air-handling units in a building. [Copyright &y& Elsevier]

• A novel strategy is proposed for optimal control of VAV air-conditioning systems. • It correlates the resetting of the temperature set-points in individual zones. • It alleviates programming challenges for optimal control of multi-zone buildings. • It is very effective to balance the thermal comfort, IAQ and energy use. • Optimal control can be deployed on local control devices of limited capacity. Determining the proper trade-off among thermal comfort, Indoor Air Quality (IAQ) and energy use is important for optimal control of air-conditioning systems. The number of optimization variables increases as systems become increasingly complex, as with multi-zone VAV (Variable Air Volume) air-conditioning systems, leading to large-scale mathematics programming challenges and inconveniences in the implementation of conventional centralized optimization strategies. This paper therefore proposes a real-time optimal control strategy adopting a multi-agent based distributed optimization method for multi-zone VAV air-conditioning systems. The proposed strategy consists of three novel schemes. First, a temperature set-point reset scheme adopts a linear rule to correlate the resetting of the temperature set-points in individual zones to simplify the optimization problem while applying proper optimization in individual zones. Second, a multi-objective optimization scheme optimizes the fresh air ratio of the supply air and the temperature set-point in the critical zone by formulating the multi-objective optimization problem. Third, a multi-agent distributed optimization scheme is developed to solve the optimization problem in a distributed manner, facilitating the deployment of local control devices of limited capacity. A TRNSYS-MATLAB co-simulation testbed is constructed to test and validate the proposed strategy. Test results show that the strategy is effective in properly balancing thermal comfort, IAQ and energy use while largely reducing programming challenges. The distributed optimization method can provide almost the same optimal outputs as conventional centralized optimization methods. [ABSTRACT FROM AUTHOR]

• A multi-agent based approach is proposed for optimal control of ventilation systems. • A complex optimization problem is decomposed into simple optimization problems. • Optimization problems can be solved in field control devices in distributed manner. • It is effective in finding the optimal solutions to compromise IAQ & energy use. • It allows control systems having good reconfigurability, scalability and robustness. A trade-off problem exists in ventilation systems to ensure acceptable indoor air quality (IAQ) with minimized energy use. It is often solved by the centralized optimization approach today. However, the dynamic operation conditions of ventilation systems and the changing expectations of users make the centralized optimal control not flexible and effective in responding to those dynamics and changes. Meanwhile, the distributed installation layouts of sensing and control networks provide appropriate application platforms for distributed optimal control. This paper therefore proposes a multi-agent based distributed approach for optimal control of multi-zone ventilation systems considering IAQ and energy use by optimizing ventilation air volumes of individual rooms and primary air-handling unit (PAU). This distributed approach decomposes the complex optimization problem into a number of simple optimization problems. Distributed agents, corresponding to individual rooms and the PAU, are assigned to handle these decomposed problems. A central coordinating agent coordinates these agents to find the optimal solutions. Two control test cases under different outdoor weather conditions are conducted on a TRNSYS-MATLAB co-simulation testbed to validate the proposed multi-agent based distributed approach for optimal control by comparing with a baseline control approach and a centralized optimal control approach. Results of the distributed approach can provide almost the same outputs as the expected optimum given by the centralized optimal control approach. The experiences of implementing the proposed distributed approach show its effectiveness in solving complex optimization problems and optimizing multi-zone ventilation systems as well as good scalability and reconfigurability. [ABSTRACT FROM AUTHOR]

• An agent-based distributed optimal control strategy for HVAC systems is developed. • A complex optimization task is decomposed into simple subtasks deployed locally. • Computation load is distributed over integrated IoT devices of limited capacity. • A convergence acceleration method is developed to achieve optimization in real-time. • It facilitates convenient plug-in of models of individual components in optimization. Existing studies on distributed optimal control of HVAC systems rarely consider the needs and constraints for practical applications and the deployment of control strategies on the physical building automation platforms. This paper proposes an agent-based distributed real-time control strategy for building HVAC systems with the objective to be deployed in the local control devices with limited programming and computation capacities, i.e. smart sensors integrated in future IoT-based field networks and local controllers in field networks of current LAN-based building automation systems. A complex optimization task with high computational complexity (i.e., computation code and computation load) is decomposed into a number of simple tasks, which can be handled by coordinating agents among the integrated local control devices. The computation task of an optimization decision is further distributed into a number of steps, each performed at a sampling interval of controllers. The test results show that the computation loads of all individual agents at each step were below 2000 FLOPs, which can be handled by the typical smart sensors using simple optimization codes and the number of iterations for each optimization decision was within 50, well below the convergence rate needed for optimal control with typical time interval of minutes. The proposed agent-based optimal control strategy is also convenient and effective to deal with multiple components of different performances and the optimization considering such performance deviations could reduce the overall energy consumption significantly. [ABSTRACT FROM AUTHOR]

High-tech industrial buildings, such as semiconductor cleanrooms, generally require strict temperature, humidity, and cleanliness controls, resulting in very high energy consumption of their air-conditioning systems. However, there exist two important problems in these air-conditioning systems, i.e., large cold-heat offset and low cooling efficiency. These two serious issues are generally neglected during the design stage and further cause great energy waste during the operation stage. This study therefore proposes a generic air-conditioning system design optimization framework for semiconductor cleanrooms by integrating heat recovery and free cooling techniques at air-side and water-side, respectively. The proposed design framework can fully eliminate cold-heat offset, simultaneously reduce cooling/heating loads and enhance cooling efficiency under full-range semiconductor applications. By detailed modeling and simulations, the proposed design framework is validated and tested under various indoor cooling loads, ventilation rates, and surrounding weather and climate conditions. Results show that 2.3–33.1 % energy savings are achieved and up to 15.8GJ/m2 annual primary energy is saved, compared with the conventional design. It is also observed that cities in cold and mild climates have higher energy-saving potentials than those in hot climates. It is recommended to utilize the proposed design framework as a benchmarking air-conditioning system design in new semiconductor cleanrooms. • A generic design optimization framework is proposed for semiconductor cleanrooms. • Design framework effectively integrates heat recovery and free cooling technologies. • Integrated system design applies to full-range weathers, loads and ventilation rates. • Annual 1.2–15.8 GJ/m2 primary energy, accounting for 2.3–33.1 % savings, is achieved. • Cleanrooms in cold & mild climates achieve higher energy savings than hot climates. [ABSTRACT FROM AUTHOR]

Highlights: [•] A review on the development and modeling of active hollow core slab is presented. [•] The applications and performance evaluation of the slab in building are reviewed. [•] Finite element or finite difference method is often used in multidimensional model. [•] Performance evaluations of building using active slabs for ventilation are limited. [•] More works on the active hollow core slab are worthwhile. [ABSTRACT FROM AUTHOR]

Since a traditional centralized control system (e.g., building energy management system) with a fixed schedule and manual control is not appropriate to irregularly occupied rooms, it is expected to have a large amount of energy saving potential in operating the HVAC system. To overcome this challenge, this study aimed to develop a novel operation approach for the energy efficiency improvement of the HVAC system in office spaces. The real-time indoor environmental indicators were collected and analyzed to evaluate the current operation status of the HVAC system as well as to propose a novel control strategy in two ways. The significant findings can be illustrated as follows. First, it could be stated that occupants would tend to establish a lower set-point temperature for a cooler indoor environment. To solve this issue, a basic control strategy was proposed to detect the anomaly detection of the HVAC system and to automatically adjust the indoor temperature within a preferred range. Second, it could be evaluated that the HVAC system would be kept operating since occupants would forget to turn off the HVAC system after the meetings. To solve this issue, an advanced control strategy was proposed to operate the automatic on/off control of the HVAC system by considering the indoor temperature and CO 2 concentration in real time. The proposed strategies can contribute to a large amount of energy savings in operating the HVAC system of irregularly occupied spaces. • The proposed strategy can achieve the energy savings in operating the HVAC system. • A novel operation strategy is developed through real-time big data analytics. • The real-time indoor temperature and CO2 concentration is considered as a proxy. • Basic approach is aiming for the automatic adjustment of the set-point temperature. • Advanced approach is aiming for the automatic on/off control of the HVAC system. [ABSTRACT FROM AUTHOR]