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The electricity required for air conditioning is soaring worldwide. Absorption chillers represent an alternative to classical vapor compression systems, using heat instead of electricity. However, absorption chillers powered by renewable geothermal heat have received little attention so far. This paper introduces a system using a hot geothermal fluid (typically in the range of 80–110 °C) to produce cooling through a single-effect absorption chiller, and Domestic Hot Water (DHW) through a heat exchanger. It considers a hotel located in Martinique, a French Caribbean island. The electric consumption of every subsystem has been thoroughly estimated. The originality of this paper is twice: i) the system is modelled in TRNSYS software considering dynamic conditions, ii) the system undergoes surrogate modelling and multi-objective optimization to minimize both the cost and the CO 2 content of the delivered thermal energy. Several scenarios are considered, depending upon the geothermal temperature, mass flow rate, well remoteness, and demand size. The studied system appears to be systematically more expensive than a combination of a classical vapor compression chiller and a boiler for DHW. However, it can significantly decrease the CO 2 content of the provided energy, especially in an island where most electricity is generated from fossil fuels. The proximity of the geothermal well and the use of the warm water leaving the absorption generator (here for DHW production) appear to be key factors for system relevance, along with a hotter geothermal fluid (e.g., 110 °C instead of 80 °C). • A geothermal absorption chiller in tropical climate is modelled. • The influence of design parameters on electricity consumption is investigated. • The system undergoes multi-objective optimization. • The well proximity and geothermal temperature are keys to the system relevance. [ABSTRACT FROM AUTHOR]

Most methods for creating an indoor thermal environment are based on controlling heating, ventilation, and air conditioning (HVAC) systems and do not consider the various needs of individuals in a multiperson space. Personal comfort systems (PCS) and personal comfort models (PCM) are popular technologies for achieving personal thermal comfort. This paper presents a thermal environmental collaborative control system (TECCS) that regulates environments at different spatial scales by leveraging the advantages of the HVAC system, PCS, PCM, and PCM-based automatic control to address the issue of individual differences in thermal demand in multiperson environments. The TECCS predicts thermal sensation votes (TSV) by combining facial skin temperature data obtained by an infrared sensor with environmental parameters. Subsequently, it performs the corresponding PCS control and adjusts the air conditioner according to the operating state of the PCS. This study proposes a collaborative control strategy with PCS at the core, enabling communication between thermal state recognition, HVAC system, and PCS. Twenty-eight adult males participated in the experiments testing the TECCS's performance. The results indicate that the TECCS can automatically regulate environments at different spatial scales based on thermal sensation prediction and that the operating state of the PCS can effectively guide air conditioning operations. Compared with constant setpoint control, the TECCS offers the advantage of improving thermal comfort. This paper also proposes future optimization directions based on the research results, focusing on recognition, equipment, and control. [Display omitted] • Skin-temperature-based comfort model and device collaborative control strategy. • Match occupant needs with environmental heat and cold supply. • Personal comfort system plays the role of both feedback and effector. • Realize the information interaction between occupants, PCS, and HVAC. • Prove the comfort improvement effect of the proposed system by subject experiments. [ABSTRACT FROM AUTHOR]

Air-cooled chillers are extensively employed to meet cooling demand in commercial and tertiary sectors. To enhance their performance during part-load operation, variable-speed drives have been integrated into compressors and condenser fans. In existing systems, condenser fans are either operated at a fixed speed or modulated to maintain a predetermined condensing pressure or temperature difference between the refrigerant and outdoor air. In the search for increased efficiency, it is worth investigating innovative control strategies aimed at minimizing energy consumption. A preliminary mapping of chiller performance at different fan speeds, loads, and operating conditions is required to achieve this goal. In this respect, this paper investigates the operation of air-cooled chillers equipped with variable-speed condenser fans, both in the case of constant- and variable-speed compressors. An ad hoc matrix test is adopted to cover appropriate ranges conditions, in terms of load and outdoor air temperatures. Performance maps are developed for a 50-kW c chiller using a 1-D simulator. As the main findings, it may be stated that (i) in the case of the variable-speed chiller, the energy efficiency ratio increases almost linearly with fan speed, resulting in an 8.8% increase when increasing the speed from the nominal to the maximum; (ii) in the case of constant-speed chillers, the system exhibits a different behavior with the cooling capacity and the energy efficiency ratio increasing with the fan speed between 380 and 980 rpm and then decreasing (slightly or sharply, at full and part load respectively) with fan speed between 980 and 1280 rpm, and a percentage increase of EER in the range 7.8–45% is observed. Also, the sensitivity of such results to the system design is investigated, analyzing a chiller equipped with a larger condenser that resulted in achieving minimum energy consumption at an optimal 980 rpm fan speed. Finally, for a constant-speed chiller serving an office building in the Mediterranean, the proposed fan control strategy could yield an electricity saving of up to 12.1% compared to the base case, confirming the potential for energy savings through optimized and system-tailored management of condenser fan speed. • The effect of variable-speed fans on the performance of air-cooled chillers is investigated. • Maps are developed for chillers with both variable-speed and constant-speed compressors. • Fan speed significantly influences the cooling capacity of constant-speed chillers. • In variable-speed chillers, it is advisable to always run the condenser fan at high speed. • The enhanced fan strategy enables 12.1% energy savings for a chiller in an office building. [ABSTRACT FROM AUTHOR]

With the significant trend towards variable frequency in heating ventilating and air-conditioner (HVAC) loads, the inverter-based air conditioner load (IACL) clusters are poised to become the mainstay in participating in demand response (DR). During the process of DR, once the indoor temperature exceeds the comfort constraint, HVAC load must be forced to exit DR, which brings correlation to the behaviour of the preceding and following periods, making cluster optimization modelling and solution difficult. In order to solve the problems, this paper proposes an analogue ON/OFF state-switching (AOSS) control method suitable for IACL cluster participating in DR. Firstly, the critical working point corresponding to the comfort constraint is analysed for eliminating the temporal coupling for IACL. Then, an AOSS control method is proposed based on the critical point analysis. The feasibility of the proposed AOSS control is validated by the experimental results, with the Hisense KFR-75W/T08SBp-A2 inverter-based air conditioning DR experimental platform. Furthermore, by using the proposed AOSS control, a day-ahead scheduling model is constructed, and, the traditional state-queuing (SQ) model is transplanted to the IACL cluster for short-term power control. And the case studies verified the effectiveness and applicability of the day-ahead scheduling model and the transplanted SQ model. • Analysing the critical working point corresponding to the comfort constraint. • AOSS control is proposed to eliminate the temporal coupling for IACL. • Aggregation and optimal dispatching for IACL cluster in day-ahead time scale. • Ultra-short time scale IACL cluster power control. [ABSTRACT FROM AUTHOR]

A large part of French electricity consumption variation is due to temperature fluctuations. While HVAC (heating, ventilation and air-conditioning) systems consumption are directly affected by the temperature, other systems (refrigerator, freezer, water heater) can also be driven by weather changes making thermal contribution to overall consumption difficult to extract. This paper presents a "by-design" unsupervised data-driven method to separate the consumptions due to the weather in the overall electricity consumption. The proposed deep-learning model is based on the separation of meteorological parameters from calendar ones within the model architecture. The performances of this model, in particular its ability to split consumption mechanisms, is tested on a synthetic dataset and on the french consumption dataset. Being relatively simple and interpretable, this approach can be generalized to other countries whereasenergy sobriety represents an important challenge we are facing. • The hourly power load of a country due to temperature is unsupervisingly identified. • Deep learning model provides Large Scale Non Intrusive Load Separation. • Engineering-driven neural network design separates weather and calendar consumption. • Model's performance is assessed on country's actual electricity consumption. [ABSTRACT FROM AUTHOR]

Highlights • EnergyPlus is capable of accurately estimating the heat transfer in parked vehicles. • Spectrally selective glazing can cause an average temperature difference inside the cabin as high as 12.5 °C. • Solar-reflective opaque coating in combination with ChLC glazing can reduce the cabin air temperature up to 23.8 °C. Abstract Parked vehicles have the tendency to overheat quickly. This can lead to a negative impact on the thermal comfort of the driver and its passengers, as well as intensive use of air conditioning systems, and thus fuel consumption of the vehicle or, in the case of electric mobility, a reduced cruising range. In the search for effective measures to mitigate this effect, important guidance can be provided by the field of sustainable building design. On the one hand, inspiration can come from design strategies in terms of shapes and advanced cover materials, but this paper advocates that this can also pertain to the simulation-based design support tools that are used by building engineers. This paper first presents the results of a thermal soak test, and then uses this data to demonstrate the suitability of the building performance simulation tool EnergyPlus for predicting the thermal behavior of parked vehicles. This fit-for-purpose validated model is used to evaluate the performance of three overheating mitigation measures for two car models in two climates. The results show that spectrally selective glazing can reduce the cabin air temperature by 12.5 °C and when combined with solar reflective opaque surfaces, the reduction of cabin air temperature can reach 23.8 °C. Increased use of building performance simulation in the automotive domain can help to further optimize the overheating reduction potential of cars. [ABSTRACT FROM AUTHOR]

Highlights • One-stop archive for developments in solid desiccant coated heat exchangers (DCHEs). • Comprehensive study on the selection of desiccants and binders. • Thorough analysis on the effect of operating parameters on dynamic performance. • Detailed review of advances in mathematical modeling of DCHEs. • Discussion on the potential system-level applications of DCHEs. Abstract Rapid urbanization and higher thermal comfort requirements have sharply increased buildings' energy demands. In tropical countries, for achieving energy efficient air-conditioning, desiccant dehumidifiers, which decouple sensible and latent load, are essential. While fixed-bed and rotary wheel desiccant dehumidifiers suffer from reduced adsorption capacity and lowered heat transfer efficiencies, desiccant coated heat exchanger (DCHE) system is a promising technology that can improve the energy efficiency of the standard vapor-compression air conditioners. Moreover, DCHEs also have prospective benefits in heat pump, adsorption chiller, and atmospheric water harvesting applications. In this paper, the advantages of DCHEs over other dehumidifiers are established, and a comprehensive review of various desiccant materials and binders used in DCHEs is carried out. The possibilities of using advanced materials to achieve superior energy efficiencies are also underlined. Different methods of coating the desiccant on heat exchangers are described, and quantitative parameters required to analyze the performance of the system are presented. Operating parameters affecting the dehumidification and thermal performance are identified, and the effect of their variation on the dynamic behavior of DCHEs is elaborately studied. The significance of using mathematical models as design tools is recognized, and the underlying assumptions, applicability, and limitations of the models for simulating the complex heat and mass transfer phenomenon are highlighted. The possibility of integrating an additional heat transfer equipment such as sensible heat exchangers, heat recovery devices, solar evacuated tube collectors, cooling towers, and evaporative coolers with DCHE is also presented. Finally, the potential system-level applications of DCHEs as heat pumps, adsorption chillers, water harvesters, and standalone air-conditioners are assessed. This review paper provides an update on recent developments in desiccant dehumidification and is intended to be a "one-stop" archive of known practical solutions that DCHEs can offer. [ABSTRACT FROM AUTHOR]

The rising demands for comfort alongside energy conservation underscore the importance of intelligent air conditioning control systems. Model Predictive Control (MPC) stands out as an advanced control strategy capable of addressing these demands. However, accurate prediction of all relevant variables remains a challenge in practical scenarios, complicating MPC's ability to devise effective control actions amid prediction inaccuracies. To counteract this issue, this paper introduces an enhanced Double-Layer Model Predictive Control (DLMPC) algorithm. This innovative approach adjusts for discrepancies between forecasted and actual values without the need for additional variables and models, thereby reducing the adverse effects of prediction errors. Additionally, we develop precise models for room temperature simulation and for calculating air conditioning (AC) load and energy consumption, grounded in empirical data from residential settings and AC performance tests. Validation of these models demonstrates their efficacy in enabling MPC to formulate efficacious control strategies. When juxtaposed with a baseline model, the DLMPC algorithm significantly improves temperature regulation accuracy by up to 15.12% and achieves a 10.50% reduction in energy consumption over the heating season. • Proposed a novel double-layer Model Predictive Control (DLMPC) algorithm that adjusts for prediction inaccuracies. • Developed high-accuracy RC models for room temperature simulation based on actual residential data. • Developed high-accuracy models for air-conditioning (AC) load and energy consumption based on actual AC experiment test. • Validated the effectiveness of the DLMPC algorithm and associated models in improving intelligent air conditioning control in residential buildings. • The proposed model demonstrates good control effectiveness under high prediction errors. [ABSTRACT FROM AUTHOR]

The advance of air-conditioning systems has become a popular topic, due to its huge energy consumption and the increasing demand of improving indoor air quality. Although various approaches have been proposed for humidity, temperature and CO 2 control, their coordination has not yet been studied. In this study, the technologies of desiccant dehumidification, indirect evaporative cooling and direct CO 2 capture are innovatively integrated in an air-conditioning system, by which their respective advantages can be exerted and limitations can be compensated. Under a base working condition with ambient temperature of 35 °C and relative humidity of 80%, the overall coefficient of performance of the integrated system reaches 0.93, with an improvement of 53.3% against a conventional scheme. The integrated system is more efficient at higher crowdedness. With occupant number from 2 to 22 in a room, the advantage of the integrated system ranges from 50.7% to 85.6%. Parametric studies on different indoor and outdoor conditions are conducted, indicating that the energy efficiency advantage is more outstanding at higher indoor temperature, lower ambient temperature and lower ambient humidity. The factors of economic, environment and health are discussed, where the integrated system exhibits superiority against conventional systems and existing studies as well. Approaches are raised to improve the performance and promote future studies. The results in this paper contribute to providing a scheme for the integration of different technologies and enlightening insights for the advance of air-conditioning systems for the sake of air quality improvement, energy saving and emission reduction. • An integrated air-conditioning system is proposed for improving energy efficiency. • Different technologies for temperature, humidity and CO 2 control are coordinated. • 53.3% improvement on energy efficiency is obtained for base working condition. • Parametric analyses indicate advantage for the integrated system at most cases. • Economic and environmental issues are discussed compared with existing studies. [ABSTRACT FROM AUTHOR]

In an effort to minimise electricity consumption and greenhouse gases emissions, the heating, ventilation and air-conditioning sector has focused its attention on developing alternative solutions to electrically-driven vapour-compression cooling. Liquid desiccant air-conditioning systems represent an energy-efficient and more environmentally friendly alternative technology for dehumidification and cooling, particularly in those cases with high latent loads to maintain indoor air quality and comfort conditions. This technology is considered particularly efficient in hot and humid climates. As a matter of fact, the choice of the desiccant solution influences the overall performance of the system. The current paper reviews the working principle of liquid desiccant systems, focusing on the thermodynamic properties of the desiccant solutions and describes an evaluation of the reference thermodynamic properties of different desiccant solutions to identify which thermodynamic, physical, transport property influences the liquid desiccant process and to what extent. The comparison of these thermodynamic properties for the commonly used desiccants is conducted to estimate which fluid could perform most favourably in the system. The economic factors and the effect of different applications and climatic conditions on the system performance are also described. The paper is intended to be the first step in the evaluation of alternative desiccant fluids able to overcome the problems related to the use of the common desiccant solutions, such as crystallization and corrosion to metals. Ionic liquids seem a promising alternative working fluid in liquid desiccant air-conditioning systems and their characteristics and cost are discussed. [ABSTRACT FROM AUTHOR]

This paper presents an algorithm for optimal management of aggregated power demand of a group of heating, ventilating and air-conditioning (HVAC) units. The algorithm provides an advanced direct load control mechanism for HVACs that leverages the availability of smart thermostats, which are remotely programmable and controllable. The paper provides a theoretical basis and an optimal solution to the problem of cycling a large number of HVAC units while respecting customer-chosen temperature limits for the purpose of maximum load reduction. The problem is presented in a new light by transforming it into a job scheduling problem and is solved using a combination of a novel greedy algorithm and a binary search algorithm. By leveraging widespread availability of smart internet-based (also referred to as IoT-based) thermostats in today’s environment, the proposed approach can be readily applied to residential buildings without additional electrical/IT infrastructure changes. [ABSTRACT FROM AUTHOR]

Heating, ventilation, and air-conditioning (HVAC) are among the major energy demand in the buildings sector globally. Improving the energy efficiency of such systems is a critical objective for mitigating greenhouse gas emissions and transitioning towards renewable sources of energy supply. The interest of this paper is to explore means to increase the efficiency of HVAC systems in accommodating occupants’ behavior in real time. For instance, rooms in office buildings are not always occupied by occupants during scheduled HVAC service periods. This offers an opportunity to reduce unnecessary energy demands of HVAC systems associated with occupants’ behavior. An in-depth analysis of occupants’ stochastic behavior within an office building is conducted in this paper. A demand-driven control strategy is proposed that automatically responds to occupants’ energy-related behavior for reducing energy consumption and maintains room temperature for occupants with similar performances as a static cooling. In this control strategy, two types of machine learning methods – unsupervised and supervised learning – are applied to learn occupants’ behavior in two learning processes. The occupancy-related information learned by the algorithms is used by a set of specified rules to infer real-time room setpoints for controlling the office's space cooling system. This learning-based approach intends to reduce the need for human intervention in the cooling system’s control. The proposed strategy was applied to control the cooling system of the office building under real-world conditions. Eleven case study office spaces were selected, representing three typical office uses: single person offices, multi-person offices, and meeting rooms. The experimental results report between 7% and 52% energy savings as compared to the conventionally-scheduled cooling systems. [ABSTRACT FROM AUTHOR]

This paper proposes an aggregated flexibility estimation method considering the distributed electricity-hydrogen (H 2) interactions for virtual power plants (VPPs) to enhance the economic benefits from the peak-regulation market (PRM) while facilitating the accommodation of renewable generation. Firstly, various distributed energy resources (DERs) such as electric vehicles (EVs), air conditioning systems (ACs), and electricity-H 2 coupled hydrogen refueling stations (HRSs) are modeled as virtual storage (VS) with characterized charging/discharging response parameters. Besides, the temporal coupling power profile of VS can be abstracted as a polytope from the geometric perspective, and the aggregated high-dimensional flexibility region of VPP is formulated by the Minkowski sum for these polytopes. Furthermore, a day-ahead peak-regulation optimal scheduling model considering the conditional value at risk (CVaR) is developed for the electricity-H 2 integrated VPP participating the PRM, and the dimensionality of the aggregated polytope is reduced by the inscribed hyperbox approximation to provide a compact and concise scheduling region. Comparative studies have validated the aggregated power range and net income can be improved by 13.05% and 15.11% with the mechanism of electricity and hydrogen integrations. • The aggregated flexibility of distributed electricity and H 2 resources is unlocked. • Different types of virtual storage models are designed for EVs, ACs, and HRSs. • An inscribed hyperbox based aggregated flexibility projection method is proposed. • A concise day-ahead peak-regulation optimal scheduling model is developed for VPPs. [ABSTRACT FROM AUTHOR]

This paper presents new metrics to measure the effect of thermal mass on the energy required to heat and cool buildings. Previous studies have been flawed as they have not considered the interaction between intermittent occupancy and thermal mass, which has a significant impact on overall energy use. However, existing parameters do not adequately capture these effects, so the new metrics developed in this paper are used to analyse the impact of thermal mass in hot climates with active cooling, and cold climates with active heating. The results agree with existing literature that high thermal mass structures are likely to be effective in hot climates; however, in cold climates the drawbacks of high thermal mass likely outweigh the advantages, and high thermal mass can cause an increase in energy use. This finding has implications for the design of buildings in cold climates, and contradicts the commonly-held assumption that high thermal mass is correlated with low energy use. The new metrics (transient energy ratio and effective U -value) provide a generalisable method to quantify these effects. They are further used here to analyse the dynamic performance of heavily insulated buildings and show that high thermal mass often leads to higher energy use in cold climates. [ABSTRACT FROM AUTHOR]

There has been an increasing concern on thermal comfort in sleeping environments and its associated energy use in the past few years. To improve the thermal environment and to reduce energy use of air conditioning in bedrooms, applications of task/ambient air conditioning (TAC) systems were proposed and studied previously. It’s indicated that the TAC system can be well integrated with a bed. Due to the variation of the envelope heat gain in a bedroom during night, it is necessary to study the thermal environment inside a bedroom and the energy use of a TAC system for the bedroom at varying envelope thermal loads. Therefore, this paper reports on a numerical study on a TAC system applied to a bedroom with different envelope heat gains. The influences of envelope heat gain on energy consumption of the TAC system and the indoor thermal comfort were studied in this paper. The research results show that at supply air flow rate ( Q s ) of 50 l/s, energy consumption was increased from 47.78 W to 213.11 W, and the PMV value was increased from −1.69 to −1.29 with the increase in envelope heat gain from 3.11 W to 155.6 W. To make PMV equal to zero under different envelope heat gains, linear regression models between supply air parameters and PMV were built and solved. The obtained values form curves where PMV = 0 and give a guide for operation of the TAC system. It was found that the calculation of energy consumption on these curves depends only on envelope heat gain. [ABSTRACT FROM AUTHOR]

This paper presents an energy-saving controller for automotive air-conditioning/refrigeration (A/C-R) systems. With their extensive application in homes, industry, and vehicles, A/C-R systems are consuming considerable amounts of energy. The proposed controller consists of two different time-scale layers. The outer or the slow time-scale layer called a set-point optimizer is used to find the set points related to energy efficiency by using the steady state model; whereas, the inner or the fast time-scale layer is used to track the obtained set points. In the inner loop, thanks to its robustness, a sliding mode controller (SMC) is utilized to track the set point of the cargo temperature. The currently used on/off controller is presented and employed as a basis for comparison to the proposed controller. More importantly, the real experimental results under several disturbed scenarios are analysed to demonstrate how the proposed controller can improve performance while reducing the energy consumption by 9% comparing with the on/off controller. The controller is suitable for any type of A/C-R system even though it is applied to an automotive A/C-R system in this paper. [ABSTRACT FROM AUTHOR]

In this paper, the cooling feasibility of air flow via a novel air-water based TEC system (as an alternative air cooling unit) is experimentally investigated for different climate conditions. Contrary to previous studies, thermoelectric hot side temperature was adjusted by a low constant water flow rate (and not by an air fan) which significantly increased the cold side performance of TEM. Ten parameters including T a,inlet , T w,inlet , T a,outlet , T w,outlet , T c , T a , m ̇ a , m ̇ w and DC voltage and DC current were directly recorded by measurement instruments during the experiments. Six other parameters including q c , q h , COP c , COP max , COP c /COP max and q air were evaluated by formulas and correlations using of aforesaid measured data. Five numbers of aforementioned parameters were variant parameters. Indeed, the effect of m ̇ a , m ̇ w , DC voltage/current and T a,inlet (variant parameters) on other impressionable parameters were investigated in present study. Optimum working condition was evaluated from a new point of view. Indeed, in this paper, it was accidently found out that, despite the descending behavior of both COP c and COP max (due to changing of variants), the ratio of said parameters (COP c /COP max ) creates a peak point (ascending and then descending) in all cases. Said peak point can be considered as an appropriate working condition of thermoelectric units. Findings showed that, the cold side of thermoelectric system can act as an applicable air cooling system especially when the hot side of thermoelectric is cooled by a current liquid such as water. [ABSTRACT FROM AUTHOR]

Modeling of the chiller performance is essential for the implementation of optimal energy-efficient control strategies in a heating, ventilation, and air conditioning (HVAC) system. Though classical data-driven chiller performance models are widely adopted in the industry, they generally suffer from poor out-of-sample generalization abilities, which refers to the model's capability to extrapolate for new data outside the range of the training dataset. In practice, however, the available chiller operation data for model development are often insufficient or collected from a few limited operating conditions, such that extrapolation is unavoidable after the model is applied for control purposes. To deal with this issue, this paper proposed a physics-guided neural network (PGNN) to model the energy performance of chillers. By adopting a new neural network architecture, modifying the loss function, and adding limited out-of-sample data, the PGNN incorporates domain knowledge into the data-driven model to achieve better out-of-sample generalization performance. Meanwhile, the convexity and monotonicity between the dependent and independent variables in the PGNN are properly addressed. The proposed PGNN is applied to model the chiller serving a high-rise building, and results show that PGNN performs much better in extrapolation than classical models and the multi-layer perceptron model. The research demonstrated the usefulness and effectiveness of the PGNN in modeling HVAC equipment. • A physics-guided neural network is developed to model chiller energy performance. • Physical constraints are added through new architecture and modified loss function. • Limited out-of-sample data are used as additional constraints for model training. • The out-of-sample generalizability of the proposed model is significantly enhanced. [ABSTRACT FROM AUTHOR]

• Energy saving is achieved by using liquid desiccant in air-conditioning systems. • Thermodynamic properties of different kinds of liquid desiccant are reviewed. • Safety issues of liquid desiccant are analyzed in different aspects. • Current situations and future concerns are concluded for different liquid desiccants. • Promising candidates of liquid desiccant for next generation are recommended. Liquid desiccant air-conditioning system (LDAS) becomes an attractive option for reducing the energy consumption of conventional air-conditioning systems. Despite lots of published papers on LDAS in various aspects, there is not yet a comprehensive and up-to-date review on the properties of liquid desiccants, while the selection of liquid desiccant plays essential role in the overall performance of LDAS. In this paper, a state-of-the-art review on the properties in regard of energy and environmental performance is delivered for present and potential liquid desiccants, including vapor–liquid equilibrium, specific heat capacity, safety concerns. The current situations and future concerns of liquid desiccant investigation can be obtained, while different kinds of liquid desiccant candidates can be compared and evaluated comprehensively. Existing liquid desiccant of halide salt faces severe drawback of corrosiveness in long-term use. Compared with existing liquid desiccants, the candidates of weak acid salt, ionic liquid and deep eutectic solvent behave low toxicity and friendly corrosiveness, whereas their weak moisture absorption ability, high cost or high viscosity is the bottleneck for further applications. Therefore, the mixture of them can be regarded as a promising candidate in LDAS applications, but the fundamental properties are urged to be measured. The work in this paper provides momentous reference and guidance for the exploration of new liquid desiccant as well as the evaluation of future prospect of LDAS. [ABSTRACT FROM AUTHOR]

• A data-driven model was developed to rapidly quantify the demand response potential of building HVAC systems. • Multiple factors affecting demand response potential were considered in the data-driven model. • A co-simulation platform based on EnergyPlus and Modelica was built for fully getting the demand response potential data. • Two commonly used DR strategies were evaluated using a series of indices. Buildings and heating, ventilation and air-conditioning systems are appropriate resources for demand response, but there is still a lack of rapid quantification methods to reveal buildings' dynamic demand response potential under different meteorological conditions and control strategies. In order to achieve real-time power grid dispatch and to facilitate grid-building interaction, this paper proposes a framework for establishing models to rapidly quantify the demand response potential of resources. First, a detailed co-simulation model of the building and its energy system is constructed, followed by extensive stochastic simulations of two commonly used demand response strategies, after which the demand response potential is quantified using a set of indices. Then, feature selection is performed on factors that may affect demand response potential, and a data-driven model for quantifying demand response potential is proposed, whose results are compared with those from the simulation model. Also, the demand response effects of the two control strategies are compared in this paper. A case study was carried out in an industrial building in Shenzhen, China. The results showed that under different boundaries, the coefficient of determination (R 2) of the quantification indices are all above 0.9, and that the data-driven model rapidly and accurately captured the demand response potential of the building and its heating, ventilation and air-conditioning system, and was easy to deploy in practice. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel approach to control CO 2 and H 2 O composition in an enclosed environment. • A cyclic CO 2 adsorption process and dehumidication units are considered. • The mathematical model shows superior performance of the proposed system. • Carbon footprint of the system is discussed with scale-up study. • Influence of parametric uncertainties in the model is discussed. Rapid growth in global energy consumption has raised concern on the environmental impacts such as ozone layer depletion and climate change. Enclosed space, such as commercial buildings, accounts for about 40% of global energy consumption and the demand is constantly increasing due to increasing population, urbanization, and economic development. The energy demands in the building sector calls for strategic measures to develop energy efficient technologies. This paper presents a strategy to decrease energy demands inside buildings by proposing a ventilation system which regulates the enclosed air quality resulting in reduced air conditioning. The system consists of multiple adsorption beds with zeolite 13X monoliths for CO 2 removal, and silica gel for humidity control, inside the enclosed space. The air conditioning system results in decrease in energy requirement and improvement in economics by 55% as compared with conventional ventilation system. The model is scaled up to the size comparable with total office inventory of New York City, and the reduction in carbon emissions by introducing the air composition control system for New York City is equivalent to replacing 57 million incandescent light bulbs by LEDs. This paper concludes that the air conditioning system proposed in this study results in the improvement in performance as compared to a conventional ventilation system and could reduce energy consumption inside commercial buildings. [ABSTRACT FROM AUTHOR]

Traditional air conditioning may be inappropriate for electric vehicles due to its moving parts noise besides using chlorofluorocarbons that harm the environment. In addition, it consumes a significant portion of the stored energy in batteries, reducing the vehicle's driving range. So, in this paper, a novel design of thermo-electric cooling (TEC) system coupled with a photovoltaic (PV) panel replacing the vehicle roof is studied. This system consists of a sandwich of PV panel outside the vehicle and TEC inside with a heat sink system integrated between them. The air temperature variation in the cabin during the daytime is predicted by solving a complete mathematical transient thermal model of the whole system before and after mounting the cooling system. The air streams through the vehicle moving are exploited to improve the TEC and PV system performance. The system performance is investigated for different cases during the day with and without including the PV output power and for the vehicle parks inside or outside. The results indicate that, for each scenario, the number of used TEC modules influences the system performance where the best number varies between 128 and 98. Coupling the PV panel with the TEC system reduces the daily required energy from batteries by about 19%. Running the TEC system during parking from 8 to 10 am decreases the cabin air temperature from 47.5 to 34°C while the input power declines by about 45%, which reduces the interior temperature to 25°C in 10 min (transition time). The contribution of the PV panel based on the studied conditions can increase the range of the vehicle by 10.4 km/day and about 160kWh/year energy saving. The reduction in the input power during transition time reaches 27.8% when the vehicle speed increases from 30 to 60 km/h, while this ratio declines to 10.8% as the vehicle speed rises from 60 to 90 km/h. During vehicle moving, powering the TEC system by the PV panel only can prevent the cabin temperature from rising over 40°C, whereas during parking, there is an optimum fan air velocity that gives the maximum reduction of the cabin temperature. • A novel design of a thermo-electric air conditioning system for electric vehicles is studied. • Contribution of the PV panel reaches 19% of the daily energy consumption in some scenarios. • PV panel increases the range of the vehicle by 10.4 km and can save 160kWh/year. • The best number of TEC modules is about 128 for scenarios 1 and 2 and 98 for the others • Power the TEC by PV power in parking reduces the vehicle temperature less than ambient. [ABSTRACT FROM AUTHOR]

This paper presents the evaluation of the performance of a ground source heat pump system monitored plant providing heating/cooling to an office building located in the Universitat Politècnica de València in Spain. The system was designed using GLHEPRO software and it has been monitored since 2005. Once a ground source heat pump has been designed, it is important to analyze its performance along the years after its construction and check whether the design was appropriate and the simulation predictions were consistent with real experimental measurements. This paper first presents the impact of the GSHP system in the ground thermal response. The simulations obtained in GLHEPRO software will be analyzed and compared to experimental measurements. The second purpose of this work is to compare the performance simulation results of a complete ground source heat pump system model built in TRNSYS, with the experimental measurements which have been registered and collected for one cooling day. Numerical predictions and experimental results are compared and discussed. [ABSTRACT FROM AUTHOR]

• This paper reviews strategies in commercial buildings for grid service delivery. • Review and technical papers are searched by Sub-keyword Synonym Searching Method. • Primary limitations, gaps, and future trends are identified. The modern power grid faces multiple challenges due to an increase in the adoption of renewable generation, such as dynamically balancing supply and demand at different time scales. Demand side management in buildings plays a vital role in achieving this balance because buildings can provide grid services through a variety of building assets. However, the development of grid-interactive, efficient buildings is still in its infancy, and a systematic and holistic understanding of grid service delivery strategies in terms of energy efficiency, load shifting, load shedding and load modulating is still limited. This paper is a comprehensive review of the development and application of building-level control strategies for utilizing heating, ventilating, and air conditioning systems to provide grid services. These strategies have been investigated through numerical and experimental studies. Control algorithms, such as heuristic rule-based control and model-based control, have been used to enable the automatic control delivery of grid services. The advantages and disadvantages of the strategies are summarized and discussed. Research trends are also identified, which include considering predicted mean vote-based and occupant-based thermal comfort, modeling of occupant behavior, integrating power grid operations with building control, and combining different demand flexibility modes in the control design. [ABSTRACT FROM AUTHOR]

Abstract: Air conditioning is essential for maintaining thermal comfort in indoor environments, particularly for hot and humid climates. Today, air conditioning, comprising cooling and dehumidification, has become a necessity in commercial and residential buildings and industrial processes. It accounts for a major share of the energy consumption of a building or facility. In tropical climates, the energy consumed by heating, ventilation and air-conditioning (HVAC) can exceed 50% of the total energy consumption of a building. This significant figure is primarily due to the heavy duty placed on cooling technologies to remove both sensible and latent heat loads. Therefore, there is tremendous potential to improve the overall efficiency of the air-conditioning systems in buildings. Based on today’s practical technology for cooling, the major components of a chiller plant are (1) compressors, (2) cooling towers, (3) pumps (chilled and cooling water) and (4) fans in air handling units. They all consume mainly electricity to operate. When specifying the kW/Rton of a plant, there are two levels of monitoring cooling efficiency: (1) at the efficiency of the chiller machines or the compressors which consume a major amount of electricity; and (2) at the overall efficiency of cooling plants which include the cooling towers, pumps for moving coolant (chilled and cooling water) to all air-handling units. Pragmatically, a holistic approach is necessary towards achieving a low energy input per cooling achieved such as 0.6kW/Rton cooling or lower by considering all aspects of the cooling plant. In this paper, we present a review of recent innovative cooling technology and strategies that could potentially lower the kW/Rton of cooling systems – from the existing mean of 0.9kW/Rton towards 0.6kW/Rton or lower. The paper, broadly divided into three key sections (see Fig. 2), begins with a review of the recent novel devices that enhances the energy efficiency of cooling systems at the component level. This is followed by a review of innovative cooling systems designs that reduces energy use for air conditioning. Lastly, the paper presents recent developments in intelligent air-control strategies and smart chiller sequencing methodologies that reduce the primary energy utilization for cooling. The energy efficient cooling technology, innovative systems designs, and intelligent control strategies described in the paper have been recently researched or are on-going studies. Several have been implemented on a larger scale and, therefore, are examples of practical solutions that can be readily applied to suit specific needs. [Copyright &y& Elsevier]

Abstract: The advantages of desiccant-based air conditioning systems, compared to conventional ones based on the dehumidification by cooling, have been highlighted in many research papers. The energy saving and the reduction of the environmental impact are higher when the desiccant material is regenerated by using “free” thermal energy (for example, waste heat from cogenerators or solar energy). Further investigation on the performance of the desiccant wheel is useful: therefore, in this paper, an experimental analysis on this component is presented, with particular attention to the variation of the performance as a function of the process and regeneration air flow rates. The desiccant material is regenerated by means of low-temperature thermal energy (about 65°C) from a microcogenerator. Both the experimental results obtained by the authors and the data provided by the manufacturer have been used to calculate some performance parameters, and a satisfactory agreement has been obtained. The performance parameters have been evaluated as a function of the regeneration temperature, the inlet process air humidity ratio and temperature and the ratio between the regeneration and process air flow rates, in both the cases of fixed regeneration temperature and fixed regeneration thermal power: the results show that higher influence on the dehumidification process is due to the regeneration temperature rather than to the regeneration air flow rate. Moreover, the process air humidity ratio and regeneration temperature influence the desiccant wheel performance more than the process air temperature. [Copyright &y& Elsevier]

Highlights • A recuperative heat pump using zeotrope with a large temperature glide is proposed. • Good application for water heater with a large temperature glide of 84 K is verified. • Operating conditions of air-conditioning and refrigeration (<2 MPa) is obtained. • N -hexane/propene and R4310mee/R32 is a superior alternative to CO 2 heat pump. • Off-the-shelf components of air-conditioning and refrigeration can be used. Abstract The heat sinks with a finite capacity and a large temperature glide bring about new challenges of efficient heat pump. This paper presents a modified subcritical zeotropic mixture recuperative high-temperature heat pump cycle for the above heat sinks by introducing a modified recuperation process of zeotropic mixtures with a large temperature glide in gas-liquid phase change region. Performance analysis and optimizations are performed by genetic algorithm in MATLAB connecting HYSYS considering COP as an objective function for hot water supply from 15 °C to 99 °C with an air source using five candidate binary zeotropic mixtures. The study presents the effects of pressures and mixture compositions on cycle COP and exergy utilization. The results show that the modified cycles using n -hexane/propene and R4310mee/R32 efficiently improve COP and exergy utilization by enabling a good temperature match of heat sink with refrigerant under the optimal conditions. Furthermore, compared with CO 2 transcritical cycle, CO 2 /R32, CO 2 /R143a and CO 2 /R41 result in about 8.88%, 6.55% and 4.95% increases of COP, while n -hexane/propene and R4310mee/R32 recuperative cycles bring about 4.35% and 3.28% increases of COP. Interestingly, the operating pressures of n -hexane/propene (1409.5 kPa/704.0 kPa) and R4310mee/R32 (1968.0 kPa/980 kPa) are far lower than those of pure CO 2 and CO 2 blends, which are consistent with those of conventional air-conditioning and refrigeration. A preliminary cost comparison result reveals the low-cost advantage of the modified zeotropic mixture recuperative cycle because off-the-shelf air-conditioning and refrigeration products can be used. It is concluded that n -hexane/propene and R4310mee/R32 subcritical recuperative heat pump cycles can be superior alternatives to CO 2 heat pump cycle. [ABSTRACT FROM AUTHOR]

Highlights • A lumped urban-building thermal coupling model is developed. • Lower urban temperatures in naturally-ventilated cities than air-conditioned ones. • Stronger urban cool island in a low-rise sparse city than a high-rise compact one. • Urban heat/cool island changes in a unique 'V' shape/'ʌ' shape under urbanization. Abstract Many cities are suffering the effects of urban heat islands (UHI) or urban cool islands (UCI) due to rapid urban expansion and numerous infrastructure developments. This paper presents a lumped urban-building thermal coupling model which captures the fundamental physical mechanism for thermal interactions between buildings and their urban environment. The benefits of the model are its simplicity and high computational efficiency for practical use in investigating the diurnal urban air temperature change and its asymmetry in a city with both naturally-ventilated (NV) and air-conditioned (AC) buildings. Our model predicts a lower urban heat island and higher urban cool island intensity in a city with naturally-ventilated buildings than for a city with air-conditioned buildings. During the urban densification (from a low-rise, low-density city to a high-rise, high-density one), the increases in the time constant and internal heat gain give rise to asymmetric warming phenomena, which become more obvious in a city with air-conditioned buildings rather than naturally-ventilated ones. Unlike previous studies, we found that a low-rise, low-density city experiences a stronger urban cool island effect than a high-rise, high-density city due to less heat being emitted into the urban atmosphere. The urban cool / heat island effect will firstly increase/decrease, and then rapidly decrease/increase and ultimately disappear/dominate with increasing time constant in the process of urbanization / urban densification. [ABSTRACT FROM AUTHOR]

Aiming to utilize the flexibility of smart buildings for flexible operation of active distribution network, a combined modeling and optimal scheduling method for the active distribution network with integrated smart buildings is proposed in this paper. Based on the heat storage characteristics of a building, the energy consumption prediction model of the building considering different heating zones with different orientations is developed using the Resistor-Capacitor thermal network model. Then, different optimal control methods of the heating, ventilation and air-conditioning system in the building are developed. The energy consumption management of the heating, ventilation and air-conditioning system is achieved by adjusting the room temperature within the suitable temperature comfort range. In order to further consider the impact of the integration of smart buildings on the economic and security operation of the active distribution network, the optimal scheduling method of the active distribution network with integrated smart buildings is developed considering the load factor of the aggregation of the smart buildings. Finally, the optimal scheduling results of the aggregation of the smart buildings under different heating, ventilation and air-conditioning control methods in the winter heating scenario are analyzed. In addition, based on the branch flow model, the optimal power flow model of active distribution network with on-load tap changer is constructed by piecewise linearization and second-order cone relaxation to achieve flexible and optimal operation of the active distribution network. Thus, the impacts of the optimal schedules of the aggregation of smart buildings on the economic and security operation of the active distribution network are further evaluated. Numerical studies demonstrate that the proposed optimal scheduling method can make full use of the demand response potential of the smart buildings and further contribute to the operating costs reduction of the smart buildings. Meanwhile, the optimization of the active distribution network with the load factor of the aggregation of buildings can reduce the power loss and increase the minimum voltage magnitude of the active distribution network utilizing the flexibility of the smart buildings. [ABSTRACT FROM AUTHOR]

Once a conventional On-Off controlled single evaporator direct expansion air conditioning (A/C) system is installed, it has to be operated at different seasonal cooling load situations, and hence would have a hard time in trying to maintain the desired indoor thermal environment at all times, unless complicated and costly supplementary measures to provide variable dehumidification capacity are provided. Therefore, a novel standalone enhanced dehumidification air conditioning (EDAC) system was proposed based on multi-evaporator air conditioning technology. There were two evaporators in the proposed EDAC system, and the mass flow rates of both refrigerant and air to both evaporators can be varied. This paper reports on an experimental study on the operational characteristics of a prototype experimental EDAC system with both evaporators operated. Using the prototype experimental EDAC system, extensive experimental work has been carried out. During the experiments, constant compressor and supply fan speeds were used, but the refrigerant and air mass flow rates to both evaporators were varied, at different inlet air states to the experimental EDAC system. The experimental results demonstrated that at a fixed inlet air state, varying refrigerant and air mass flow rates to both evaporators led to outputting varied total cooling capacity (TCC) and equipment sensible heat ratio (E SHR) from the experimental EDAC system. For example, at an inlet air state of 26 °C and 50% RH, TCC varied from 4.5 kW to 5.32 kW and E SHR from 0.63 to 0.7. Furthermore, TCC and E SHR were mutually constrained within an irregular area in a TCC - E SHR diagram. Different inlet air states would result in shifted position of, or varied shape of an irregular area. Therefore, the use of the proposed EDAC system could provide variable output sensible and latent cooling capacity to deal with variable indoor space thermal load, so that achieving better indoor humidity and thus thermal control is possible with the proposed EDAC system. [ABSTRACT FROM AUTHOR]

Abstract: A data-driven approach for modeling indoor-air-quality (IAQ) sensors used in heating, ventilation, and air conditioning (HVAC) systems is presented. The IAQ sensors considered in the paper measure three basic parameters, temperature, CO2, and relative humidity. Three models predicting values of IAQ parameters are built with various data mining algorithms. Four data mining algorithms have been tested on the HVAC data set collected at an office-type facility. The computational results produced by models built with different data mining algorithms are discussed. The neural network (NN) with multi-layer perceptron (MLP) algorithms produced the best results for all three IAQ sensors among all algorithms tested. The models built with data mining algorithms can serve as virtual IAQ sensors in buildings and be used for on-line monitoring and calibration of the IAQ sensors. The approach presented in this paper can be applied to HVAC systems in buildings beyond the type considered in this paper. [Copyright &y& Elsevier]

Abstract: A large number of ground-coupled heat pump (GCHP) systems have been used in residential and commercial buildings throughout the world due to the attractive advantages of high efficiency and environmental friendliness. This paper gives a detailed literature review of the research and developments of the vertical-borehole GCHP technology for applications in air-conditioning. A general introduction on the ground source heat pump system and its development is briefly presented first. Then, the most typical simulation models of the vertical ground heat exchangers currently available are summarized in detail including the heat transfer processes outside and inside the boreholes. The various design/simulation programs for vertical GCHP systems primarily based on the typical simulation models are also reviewed in this paper. Finally, the various hybrid GCHP systems for cooling or heating-dominated buildings are well described. It is found that the GCHP technology can be used both in cold and hot weather areas and the energy saving potential is significant. [Copyright &y& Elsevier]

Abstract: Thermally activated building systems (TABS) integrate the building structure as energy storage, and have proofed to be energy efficient and economic viable for the heating and cooling of buildings. Although TABS are increasingly used, in many cases control has remained an issue to be improved. In this paper, a method is outlined allowing for automated control of TABS in intermittent operation with pulse width modulation (PWM). This method represents one part of a TABS control solution with automatic switching between cooling and heating modes for variable comfort criteria which was published before. A first pulse width modulation control solution is derived based on a simple 1st order model of TABS. Then a second, even simpler solution is given that significantly reduces the tuning effort. Finally, the paper outlines a pulse width modulation control procedure and gives two application examples of the PWM control carried out in a laboratory test room. [Copyright &y& Elsevier]

Abstract: There is a lack of detailed experimental and simulation studies on air-cooled centrifugal chillers. This paper investigates how to optimize the control of condenser fans within the chillers to maximize their coefficients of performance (COPs). A thermodynamic model for the chillers was developed and used to analyse the steady-state COP under various load and ambient conditions. An algorithm is introduced to compute the number of staged condenser fans based on settings of the condensing pressure and outdoor temperature. The model was validated using the experimental data and performance data of an existing chiller running under various operating conditions. It is found that the best strategy for switching condenser fans is to vary their rotating speed by the use of a set point of the condensing temperature, which is adjusted in response to the chiller load and condenser air-inlet temperature. The results of this paper provide an important insight into how to increase the COPs of air-cooled chillers. [Copyright &y& Elsevier]

This paper presents a study on a mechanically ventilated Trombe wall that adds additional windows to the storage wall. The mechanically ventilated Trombe wall is located on the south side of the house with a central air conditioning and air circulation system. To reduce the heating load, during the heating period, the heat from the Trombe wall air channel is sent to the air conditioning room, from where it is then distributed and stored throughout the house by way of air circulation. Taking a house located in Miyazaki, Japan as an example, we conducted an actual survey to understand the situation of heat utilization of the Trombe wall and used numerical simulations to examine the effective method of heat utilization of the Trombe wall. Results showed that in all-day air conditioning, even when sending the air in the Trombe wall to the air-conditioned room, the temperature of the Trombe wall remained high. The heating load was reduced by sending the air from the Trombe wall to the central air-conditioned room and installing the large heat capacity material on the floor in the Trombe wall. [ABSTRACT FROM AUTHOR]

This paper presents an autonomous hierarchical control method for a direct expansion air conditioning system. The control objective is to maintain both thermal comfort and indoor air quality at required levels while reducing energy consumption and cost. This control method consists of two layers. The upper layer is an open loop controller that allows obtaining tradeoff steady states by optimizing the energy cost of the direct expansion air conditioning system and the value of predicted mean vote under the time-of-use price structure of electricity. On the other hand, the lower layer designs a model predictive controller, which is in charge of tracking the tradeoff steady states calculated by the upper layer. Control performance of the proposed control method is compared to a conventional control strategy. The results show that the proposed control strategy reduces the energy consumption and energy cost of the direct expansion air conditioning system by 31.38% and 33.85%, respectively, while maintaining both the thermal comfort and indoor air quality within acceptable ranges, which validate the proposed methodology in terms of both comfort and energy efficiency. [ABSTRACT FROM AUTHOR]

This paper presents a new algorithm for managing solar PV intermittency in green buildings using demand response management (DRM) technique. The proposed DRM algorithm utilizes the building air conditioning and mechanical ventilation (ACMV) system to dynamically compensate for the deficit of power generated by solar PV system from its rated capacity. For example, the developed solution will reduce the load demand of the ACMV system equal to the drop of solar generation by controlling the speed of the fan. This will ensure that the amount of power supplied by the grid to the building will remain the same (as before the drop of solar generation) and thus no impact on the grid stability. However, since ACMV system is directly linked to building occupant comfort/health, the proposed solution will also include energy storage management and priority-based load shedding programs to provide support when room temperature (air conditioning) or CO level (ventilation) is above regulatory limit. A thermal model for building temperature variation is developed to test and analyze the proposed algorithm to dynamically manage solar PV fluctuation. [ABSTRACT FROM AUTHOR]

A solid-desiccant system that utilizes low grade heat is potentially a viable add-on to conventional HVAC systems since it can help reduce power consumption significantly, for achieving indoor thermal comfort conditions. In contrast to desiccant wheels which carry out adiabatic dehumidification, isothermal dehumidification process that may be realized by a cross-flow heat exchanger is much more efficient. In this paper, a novel mathematical model is developed to simulate heat and mass exchange phenomena of a desiccant coated fin tube heat exchanger (DCFTHX). This model takes solid side mass transfer resistance as well as fin efficiency into consideration. The model is validated using experimental results in the literature. It is also compared against simplified models to establish its utility. A parametric study is then conducted to investigate the effects of geometrical parameters as well as mass flow rate of water and air velocity on dehumidification and adsorption heat removal performance of the DCFTHX as well as the performance of the augmented air-conditioning system under warm and humid ambient conditions. Under the range of parameters and conditions simulated, if low grade waste heat (50 °C hot water) is available for regeneration, integration of DCFTHX sub-system with a conventional air conditioning system can yield as high as 31% energy savings (even when the additional power consumed by pumps and blower fans is accounted for). [ABSTRACT FROM AUTHOR]

Sizing of air-conditioning water pump systems in buildings is a critical issue in design practice concerning the pump energy consumption in operation and risk of being undersized. As a result, significant energy is often wasted in operation due to oversizing to avoid the risk of being undersized. In current practice, throttling of commissioning valves are commonly adopted to push water flowrate (and pressure head) back to the design point no matter how much oversizing exists in a system. That partly mitigates the oversizing problem. This paper presents a novel approach consisting of probabilistic optimal design concerning uncertainties and on-site adaptive commissioning to further maximize energy savings of constant water flow pump systems. Minimized throttling is achieved by on-site adaptive commissioning, which reduces unnecessary pressure head and significant energy consumption. Pumps selected by the probabilistic optimal design can operate under both conventional design conditions and the projected possible off-design (oversized) conditions. The projection is based on the probability distribution of actual pressure head, which is estimated using Monte Carlo simulation by quantifying uncertainties in pressure loss calculation and system construction. Three case studies are conducted to test and validate this new design and commissioning approach. Results show that about 20% energy saving could be achieved, when the system is oversized by 20%, compared to conventional design and commissioning methods. The proposed approach also offers better energy performance in general compared to the designs all using variable speed pumps. [ABSTRACT FROM AUTHOR]

Sensors are critical components of heating, ventilation, and air-conditioning systems. Sensor faults can impact control regulations, resulting in an uncomfortable indoor environment and energy wastage. To detect and identify sensor faults quickly, this study proposes an enhanced principal component analysis (PCA) method using the Savitzky–Golay (SG) filter and density-based spatial clustering of applications with noise (DBSCAN) algorithm. First, the DBSCAN algorithm is used to automatically divide the dataset into sub-datasets with different working conditions to reduce the interference information and concentrate the information of each training set. Then, each sub-dataset is smoothed using the SG algorithm to reduce the effects of data fluctuations. The processed dataset is used to build a sub-PCA model that ultimately identifies and locates faults. The proposed strategy is validated using field operating data for 20 air-handling unit (AHU) systems, as obtained from a large commercial building. The fault detection performances of multiple strategies are compared and analysed under different degrees of bias in single AHU and multiple AHU systems. The verification results show that the proposed DBSCAN-SG-PCA model offers significant improvements in fault detection accuracy and fault identification sensitivity over the conventional PCA method. Compared with the SG-PCA model, the proposed model reduces the amount of data required for fault detection by an average of 13.7%, and the Youden index is increased by an average of 0.21. Furthermore, the fault detection accuracy of the proposed model is ±0.7 °C. • This paper proposes a high-precision sensor fault detection and diagnosis method. • DBSCAN can recognize the different operating conditions of the air handling unit (AHU) successfully. • Field operating data from 20 real AHU systems were used for model validation. • The sensor's fault detection accuracy and sensitivity are significantly improved using the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we study multi-zone air environment comfort and building energy conversation for the heating, ventilation, and air conditioning (HVAC) system. Each zone is equipped with the air-handling unit (AHU) and fan coil unit to regulate the supply air state for comfortable zone climate. It is known that the multi-zone air environment appears spatial and temporal variation due to the hygro-thermal interaction which is an extremely complex nonlinear dynamic process. In this study, hybrid models incorporating the first-principles model with full form dynamic linearization (FFDL)-based data-driven model have been proposed to precisely describe the multi-zone climate dynamics including unknown nonlinearity and uncertainty. Then model-free adaptive control (MFAC) scheme is designed for multi-zone climate control, which contains controller design, parameter estimation and reset mechanism to ensure system control performance. Finally, different case studies are conducted to test the performance of model prediction and system control for the multi-zone climate environment. Model validation shows that the zone climate prediction of the proposed hybrid model shows better agreement with actual measured data. The step response results display that the hybrid model-based MFAC can realize multi-zone climate control performance improvement in faster convergence without stable bias. By comparing with prior work, the hybrid model-based MFAC has the potential to get closer to actual situation in cost-effective multi-zone climate control. • The first principles and data-based hybrid model is built for multi-zone climate. • Full form dynamic linearization is used for unknown hygro-thermal dynamics. • An adaptive controller is designed for higher temperature and humidity accuracy. • The average energy saving can reach up to 4% by the hybrid model-based MFAC scheme. [ABSTRACT FROM AUTHOR]

Generally, conventional controllers for comfort are designed by using on/off control or proportional-integral (PI) control, with little consideration of energy consumption of the system. This paper presents a multi-input-multi-output (MIMO) model predictive control (MPC) for a direct expansion (DX) air conditioning (A/C) system to improve both indoor thermal comfort and air quality, whereas the energy consumption is minimised. The DX A/C system is modelled into a nonlinear system, with a varying speed of compressor and varying speed of supply fan and volume flow rate of supply air being regarded as inputs. We first propose an open loop controller based on an optimisation of energy consumption with the advantage of a unique set of steady states. The MPC controller is proposed to optimise the transient processes reaching the steady state. To facilitate the MPC design, the nonlinear model is linearised around its steady state. MPC is designed for the linearised model. The advantages of the proposed energy-optimised open loop controller and the closed-loop regulation of the MIMO MPC scheme are verified by simulation results. [ABSTRACT FROM AUTHOR]

The dual source multi-functional heat pump (DMHP) system, which can adopt air source and solar energy to provide air conditioning and domestic water for building all the year round, is the integration of solar thermal collecting system and multi-functional heat pump system. This paper presents an investigation into the operation characteristics of the novel DMHP system under various working modes by theoretical and experimental methods. For each working mode, a dynamic model has been proposed and validated with the experimental data. With the verified model, the switch point between air source and solar energy can be identified by comparing the operation performance of different working modes under a range of boundary conditions. The results indicate that the performance of air source space heating mode is superior to that of solar space heating mode with the ambient temperature above 4 °C, and solar water heating mode is more efficient than air source water heating mode when the ambient temperature is below 3 °C. On this basis, annual performance of the system under different climate conditions reveals that the DMHP system can obtain relatively high COP with the optimal working strategy in the whole year especially for the district with cold winter. Furthermore, the exergy loss ratio in each component of the DMHP system has been discussed to provide the reference for further optimization. In general, the DMHP could be a promising building energy supply system with the advantage of high equipment utilization, compact structure, and full-featured, and this research would promote the development of such an innovative technology leading to significant energy saving and carbon emission reduction in building sector. [ABSTRACT FROM AUTHOR]

This paper proposes a gravity heat pipe exchanger used for cooling the communication base station to replace the traditional air conditioning system during winter and transition seasons. Tests were conducted on a commercial available gravity heat pipe exchanger. The experiment was performed to study the effects of the air flow rate and temperature on the cooling capacity, the heat transfer unit number (NTU) and cooling efficiency of the heat pipe exchanger. The results showed that the larger the air flow rate, the smaller the NTU and the larger the cooling capacity. Based on the analysis of the experimental data, it proved that the gravity heat pipe exchanger could reduce running time and operating cost of air conditioning system. According to the practical applications, the yearly cooling loads of a typical communication base station were further calculated for five typical cities which represent the five climatic zones of China. The results validated that the energy saving by using the gravity heat pipe exchanger is significant. The highest annual electricity-saving rate is achieved by Kunming, about 48.6%, while the lowest annual electricity-saving rate is obtained in Guangzhou, about 18.7% among the five climatic zones. The fitted correlation of cooling capacity in term of outdoor temperature is generic to evaluate approximately the performance of applying the gravity heat pipe exchanger in the actual applications subject to various outdoor temperatures. [ABSTRACT FROM AUTHOR]

In a central heating, ventilation, and air conditioning (HVAC) system, the set-points for several local control loops have a significant influence on the overall energy performance of the system. Real-time optimization (RtOpt) of those set-points has therefore been widely studied. However, due to the nonlinear dynamics of the HVAC system as well as the constraints associated with the system operation, real-time optimization always suffers from a heavy on-line computational load when those set-points are optimized simultaneously. To overcome this problem, multiplexed real-time optimization (MRtOpt) has been developed, which optimizes only one set-point at a time but with a faster optimization frequency. Because frequently resetting the set-points introduces artificial disturbances into the local control loops and may deteriorate the system stability, this paper presents a study to enhance the system stability of the multiplexed real-time optimization by integrating a degree of freedom (DOF) based set-point reset to renew the set-points instead of the conventional step-change set-point reset. The control performance of the integrated strategy was investigated using case studies. The results showed that around 10% of the energy saving was achieved by the proposed method compared with a method without real-time optimization. When compared with the conventional real-time optimization method, the proposed method resulted in around 70% computational load reduction, and over 26% reduction in the tracking errors of the local control loops. [ABSTRACT FROM AUTHOR]

It is well known that application of solar powered absorption refrigeration (SPAR) systems will save energy, especially for air conditioning during the summer. This paper presents a SPAR system where evacuated tubes act as both solar collector and solution generator simultaneously while aqueous lithium bromide (H 2 O/LiBr) is used as the working fluid. In order to investigate the heat absorbing and vapor generating characteristics of lithium bromide solution in the evacuated tube, a test system was built and tested outdoors in Guangzhou in October 2015. The test results showed that lithium bromide solution in an evacuated tube can be heated up rapidly and generate vapor continuously. The vaporization rate, the solution concentration, the equivalent refrigerating capacity, the total energy absorbed by the solution, the thermal collecting efficiency and the solar coefficient of performance in theory were analyzed according to the test data. The work provides a reference for the design and simulation of SPAR systems where evacuated tubes are used as both solar collector and lithium bromide solution generator. [ABSTRACT FROM AUTHOR]

• An accurate and rapid control strategy is proposed without an aggregated model. • The approach is decentralized in a completely decoupled and bottom-up manner. • The regulation performance has high adaptability and strong robustness. • Data dimensionality reduction and better privacy protection can be achieved. To deal with the power fluctuation caused by renewable energy integration and load growth, it has been a general recognition to provide regulation services for local power system or main grid by flexible loads. There is a certain range of adaption to temperature for users and thermal inertias for building components, making it possible for air conditioning (AC) loads to participate in demand response (DR). Large cluster of ACs offers a resource akin to that of a distributed energy storage system, which is also an important regulation module of virtual power plant (VPP). Inverter air conditioning (IAC) is gradually occupying the market proportion owing to comfort and power savings. It has become a key technology in the new power system on how to coordinate massive IAC resources with heterogeneous parameters and status to output reliable load regulation services. To this end, this paper proposes a consensus control strategy for the IACs cluster based on lightweight decentralized architecture. The task is distributed fairly while ensuring the occupants' comfort. The target load curve can be accurately tracked with high adaptability and robustness. The interactive parameters are generated from the bottom up based on individuals' response ability, which facilitates rapid convergence. Together with the intrinsic adaptability and robustness, the hosting mechanism for the coordinator is designed to guarantee high fault-tolerance, and therefore plug-and-play can be satisfied. Besides, dimensionality reduction and locality for the interaction data ensure a higher level of privacy protection. The advantages are illustrated in case studies and compared with other approaches. To the best of our knowledge, the proposed method has the overwhelming convergence performance over the present literatures. These characteristics indicate a sufficient basis for its application in the variable conditions with massive users and can be extended to more scenarios using consensus control. [ABSTRACT FROM AUTHOR]

Current air conditioning (AC) systems consume a significant amount of energy, particularly during peak times where most electricity suppliers face difficulties to meet the users’ demands, and the global demands for AC systems have increased rapidly over the last few decades leading to significant power consumption and carbon dioxide emissions. This paper presents a new technique that uses liquid nitrogen (LN2) produced from renewable energy sources, or surplus electricity at off peak times, to provide cooling and power for domestic houses. Thermodynamic analyses of various cryogenic cycles have been carried out to achieve the most effective configuration that produces the maximum power output with minimum LN2 flow rate, to meet the required cooling of a 170 m 2 dwelling in Libya. A comparison with a conventional AC system was also made. Results showed that at the current LN2 prices, using LN2 to provide cooling and power demands of residential buildings is feasible and saves up to 36% compared to conventional air conditioning systems with an overall thermal efficiency of 74%. However, as the LN2 price decreases to around 1.3 pence per kg, the proposed technology will have significant advantages compared to conventional AC systems with savings of up to 81%. [ABSTRACT FROM AUTHOR]

This paper presents several robust model predictive controllers that improve the temperature performance and minimize energy consumption in an automotive air-conditioning/refrigeration (A/C-R) system with a three-speed and continuously-varying compressor. First, a simplified control-oriented model of the A/C-R system is briefly introduced. Accordingly, a discrete Model Predictive Controller (MPC) is designed based on the proposed model for an A/C-R system with a three-speed compressor. A proper terminal weight is chosen to guarantee its robustness under both regular and frost conditions. A case study is conducted under various heating load conditions. Two hybrid controllers are made, which combine the advantages of both the on/off controller and discrete MPC such that they will be more efficient under any ambient heating condition. In addition, a continuous MPC is developed for systems with continuous variable components. Finally, the experimental and simulation results of the new controllers and the conventional on/off controller are provided and compared to show that the proposed controllers can save up to 23% more energy. [ABSTRACT FROM AUTHOR]