Chilled Water Flow Research Articles

Experimental studies on the operating characteristics of air-layer-integrated radiant cooling units

Radiant cooling is widely acknowledged as an energy-efficient approach to indoor thermal environment regulation. It offers an improved environment in terms of thermal comfort, compared to traditional air-cooling methods, but suffers from condensation risk and insufficient cooling power in hot and humid climates. To overcome these limitations, an Air-Layer-Integrated Radiant Cooling Unit (AIRCU) was developed, which seals a layer of dry air between an infrared transparent membrane and the radiant cooling surface. This innovative approach allows the use of lower radiant cooling temperatures to increase cooling power while concurrently maintaining the membrane at a higher temperature to minimize the risk of condensation. In our previous studies, the heat transfer model of AIRCUs was established, and the feasibility of the concept was verified. However, there is a lack of research on the operating characteristics of AIRCUs. In this paper, both experimental and numerical studies are conducted to investigate the operating characteristics of the AIRCUs under diverse cooling temperatures, chilled water flow rates, and cooling loads. Results indicated that the thermal environment created by the AIRCUs was uniform, and it can be characterized by uncooled surface temperature and radiant cooling surface temperature. Under different load conditions, the chilled water supply temperature was suggested as the control variable to adjust the thermal environment. To satisfy the thermal comfort, the operative temperature should be controlled within 23.6 °C ∼26.4°C. This study provides valuable guidance on operating variable settings and environmental control of the AIRCU and promotes its application.

Experimental investigation of two-bed adsorption thermophysical battery with mass recovery technology

This paper developed a novel semi-continuous two-bed Adsorption Thermophysical Battery (ATB), utilizing silica gel RD/water as the adsorption pair. The Absorber Bed Unit (ABU) was designed and manufactured using finned tubes, while the condenser and evaporator are incorporated under a single Evaporator-Condenser Unit (ECU). The study investigated the impact of mass recovery, hot and cooled water temperature, and the chilled, cooled, and hot water flow rate on the system performance. The results of the study revealed that the ATBwith mass recovery demonstrated a higher Coefficient of Performance (COP) and Refrigeration Capacity (RC) in comparison to the system without mass recovery. The average COP for the cycles with and without mass recovery were 0.228 and 0.2, respectively. The present study determined that the most favorable duration for mass recovery was 60 s. A substantial reduction in the COP can be observed as the hot and cooled water temperature increases. Also, the COP of the ATB was found to be directly related to the flow rates of chilled and cooled water but not to the flow rates of hot water. In addition, the COP of the two-bed ATB with mass recovery was improved by 14 % compared with the single-bed ATB. Finally, the adsorption uptake rose by 24 % when the cooled temperature was decreased from 313 K to 303 K.

CONFUSION OF REAL SITE IMPLEMENTATION OF VSD UTILIZATION ON WATER PUMP OF A CHILLER PLANT SYSTEM IN OFFICE BUILDING JAKARTA

The utilization of VSD in centralized air conditioning systems has been applied for years for efficiency purposes. However, found in real implementation has not been really applied as its function yet. This paper will present real site implementation of applying VSD on regulating the motor speed of chilled water pump as its function [1] to control the chilled water flow rate [2] go into the evaporator to let the chiller work as correspond on cooling demand at the actual load level and at its necessary power input. By analyzing some related parameters such as temperature, water pressure and amperes measured and observed to be the raw data then they will show the working performance of chiller impact on energy consumed to be evaluated on its efficiency impact. Found the real implementation at this site the VSD does not look like varying the speed of motor pump as usually applied but more by being set at certain frequency such as 32 Hz. Then mostly the chiller cannot be run as high as cooling demand as running at only about 50-60% as lower chilled water flow rate flowing into the evaporator. Other than that it looks efficiency of refrigeration effect on handling the building load is not good enough as mentioned in catalogue/reference with difficulties on reaching the target chilled water leaving temperature.

Study on Effects of Operating Parameters on a Water-Cooled Loop Thermosyphon System under Partial Server Utilization

During the operation of a data center, servers are gradually installed in racks, causing most racks to work under a low heating load for a long time and affecting the cooling efficiency of the loop thermosyphon system (LTS). Thus, the effects of operating parameters on the thermal performance should be investigated. In this study, a water-cooled LTS was experimentally investigated under different airflow rates and heating loads. The results show that the additional liquid refrigerant reduced the heat transfer performance and aggravated a drop in cooling capacity when the airflow rate and heating load were decreased. To further reveal the effects of the operating parameters on the thermal performance and cooling efficiency, a steady-state distributed-parameter model was developed and validated based on the experimental data. The results show that the excessive cooling capacity was reduced by decreasing the airflow rate according to the upper limit of the server exhaust air temperature under partial server utilization. The excessive cooling capacity was reduced by 14.5–52.1% under 5–56.5% server utilization. To further reduce the excessive cooling capacity while ensuring thermal security, the water side operating parameters (including the supply chilled water temperature and water flow rate) were adjusted according to the upper limit of the rack’s average outlet air temperature, which reduced the excessive cooling capacity by more than 23.8% under partial server utilization.

Performance improvement for chilled water air conditioning cooling coils with various dimple fin geometries

The present research inspected the thermal and flow behavior of finned coiled tube heat exchangers in crossflow for chilled water air conditioning systems. The investigation variables cover the impacts of several variables, such as fin dimple shape, the number of fins, and the Reynolds number of water and air sides on the thermal-hydraulic aspects of a finned cooling coiled tube heat exchanger. The goal is to enhance this famous finned cooling coiled tube heat exchanger using dimples concerning the same coiled tube heat exchanger without dimples. Six test specimens were fabricated, three with fin dimple geometries as sharp-sided triangle dimples, curved-sided triangle dimples, and teardrop dimples. The other specimens with three different fin numbers 140, 155, and 170. The test runs were experimented in a transparent air duct with air Reynolds numbers ranging from 1540 to 6205, while the chilled water flow side has experimented with Reynolds numbers ranging from 3350 to 16250. The findings revealed that a higher Nusselt number and flow area goodness factor is achieved by a heat exchanger (D) with a curved-sided triangle fin dimple shape. The energy efficiency ratio for a cooling coil with a fin number of 170 is higher than that of cooling coils with fin numbers 140 and 155 by approximately 24.68% and 12.94%, respectively. Correlations of energy efficiency ratio, effectiveness, flow area goodness factor, and friction factor are extracted according to the experimental results with deviations.

Mathematical modelling of passive displacement dual cooling coil (PDDCC) system in a tropical climate

Unlike the conventional displacement ventilation (DV) systems, the Passive Displacement Dual Cooling Coil (PDDCC) system generates airflow in indoor environments based on natural convection and eliminates the necessity of mechanical ventilation to meet the thermal comfort and indoor air quality requirements. Investigations on such PDDCC systems, though, have been largely limited and its performance capacity and fluid flow behaviour are not fully understood. A mathematical model was, hence, developed in the current study to explore the effects of various boundary conditions on the performance of the PDDCC system. Results obtained from the mathematical model were, first, compared and validated against the measurement readings gathered from an experimental investigation conducted on the PDDCC system in a controlled test environment. The validated mathematical model was then applied to a parametric evaluation where the effects of chilled water supply (CHWS) temperature, flow rate, and return air temperature on the PDDCC system performance were examined. The varying effect of the latent and sensible cooling load was observed at the different boundary conditions applied to the PDDCC model. Slightly more than 32% of rise in total cooling load was predicted by reducing the CHWS temperature which established a much more significant contribution in comparison to the CHWS flow rate which generated approximately 5% rise in the total cooling load. Findings were supported by examining the sensible heat ratio (SHR) and the ratio of Latent cooling load: Sensible cooling load which was then was attributed to the temperature difference between the supply and return air temperature. By ensuring the maximum temperature difference, the total cooling load performance of the PDDCC system can be maximised. The contribution of both the CHWS temperature and flowrate was essential to achieve the maximum cooling load, hence, improving the total cooling performance of the PDDCC as a result.

Dynamic simulation study on regulation characteristics of transcritical CO2 multi-ejector refrigeration system

This paper presents a dynamic model of transcritical CO2 refrigeration system with multi-ejector which is developed based on the real CO2 properties and considering the internal transonic flow, phase change and choking, and its predictions are in good agreement with experimental data from the literature. The transient response of the system is studied by adjusting the speed of compressor, water flow of heat exchanger, opening of expansion valve and combination of ejector as disturbance conditions. The presented results show that the developed dynamic model has similar response rules with the same type of system. Changes of cooling water flow of gas cooler and chilled water flow of flooded evaporator can cause significant response of other pressures in the system except low-temperature evaporator, and can regulate the cooling and heating load to some extent. Opening of medium and low temperature expansion valve plays a decisive role in the system's medium and low temperature refrigeration capacity respectively, and the low-temperature expansion valve is the only regulation means of the low-temperature cooling capacity. Optimal operating combination of multi-ejector maximizes the system performance and ejector pressure lift ratio. Furthermore, the optimal ejector combination of the system under the refrigeration capacity of 75∼115 kW is studied and compared, a control strategy of adjusting ejector combination by "nozzle mass flow rate" is put forward to adapt to the high-performance operation of the system under different loads. Under the research conditions, the optimal ejector combination satisfies that the nozzle mass flow rate is stable in 0.066∼0.070 kg·s-1.

Thermal performance analyses and optimization of data center centralized-cooling system

In this study, the factors that influence the power consumption of a data center centralized-cooling system were investigated from both the indoor thermal environment and chilled water mass flow rate perspectives to maximize the free cooling utilization potential. First, a cooling load model is proposed and verified. Subsequently, based on a typical centralized-cooling system that combines free cooling devices and chillers, mathematical analyses were conducted on its thermal performance, considering different climate regions and heat dissipation densities related to the IT equipment. The results indicated that up to 83.5 % and 75.3 % of the annual cooling demand could be recovered by free cooling in Harbin and Beijing, respectively. However, during actual operations, this value is reduced because of the mixture of cold and hot air and inappropriate chilled water flow rates. To achieve the lowest annual or daily power consumption of the cooling system, the chilled water flow rates were optimized. Under optimal conditions, Power Usage Effectiveness (PUE) can be improved by 4.5 to 30.6 % compared to the worst case scenario under discussion.

Dynamic optimization of chilled water pump operation to reduce HVAC energy consumption

• Actual building energy performance and HVAC system have been simulated. • Optimal control is developed to optimize chilled water pump operation by integrated ANN and GA method. • ANN model has successfully modeled the dynamic relationship between pump operation, indoor temperature, and weather conditions. • Optimization of chilled water flowrate could reduce pump energy consumption by 51.11%. Energy consumption in building has been increasing significantly due to higher demand on cooling system. It consumes a large share of total building energy usage. A proper operation control strategy for this system promises the large energy saving. This paper proposes the optimization of chilled water pump operation to improve the cooling system efficiency in a building. The method is developed by combining the artificial neural network and genetic algorithm. This study aims to develop a control method that can determine the optimal chilled water flow rate to absorb the heat on cooling system during the operation. The building energy performances are modeled using EnergyPlus software, while the control strategy is developed in MATLAB. Input output data sharing between MATLAB and EnergyPlus is performed by BCVTB (Building Controls Virtual Test). The dynamic optimization of chilled water flow rate is carried out continuously during real time operation. The developed control performance has been tested under various operating condition including variable outdoor temperature, sudden change of load condition, and different indoor temperature set point. The results show that the optimization of chilled water flow rate on large cooling system could reduce the energy consumption of chilled water pump as 51.11%.

Simulation and Experimental Study of CO2 Transcritical Heat Pump System with Thermoelectric Subcooling

In order to improve the efficiency of the system and promote its application in other industries, the performance of a thermoelectric subcooled CO2 transcritical heat pump system was studied. A simulation model of the system was established using steady-state lumped parameter technology, and the experimental data were compared with the simulation results. The effects of cooling and chilled water flow rate and temperature, subcooling degree, compressor discharge pressure on the coefficient of performance (COP), and heating coefficient of performance (COPh) were analyzed. The results showed that COP/COPh increased with the increase in cooling and chilled water flow rate and chilled water temperature and decreased with the increase in cooling water temperature. The experimental COPh and COP of the system with a thermoelectric subcooler increased by 4.19% and 4.62%, respectively, compared to the system without it. The simulated data was in good agreement with the experimental data, and the error was within 10%, thus verifying the correctness of the model. When the subcooling degree increased to 11 °C, the system simulation results showed that COP/COPh increased by about 40% and 13.3%, respectively. The optimal high pressure was about 8.0 MPa, which corresponded to the maximum COP and COPh of the system of 3.25 and 4.25, respectively. The research results can provide a theoretical basis for future system optimization.

Investigation on Water Immersing and Spraying for Cooling PV Panel

The use of photovoltaic cells has increased dramatically in recent years. However, the photovoltaic cells convert most of the solar radiation into heat, and this heat negatively affects the PV productivity. Therefore, a cooling system can get rid most of this heat. An experimental and theoretical examination is conducted for the augmentation of PV power and efficiency by using two different water cooling systems. The PV cooling has been equipped with two types of water-cooling systems, i.e. immersion, and spraying. For the immersion cooling, the temperature decrease is achieved but the power output has been low. On the other hand, the water spraying cooling has been studied at three different chilled water flow rates. The solar simulator having an average radiation of 1300 W/m2 is generated through 50 W halogen lights for testing. It has been found out that a 60% temperature reduction has been achieved, with a remarkable increase in power output by 59% and efficiency by 8%. However, no remarkable difference has been achieved by varying water flow rates. Therefore, cooling by spraying system has given better results than immersion. Finally, the experimental results have been found to be consistent with the numerical results.

Development and performance evaluation of a chiller plant predictive operational control strategy by artificial intelligence

Traditionally, chiller plants are controlled and monitored by a predetermined control strategy to ensure appropriate operation based on the designed system configuration. With the use of new technology of variable speed drive (VSD) for compressors, smart control strategies could be leveraged to enhance the system efficiency in lieu of traditional control strategies. For example, using orderly and straightforward switching procedures without considering various factors in switching the units, including the high-efficiency partial load range benefitted from the VSD, the actual performance of the units as a whole and the variable chilled water flow rate, result in the chiller plant not operating at maximum performance and efficiency. To address these issues, a hybrid predictive operational chiller plant control strategy is proposed to optimize the performance of the chiller plant. Artificial intelligence is employed as the data mining algorithm, with big data analysis based on the actual acquired voluminous operation data by fully considering the characteristics of chiller plants without additional installation of large-sized and high-priced equipment. Artificial neural network (ANN) was employed in the control strategy to predict the future outdoor temperature, building cooling load demand and the corresponding power consumption of the chiller plants. At the same time, particle swarm optimization (PSO) was applied to search for the optimized setpoints, e.g., chilled water supply temperature, operating sequence, chilled water flow rate, for the chiller plants. The developed control strategy has been launched in a chiller plant with a cooling capacity of 7,700 kW installed in a hospital in Hong Kong. The system coefficient of performance (COP) and overall energy consumption of the chiller plants were enhanced by about 8.6% and reduced by about 7.9%, respectively, compared with the traditional control strategy. This real-time, continuous, automatic optimization control strategy can determine the most efficient combination of operating parameters of a chiller plant with different control settings. This ensures that the chiller plant operates in its most efficient mode year-round under various operational conditions.

Testing of a Falling-Film Evaporator for Adsorption Chillers

In this work, the performance of an innovative evaporator based on water falling film was investigated. The studied evaporator has been equipped with a recirculation system to maximise the wetted surface. Tests have been carried out in a lab-scale adsorption unit connected to a test bench recently realised at Politecnico di Milano labs for evaluating heat transfer performances under realistic operating conditions. Several ad/desorption cooling cycles were performed, setting different liquid refrigerant initial contents (0.9–1.5 kg), different chilled water inlet temperatures (7–20 °C) and flow rates (200–1000 L/h) and different adsorbent bed temperatures (25–30 °C). Evaporation performance has been determined in delivered cooling capacity. Moreover, the experimental data were used to calculate the overall evaporator heat transfer conductance (UA). Experiments showed how the heat duty peaks are mainly due to the thermal level of the chilled water that enters the evaporator, not the water content inside it because this value only affects the duration of the process. Instead, the UA value does not depend on the evaporator inlet chilled water temperature and initial mass content inside the evaporator. UA is 540–570 W/K for temperatures of chilled water entering the evaporator, equal to 10–20 °C, and mass of refrigerant of 0.9–1.5 kg.

Room temperature and humidity decoupling control of common variable air volume air-conditioning system based on bilinear characteristics

Variable air volume (VAV) air-conditioning (AC) systems are widely employed to achieve a comfortable room thermal and humid environment depending on its better regulation performance and energy efficiency. In the single coil VAV AC system, conventional proportional-integral (PI) control algorithm is usually adopted to track the set-points of the room temperature and humidity by regulating the supply air flow rate and the chilled water flow rate, respectively. However, the control performance is usually not good due to the high coupling of the heat and mass transfer in the air-handling unit (AHU). A model-based control method is developed to realize the decoupling control of the room temperature and humidity according to the bilinear characteristics of the temperature and humidity variation. In this control method, a bilinear room temperature controller is used to track the room temperature set-point based on the real-time cooling load, while a room humidity controller is used to track the room humidity set-point depending on the real-time humidity load. The control performance was validated in a simulated VAV AC system. The test results show that comparing with the conventional PI control, the room temperature and humidity are controlled much more robustly and accurately by using the proposed model-based control method.

User-friendly fault detection method for building chilled water flowmeters: Field data validation

In building HVAC systems, a chilled water flowmeter is an important sensor. Its reading can be used to measure the real-time cooling load, which is a critical variable for the automated control of building HVAC systems, especially central chiller plants. To maintain accurate reading data, fault detection and diagnosis (FDD) of flowmeters are necessary. The available FD/FDD methods for chilled water flowmeters have several common disadvantages: (1) high requirements on sensor integrity: multiple sensors are usually involved in the construction of energy balance models; (2) complex methodology: the fault of any monitored sensor could trigger a detection hit, and a diagnosis procedure must be used to isolate the faulty sensor; and (3) the more sensors that are involved, the more difficult it is to collect fault-free historical data for the establishment of a fault-free benchmark. To address these problems, a user-friendly fault detection (FD) method for building chilled water flowmeters is proposed in this study. The proposed method requires three types of variables to function: the pump frequency, the pump power, and the measured chilled water flow rate on the header pipe. The real-time pump frequency and electrical power data that are collected by VFDs/power meters are used to estimate the true value of the chilled water flow rate with random forest regressor. An auxiliary alarm rule is proposed to tackle the tradeoff issue between detector sensitivity and false alarm rate. Field data of a real HVAC system are used in a case study to evaluate the performance of the proposed method in comparison with three existing FD methods. The results of the validation case study suggest that compared to existing FD methods, which are based on the physical pump model, ensemble learning and clustering techniques, the proposed method could realize higher hit rates and higher alarm rates when confronting different faults (bias, noise and drift) at various levels. Besides, due to the proposed alarm rule, false alarms caused by occasional data errors are completely evaded. Sensitivity analysis to the proposed method indicates that the random forest with default hyperparameters is good enough for the FD task. In brief, the good features of the proposed method (i.e., the simple workflow, low sensor requirements, accessible robust input variable data, handy estimation model, auxiliary alarm rule with tight detection threshold) render the proposed method feasible and user-friendly for engineering practice.

Adaptive control algorithm with a retraining technique to predict the optimal amount of chilled water in a data center cooling system

We developed control algorithms based on one of three artificial-intelligence-based retraining techniques (sliding window, vector adaptation, and vector augmentation) to provide the optimal indoor temperature and save on the energy expenditure for cooling in data centers. The artificial neural network prediction model predicts the computer room air handler supply air temperature of a central chilled water system and is added to the control algorithm. The proposed algorithm can determine the optimal chilled water flow rate required to cool the server to the set temperature by using the predicted computer room air handler supply air temperature. We developed a control algorithm embedded in an artificial neural network predictive model that includes three retraining techniques. Afterward, we compared the control performance and verified its adaptability by using computer simulation. When using the algorithm with sliding window control, the root mean-squared error between the set temperature and the control temperature was 0.08 °C, the maximum error was 0.81 °C, and the cooling load was 21,026.27 kWh. The accuracy, stability, and energy-saving ability of the sliding window control algorithm were higher those of the other two algorithms, and its superior adaptability and scalability under changing environmental conditions were demonstrated.

SOIL TEMPERATURE CONTROL FOR GROWING OF HIGH-VALUE TEMPERATE CROPS ON TROPICAL LOWLAND

Low soil temperature (14℃–20℃) favours growing of high-value temperate crops that are known to have higher return per hectare of land than other widely cultivated crops, thereby presenting increased income to farmer. However, due to high soil cooling load, growing these crops on tropical lowland area is a challenge except through greenhouse farming or on few cool higher altitudes with resemblance of temperate climate. Greenhouse farming involves cooling the entire volume of planting zone and is energy intensive, while few cool highlands are not sufficient to achieve food security in this direction. This study aims at application of chilled water for direct cooling of soil, to create favorable soil conditions for optimal performance of planted temperate crops. However, soil cooling using vapour compression refrigeration system may not be economically viable. Solar thermal chilled water production system is presented in this study to supply the cooling. The system consists of absorption refrigeration system and dimensioned size of soil bed with chilled water pipe network. The study includes modeling of soil cooling load to determine the refrigeration power required to overcome such load. The modeled system matched well with the experiment; having standard deviation of 1.75 and percentage error of 12.24%. Parametric analysis of the soil cooling showed that temperatures of cooled soil were significantly affected by chilled water flow rates. The regression equation developed from the Analysis of Variance (ANOVA) is suitable for predicting cooled soil temperature. The cooling process is technically feasible, with potential for greenhouse gas emission reduction.

Application of machine learning and its improvement technology in modeling of total energy consumption of air conditioning water system.

Accurate energy consumption model is the basis of energy saving optimal control of air conditioning system. The existing energy consumption model of air conditioning water system mainly focuses on a certain equipment or a part of the cycle. However, the coupling between water system equipment will affect the setting of optimal energy consumption of equipment. It is necessary to establish the energy consumption model of water system as a whole. However, air conditioning water system is a highly nonlinear complex system, and its precise physical model is difficult to establish. The main goal of this paper is to develop an accurate machine learning modeling and optimization technique to predict the total energy consumption of air conditioning water system by using the actual operation data collected. The main contributions of this work are as follows: (1) Three commonly used machine learning techniques, artificial neural network (ANN), support vector machine (SVM) and classification regression tree (CART), are used to build prediction models of air conditioning water system energy consumption. The results show that all the three models have fast training speed, but the ANN model has better performance in cross-validation. (2) The improved differential evolution algorithm was used to optimize the parameters (initial weights and thresholds) of the ANN, which solved the problem that the ANN is easy to fall into the local optimal solution. The simulation results show that the root mean square error (RMSE) of the improved model decreases by 20.5%, the mean absolute error (MAE) decreases by 30.2%, and the coefficient of determination (R2) increases from 0.9227 to 0.9512. (3) Sensitivity analysis of the established optimization model shows that chilled water flow, chilled water outlet temperature and air conditioning load are the main factors affecting the total energy consumption.

Performance Testing and Analysis of Silica Gel-Water Adsorption Refrigerator

In recent years, adsorption refrigeration technology has attracted wide attention from experts and scholars at home and abroad due to its environmental friendliness and energy saving advantages. In order to study the effectiveness of adsorption refrigeration technology to recover low-grade energy, a silica gel-water adsorption refrigeration system was proposed, which can effectively utilize low-grade energy such as industrial waste heat. The structure and composition of the system are introduced. The operation performance of the unit is tested under different working conditions by orthogonal experimental method, and the experimental results are analyzed. The effects of hot water temperature and flow, chilled water temperature and flow on the refrigeration capacity and COP value of the system are obtained. The experimental results show that under the low-temperature heat source of 55-75°C, the cooling capacity of the system can reach 5.3-12 and the COP value can reach 0.36-0.56. Under the same hot water temperature difference, the cooling capacity and COP value of the system increase rapidly under the condition of changing the hot water temperature at low temperature, indicating that increasing the heat source temperature at low temperature has a greater impact on the system performance. Through the analysis of primary and secondary effects, it is concluded that the inlet temperature of hot water is the main factor affecting the refrigeration capacity and COP value of the system.

Parameter selection in data-driven fault detection and diagnosis of the air conditioning system

Data-driven fault detection and diagnosis system (FDD) has been proven as simple yet powerful to identify soft and abrupt faults in the air conditioning system, leading to energy saving. However, the challenge is to obtain reliable operation data from the actual building. Therefore, a lab-scaled centralized chilled water air conditioning system was successfully developed in this paper. All necessary sensors were installed to generate reliable operation data for the data-driven FDD. Nevertheless, if a practical system is considered, the number of sensors required would be extensive as it depends on the number of rooms in the building. Hence, parameters impact in the dataset were also investigated to identify critical parameters for fault classifications. The analysis results had identified four critical parameters for data-driven FDD: the rooms' temperature (TTCx), supplied chilled water temperature (TCHWS), supplied chilled water flow rate (VCHWS) and supplied cooled water temperature (TCWS). Results showed that the data-driven FDD successfully diagnosed all six conditions correctly with the proposed parameters for more than 92.3% accuracy; only 0.6-3.4% differed from the original dataset's accuracy. Therefore, the proposed parameters can reduce the number of sensors used for practical buildings, thus reducing installation costs without compromising the FDD accuracy.