Chiller fault detection and diagnosis can optimize building energy and maintenance costs. Previous reviews have largely overlooked the detailed assessment of chiller fault detection methods; this ...study focuses on chiller methods proposed since 2004. Categorized into regression-based, classification-based, and knowledge-based approaches, the study delves into their procedural aspects and practical implications for field-installed chillers such as availability of the required training parameters and information, accuracy versus energy performance fault impact, and complexity of required data. Classification-based methods are mostly supervised learning, and few have been validated with faulty chiller data from real-world installations. Over 90% of classification-based, over 70% of regression-based, and all knowledge-based surveyed methods were tested using experimental data only. Some measured parameters like the subcooling temperature, oil feed pressure, and oil sump temperature that are commonly used in model training for detection and diagnosis algorithms are rarely measured in field installations. Despite significant research efforts to enhance the early detection of refrigerant leakage and condenser fouling faults, studies indicate minimal impact of these faults at low severities. Justifying their early detection may primarily rely on environmental considerations. To bolster field implementation, incorporating common factory-installed sensor parameters in new method development or testing of existing ones is recommended. Means that can provide faulty data for classification-based methods should also be devised. Hybrid methods that incorporate experts’ knowledge in the detection and diagnosis algorithms are encouraged and more testing of existing methods with real-world installations to ensure applicability is recommended.
•The field-implementation potential of chiller FDD methods is explored.•Fault-detection accuracies have significantly improved since 2004.•Classification-based methods are challenged by absence of real-world faulty chiller data.•Several proposed methods use parameters from sensors that are rarely factory-installed.•Low-severity detection of some faults is environmentally appealing but has little energy impact.
This study evaluates the energy efficiency of multi-chiller systems in large office buildings, focusing on their optimization across various climate zones as defined by ASHRAE. Using EnergyPlus for ...simulations, the research examines five different load distribution algorithms in multi-chiller systems that range from one to ten chillers, aiming to understand their effectiveness in 15 distinct climate zones. The primary objectives of the study include identifying the energy efficiency of multi-chiller systems in each climate zone, determining the appropriate number of chillers for each zone, and evaluating the performance of the load distribution algorithms. Based on the U.S. Department of Energy’s commercial building model, the results suggest that multi-chiller systems can significantly reduce cooling energy consumption in various climates. Among the algorithms evaluated, the Sequential Uniform Part Load Ratio (SUPLR) algorithm demonstrates notable efficiency, especially in the 4A climate zone (Baltimore), where it achieves substantial energy savings. Applying the SUPLR algorithm in a multi-chiller setup with four chillers in this zone leads to an estimated 24.5 % reduction in energy usage, equivalent to 183 MW annually. The research indicates that a range of 3 to 5 chillers is typically optimal for most climate zones. In-depth analysis in the 4A climate zone highlights the importance of minimizing operation hours at low Part Load Ratios (PLR) to ensure that chillers operate at a high Coefficient of Performance (COP). This strategy underscores the potential of well-designed multi-chiller systems to reduce cooling energy demand, particularly in climates with transitional seasons. This study provides an overview of the energy-saving potential of multi-chiller systems, applicable across a variety of climatic scenarios.
•A building energy model is created using DeST to simulate the hourly cooling load of the office building.•Feasible chiller combinations are studied based on 13 available chillers with different ...capacities.•Four control strategies are explored, including three sequencing control strategies based on weekly, daily, and hourly maximum cooling loads and one optimal control strategy.•The results indicate that it is essential to control the chiller plant hourly; however, the optimal control may not be necessary.•The capacity of the chillers should be slightly different to provide flexibility for control.
Buildings consume about 20% of the total primary energy use in China. It is critical to enhancing building energy efficiency for sustainable development. The heating, ventilation, and air-conditioning (HVAC) systems account for about half of the energy consumption in commercial buildings. For large commercial buildings, central chiller plants are typically used to provide chilled water for space cooling and consume lots of energy. This study evaluates the impacts of different chiller design and their operation strategy on the energy performance of central chiller plants. A case study is conducted using an office building located in Beijing, China. Feasible chiller combinations are studied based on 13 available chillers with different capacities. Four control strategies are explored, including three sequencing control strategies based on weekly, daily, and hourly maximum cooling loads and one optimal control strategy. A building energy model is created using DeST to simulate the hourly cooling load of the office building, and calibrated using the measured data. An integration model has been developed in MATLAB scripts to calculate the annual energy consumption of the chillers for each chiller design under each control strategy. The results indicate that it is essential to control the chiller plant hourly; however, the optimal control may not be necessary. It is not good to select the chillers with all the same capacity. The capacity of the chillers should be slightly different to provide flexibility for control. The design of the chiller combination is essential in the design stage. When bad combinations of chillers were designed, the performance of the chiller plant may be low even with optimization control strategies.
A hybrid network integrating absorption and compression chillers is a suitable solution to respond to the variable cooling demand in a large-scale chiller plant, in regions with multiple energy ...sources. However, the design and control challenges of such networks remain uncharted, lacking a comprehensive approach. This study presents a general procedure for designing a hybrid chiller network for a building with an arbitrary annual cooling demand distribution. The procedure determines the optimal configuration considering the different capacity ratios of absorption to compression chillers, chiller numbers, and arrangements. Utilizing the Particle Swarm Optimization algorithm, the optimal chiller loading distribution is found for each configuration. Life cycle cost analysis aids in selecting the optimal configuration. Simulations conducted in TRNSYS, reveal that optimal energy and economic choices depend on the natural gas and electricity price ratio. The best energy performance occurs at a low capacity ratio, while the economic trend varies with capacity ratio for different price ratios. The potential reduction in life cycle cost associated with the configuration, when compared to the full absorption baseline and the full compression baseline, can reach up to 7,210,000 $ (72.6%) and 724,000 $ (24.5%), respectively. From an environmental perspective, compared to the full absorption baseline and the full compression baseline, hybrid chiller configurations reduce the CO2 emissions for up to 899 tons (68.8%) and 52 tons (11.3%), respectively.
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•General approach for design of hybrid chiller network.•Evaluating various configurations in terms of absorption-compression capacity ratio.•Evaluating optimal configuration for different price ratio of gas to electricity.•Applying Particle Swarm Optimization algorithm as performance control strategy.•Analyzing configurations from energy, environmental, and economic perspectives.
As part of the design process of a chiller plant, one of the final stages is the energy testing of the system in relation to future operating conditions. Recent studies have suggested establishing ...robust solutions, but a conservative approach still prevails at this stage. However, the results of some recent studies suggest the application of a new co-design (control–design) approach. The present research involves a comparative analysis between the use of conventional staging and the co-design approach in the design phase of a chiller plant. This paper analyzes the energy consumption estimations of six different chiller plant combinations for a Cuban hotel. For the conservative approach using on/off traditional staging, the results suggest that the best option would be the adoption of a chiller plant featuring a symmetrical configuration. However, the outcomes related to the co-design approach suggest that the best option would be an asymmetrical configuration. The energy savings results were equal to 24.8% and the resulting coefficient of performance (COP) was 59.7% greater than that of the symmetrical configuration. This research lays firm foundations for the correct choice and design of a suitable chiller plant configuration for a selected hotel, allowing for significant energy savings in the tourism sector.
Automatic fault detection and diagnosis (AFDD) for chillers has significant impacts on energy saving, indoor environment comfort and systematic building management. Recent works show that the ...artificial intelligence (AI) enhanced techniques outperform most of the traditional fault detection and diagnosis methods. However, one serious issue has been raised in recent studies, which shows that insufficient number of fault training samples in the training phase of AI techniques can significantly influence the final classification accuracy. The insufficient number of fault samples refers to the imbalanced-class classification problem, which is a hot topic in the field of machine learning. In this study, we re-visit the imbalanced-class problem for fault detection and diagnosis of chiller in the heating, ventilation and air-conditioning (HVAC) system. The generative adversarial network is employed and customized to re-balance the training dataset for chiller AFDD. Experimental results demonstrate the effectiveness of the proposed GAN-integrated framework compared with traditional chiller AFDD methods.
•This work proposes a chiller AFDD method integrating generative adversarial network.•The traditional GAN is revised to meet the requirements of chiller AFDD.•A comparative study is conducted to show the effectiveness of the proposed method.
•Fault indicative features are used for FDD.•FDD performance for system-level faults is improved significantly.•Fault detection and fault diagnosis are carried out simultaneously.•Least square ...support vector machine (LS-SVM) is optimized before FDD.•Optimized LS-SVM model is more effective and efficient than the other two (SVM and PNN).
Fault detection and diagnosis (FDD) of chillers, generally the single most energy consuming piece of building equipment, is an important but hard task where many parameters are involved, and the problem is always quite non-linear. This study proposes a least squares support vector machine (LS-SVM) model optimized by cross validation to implement FDD on a 90-ton centrifugal chiller. Four component-level and three system-level faults were investigated. The effectiveness and efficiency of the eight fault-indicative features extracted from the original 64 parameters have been validated and employed in the detailed discussions. The results indicated that as compared with the other two machine learning methods, the proposed LS-SVM model with optimization showed a better FDD performance in terms of the overall correct rate for all the samples, the individual correct rate for each fault, the diagnostic efficiency, the detection rate and the false alarm rate, etc., especially when it comes to the faults of system level where the detection and diagnosis become rather more difficult due to the system-level effect (SLE)—widespread symptoms caused throughout the system. The correct rates for system-level faults of refrigerant leak/undercharge, refrigerant overcharge and excessive oil were as high as 99.59%, 99.26% and 99.38%, respectively, and the running time was only 36.7% of that of the SVM model.
A novel solar based combined system is proposed to produce hydrogen and cooling. The presented cogeneration system is analyzed in detail from the viewpoints of exergy and exergoeconomic (exergy based ...economic analysis). The proposed system includes a concentrated PVT (CPVT), a single effect LiBr-H2O absorption chiller and proton exchange membrane electrolyzer (PEM). Produced electrical power is consumed in the PEM electrolyzer to split water into oxygen and pure hydrogen while heat removal from the CPVT is done by the absorption chiller to guarantee its better performance. Second law analysis showed that, among the three different parts of the system, the most part of exergy destruction refers to the CPVT followed by absorption chiller unit and PEM electrolyzer. Also, it is observed that, among the absorption units' components, the highest percent of exergy destruction belongs to the generator which absorbs the heat from the CPVT. Moreover, exergoeconomic analysis revealed that the most important unit from the viewpoint of economic is the CPVT with the capital investment cost of 0.08946 $/h and an exergoeconomic factor of 28.82%.
•A solar based energy system is presented in order to produce hydrogen and cooling.•Exergy and exergoeconomic principles is applied to presented system.•The system components are listed in the order of cost descending.
•Methods to enhance the robustness of chiller sequencing control were developed.•The proposed methods hybridizes the use of different load indicators.•The proposed methods were evaluated under ...different levels of uncertainty.•The proposed methods show their robustness even when the uncertainty is significant.
Chiller sequencing control is an important technique for achieving energy efficiency of multi-chiller plants while not sacrificing indoor thermal comfort. Available typical controls, such as bypass flow-based control and direct power-based (P-based) control, uses individual indicator to switch chillers on or off. However, these controls suffer from various uncertainties in operation and may lead to insufficient cooling supply, unstable operation, or energy waste. A simple but practical way to enhance the robustness of chiller sequencing control is to explore and make use of the complementarity of different load indicators. Hence, this paper presents three methods to enhance the robustness of chiller sequencing control by hybridizing the use of different load indicators. Numerical studies are used to analyze the robustness of the enhanced controls under different levels of uncertainty.
•Proposes a model-free optimization scheme for parallel-chiller plant with multivariable ESC.•Penalty-function multivariable ESC is used to avoid integral windup due to actuation saturation.•The ...chiller sequencing control logic is based on ESC inherent control signals.•Validated with simulations on a Modelica based model of a two-chiller plant.•Simulation results show good steady-state performance and reasonable transient performance.
Chilled water plants with multiple chillers are commonly used to provide cooling in large commercial buildings. Optimization offers a significant opportunity for improving the energy efficiency of such plants. Model based approaches used for control and optimization require accurate models, which can be difficult and/or expensive to obtain in practice due to large variations in equipment characteristics and operating conditions. In this paper, a model-free optimization strategy based on multivariate Extremum Seeking Control (ESC) with penalty terms is proposed for maximizing the energy efficiency of a chilled-water plant with parallel chillers. The feedback to ESC is the total power consumption of the plant consisting of chiller compressors, cooling tower fan, and condenser water pumps, in combination with penalty terms for input-saturation. The control inputs include the cooling tower fan airflow, condenser water flows and evaporator leaving chilled-water temperature setpoint. A band-pass filter array, instead of the high-pass filter in the standard ESC, is adopted to reduce the coupling among the input channels. The proposed strategy is evaluated with simulation study using a Modelica based dynamic simulation model of a chilled-water plant with two parallel chillers. Six cases are presented that demonstrate real-time optimization capability of ESC for this application.
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