Online fault detection and diagnosis in VAV air handling unit by RARX modeling

Assimilation of cost-effective fault detection and diagnosis (FDD) technique in building management system can save enormous amount of energy and material. In this paper, recursive autoregressive exogenous algorithm is used to develop dynamic FDD model for variable air volume (VAV) air handling units. A methodology, based upon frequency response of the model is evolved for automatic fault detection and diagnosis. Results are validated with data obtained from a real building after introducing artificial faults. Robustness of the method is further established against sensor errors arising out of faulty bias during long term use or lack of proper commissioning. It is concluded that the method is quite robust and can detect and diagnose several types of faults. A short and simple method is also included in this paper to detect the faults of VAV units operating in the same zone by comparing their behavior. The new method, which requires very small amount of computation time, was tested with the aforementioned database and shows satisfactory results.     

Multi-floor building heating models in MATLAB and Modelica environments

Buildings are one of the largest energy consumers in the world.In northern countries,buildings consume most of the energy for space heating owing to the predominating cold climate conditions.Today there is a trend to use Building Energy Management Systems(BEMS)in buildings to make the indoor environment more comfortable and to utilise energy in a more efficient way.Currently,BEMS lack a building heating model,and the control is often based on temperature zones.Integration of a good building heating model with BEMS may assist in monitoring the heating of buildings in an optimal way while saving energy.Hence,the goal is to develop a model that can be applied in on-line control with acceptable performance and accuracy.This article covers multi-floor physics-based building heating modelsdeveloped in MATLAB and Modelica environments.The Modelica model uses the model components from Modelica Buildings Library and is more complex than the MATLAB model.The applicability of the two models in on-line control in BEMS principally depends on the accuracy of the predictions and prediction time.The prediction accuracy of both models is satisfactory while the Modelica model is robust.With the used computational power,the MATLAB model provides faster results compared to the Modelica model.More real-time experiments are needed for both models,and they can be applied in on-line control,depending on the model simplicity,available computational power and real-time segments in the system.In addition,the methodology used in the MATLAB model development is application independent and can be implemented in different natures of building configurations.     

An experimental study of energy consumption and thermal comfort for electric and hydronic reheats

This paper compares the performances of electric and hydronic reheat modes for variable-air-volume units using experimental data for a building. The comparisons are made based on the daily energy consumption associated with each reheat mode and comfort performances within a building zone. Data are collected from a full-scale heating, ventilating, and air conditioning system. Weather conditions are considered and the corresponding energy distributions are evaluated. The results showed that the energy for the air handling unit using hydronic reheat is lower than that using electric reheat by about 24% when the air handling unit is operated in either the mechanical or mechanical and economizer cooling mode and 33% for the economizer cooling mode. The reheat energy for the variable-air-volume units using hydronic reheat is lower by about 75% than for electric reheat for either the mechanical or mechanical and economizer cooling mode and 54% for the economizer cooling mode. The main reason for the low-energy consumption using hydronic reheat is attributed to the lower requirement for the minimum air flow across the reheat coil. Electric reheat provides a slightly cooler comfort environment than that for hydronic reheat.     

A study on the energy penalty of various air-side system faults in buildings

Automatic fault detection and diagnosis (FDD) can help enhance building energy efficiency by facilitating early detection of occurrence of system faults, especially those of air-conditioning systems, thus enabling rectification of the faults before much energy is wasted due to such faults. However, building owners may not invest in FDD unless they are convinced of the energy cost savings that can be achieved. This paper presents the results of a study on the energy cost impacts of a range of common system faults in variable air volume (VAV) air-conditioning systems, which are widely adopted for their good part-load energy efficiency. The faults studied include room air temperature sensor offset, stuck VAV box damper, supply air temperature sensor offset, stuck outdoor air damper and stuck/leaking cooling coil valve. The simulation results indicate that some faults may significantly increase energy use in buildings, for example, negative room air temperature sensor offset, stuck open VAV box damper, negative supply air temperature sensor offset, stuck open outdoor air damper and stuck open and leaking cooling coil valve. Since building occupants may adapt to the symptoms of these faults, such as reduced room air temperature, and thus may not complain about them, the occurrence of such faults are not immediately apparent unless a FDD system is available. Some other faults, e.g. positive supply air temperature sensor offset, positive room air temperature sensor offset, stuck closed cooling coil valve and stuck closed VAV box damper, may allow less energy to be used but will lead to unbearable indoor environmental conditions, such as high indoor temperature. Such faults, therefore, can easily be detected even without a FDD system, as there will be feedback from the building occupants.     

The heating system as a distributed sensor network

The conventional method of obtaining a detailed picture of the energy performance of a building is by the installation of a dense network of air temperature sensors. The data from all the sensors is accumulated at a central point for analysis. However, it is argued that air temperature measurement is merely a secondary indicator of energy use and a more direct method of tracking energy flow is preferable. Focussing on the types of heating system where heat is produced at a central source and pumped around the building (for example, hydronic systems), it is suggested the heating system itself can function as a low-cost distributed sensor network to directly monitor energy use, although the information retrieved is mixed in a complex way that is dependent on the topology of the distribution system. It is claimed that high-resolution information can nevertheless be extracted by mapping the acquired data to the geometry of the system and by the use of adequate computer processing power to run the physical model. A method of testing the concept in a domestic context is described as a precursor to more extensive deployment.     

A development of easy-to-use tool for fault detection and diagnosis in building air-conditioning systems

There are many reports about faulty status in building air-conditioning systems recently. It becomes difficult to keep indoor air temperature appropriately as faults occur, and the faults cause waste of building energy consumption. The model-based fault detection and diagnosis (FDD) methods have been researched for specific parts of air-conditioning system such as chillers, coils, variable air volume units (VAV units), etc. It needs, however, much time and labor to monitor and check every single part because we cannot predict where and when the faults occur. The purpose of this study is to examine indoor air temperature changes and energy consumption increase when faults occur and to develop an easy-to-use FDD tool that helps to find out the faulty place through the whole building air-conditioning system. And then, we treat the reliability of the proposed FDD tool and effectiveness to control of indoor environment deterioration and energy consumption increase by the tool is evaluated based on building air-conditioning system simulation in this paper.     

A cellular automaton based model simulating HVAC fluid and heat transport in a building. Modeling approach and comparison with experimental results

A discrete model characterizing heat and fluid flow in connection with thermal fluxes in a building is described and tested against experiment in this contribution. The model, based on a cellular automaton approach, relies on a set of a few quite simple rules and parameters in order to simulate the dynamic evolution of temperatures and energy flows in any water or brine based thermal energy distribution network in a building or system. Using an easy-to-record input, such as the instantaneous electrical power demand of the heating or cooling system, our model predicts time varying temperatures in characteristic spots and the related enthalpy flows whose simulation usually requires heavy computational tools and detailed knowledge of the network elements. As a particular example, we have applied our model to simulate an existing fan coil based hydronic heating system driven by a geothermal heat pump. When compared to the experimental temperature and thermal energy records, the outcome of the model coincides.     

Evaluation of hydronic loop energy and modeling of heated water loop containing multiple variable air volume units with hydronic reheat coils

Experimental data recorded for a heating, ventilating, and air conditioning system showed that the daily heated water loop energy calculated by summing the hourly-averaged loop heat transfer for the heated water loop is almost 35% higher than the sum of the daily energy consumed by variable air volume hydronic reheat coils in each zone. The main reason for this difference was attributed to the time delay of the loop return water temperature caused by the water traveling along the loop. This study examines methods to evaluate the heated water loop energy when there are time varying conditions. Data for a heated water loop are used to demonstrate the effects of the time delay on the evaluation of the loop energy. A pipe heat transfer model characterizing the transient response of a fluid flowing through a single pipe is developed to examine the effects of time varying conditions on the pipe thermal response. Based on the pipe heat transfer model, a loop model is constructed to simulate the actual loop with multiple hydronic reheat coils. The comparisons of the simulation results with the data indicate that the loop model is capable of predicting the loop return water temperatures and loop heat transfer based on data.     

Evaluation of the control performance of hydronic radiant heating systems based on the emulation using hardware-in-the-loop simulation

This study presents an emulation method to evaluate the control performance of a hydronic radiant heating system. Since heat output in the system is dependent on the pressure loss and flow rate in the hydronic network, the interaction between thermal and hydronic models needs to be considered in the evaluation of the control performance. For this reason, many studies apply an integrated simulation to the evaluation; however, the analysis of the hydronic network sometimes leads to unreliable results due to the improper initial values for algebraic loops or the lack of modeling information on the hydronic components. In order to deal with this problem, this study suggests an emulation method, where the hydronic network is replaced by real hardware and the building physics is analyzed by a simulation. In the emulation, the pressure loss and flow rate in the hydronic network were represented by replacing the real pipe with equivalent hydraulic resistance. In addition, by using real control systems that connect the hydronic network and building simulation, the interaction between building physics and hydronic network could be considered in the evaluation. Based on the proposed emulation method, the performance of several control strategies was evaluated in terms of the accuracy and the rise time. The result shows that the individual control needs to be combined with hydronic balancing for more accurate control. Hydronic control devices such as a flow limit valve and a pressure differential control valve also proved to be helpful to the improvement of the control performance.     

Optimum operating performance based online fault-tolerant control strategy for sensor faults in air conditioning systems

This paper presents an online fault-tolerant control strategy. By correcting the faulty measurements with a final correcting factor, the strategy covers five steps: fault detection, construction of correcting alternatives, performance forecasting, alternatives outranking, and fault correction. System energy, indoor air quality, human thermal comfort, and control efficiency are considered as a whole to evaluate the operating performance. Taking the supply air temperature sensor faults as testing examples, the strategy is tested in a virtual air conditioning system and simulated on TRNSYS platform. The testing results show that a large fault correcting factor is obtained in the first hour, an adjusting phase presents in the next several hours, and the correction factor keeps unchanged finally. High level of calculating accuracy is required for the performance prediction model. Also, for the outranking evaluation model, the thresholds and weight coefficients should be assigned appropriately to meet the requirements of building functions and/or owners.     

Simulink simulator for building hydronic heating systems using the Newton-Raphson algorithm

The efficiency of heating systems is increasingly important because of the increasing need to save energy and protect the environment. This paper presents an innovative technique for modeling multi-zone hydronic heating systems in buildings in an easier and more user friendly manner. An original approach is described in which the thermal and hydronic systems are solved simultaneously by simulating the dynamic behavior of pipe water flow rates, water temperatures, and room air temperatures. The simulation uses mathematical models that apply a Newton-Raphson method (NRM) developed in Matlab^© and Simulink^© environments. A user friendly graphical user interface (GUI) enables the designer to analyze any multi-zone hydronic heating system from the point of view of improving its efficiency.A laboratory heating system was used to validate this modeling technique. A series of trials were conducted in a multi-zone laboratory heating system located within the R&D division of a leading Italian boiler manufacturer, and the results presented in this paper validate the model.     

Hydronic radiant cooling — preliminary assessment

A significant amount of the electrical energy used to cool non-residential buildings equipped with all-air systems is drawn by the fans that transport the cool air through the thermal distribution system. Hydronic systems reduce the amount of air transported through the building by separating the tasks of ventilation and thermal conditioning. Due to the physical properties of water, hydronic systems can transport a given amount of thermal energy and use less than 5% of the otherwise necessary fan energy. This improvement alone significantly reduces the energy consumption and peak-power requirement of the air conditioning system. Radiant cooling has never penetrated the US markets significantly. The scope of this survey is to show the advantages of radiant cooling in combination with hydronic thermal distribution systems, as compared to the commonly-used all-air systems. The report describes the development, thermal comfort issues, and cooling performance of the hydronic systems. The peak-power requirement is also compared for hydronic systems and conventional all-air systems.     

建筑能源管理与控制系统中传感器故障及其检测与诊断

描述了传感器故障类型，给出了其故障函数。用主成分分析法对建筑能源管理与控制系统测量数据进行建模并对空调检测系统中的四类传感器故障进行检测与诊断。结果表明主成分分析法具有很好的故障检测和故障诊断能力。     

Conversion of electric heating in buildings: An unconventional alternative

To decrease the electric energy used for heating buildings it has become desirable to convert direct electrical heating to other heat sources. This paper reports on a study of the possibility of using an unconventional method for conversion to avoid installing an expensive hydronic system. The conversion method combines the ventilation and heating systems and uses air instead of water for distribution of heat within the building, taking advantage of thermal forces and the special properties of gravity currents. Full-scale tests have been carried out in a test apartment inside a laboratory hall where the conditions could be controlled. Temperatures and efficiency of ventilation have been measured to ensure that the demands with respect to thermal climate and air exchange were fulfilled. The results show that it is possible to use the method for heating and ventilation when converting the heating system, but further work has to be done to develop a detailed solution that works in practice.     

A fault detection technique for air-source heat pump water chiller/heaters

This paper describes a fault detection method and system to detect the faults in air-source heat pump water chiller/heaters. Principal component analysis (PCA) approach is used to extract the correlation of variables in heat pump unit and reduce the dimension of measured data. A PCA model is built to determine the thresholds of statistics and calculate square prediction errors (SPE) of new observations, which are used to check if a fault occurs in heat pump unit. The fault detection system consists of a PCA-based fault detection code, a backpack computer, a digital logger and eight easy-to-install temperature sensors. A real air-source heat pump water chiller/heater for the air-conditioning system of an office building provides the realistic test platform for the validation of fault detection method. The measured data from the heat pump unit under normal condition shows that the PCA model can capture the major correlation and variance among the test variables. Two levels of artificial condenser fouling fault are successfully detected. The results show that the PCA-based fault detection method is applicable and effective for air-source heat pump water chiller/heater.     

Development and validation of online models with parameter estimation for a building zone with VAV system

The energy consumption by building heating, ventilating, and air conditioning (HVAC) systems has evoked increasing attention to promote energy efficient control and operation of HVAC systems. Application of advanced control and operation strategies requires robust online system models. In this study, online models with parameter estimation for a building zone with a variable air volume system, which is one of the most common HVAC systems, are developed and validated using experimental data. Building zone temperature and zone entering air flow are modeled based on physical rules and only the measurements that are commonly available in a commercial building are used. Various validation experiments were performed using a real-building test facility to examine the prediction accuracies for system outputs. Using the online system models with parameter estimation, the prediction errors for all validation experiments are less than 0.28 °C for temperature outputs, and less than 84.9 m³/h for air flow outputs. The online models can be further used for local and supervisory control, as well as fault detection applications.     

建筑能源管理系统及其在绿色建筑中的应用

对建筑能源管理系统(BEMS)的结构和功能进行阐述,并结合实际工程设计,介绍BEMS在大型公共建筑中的应用。阐明大型公共建筑设置BEMS可以实现绿色建筑高效利用资源、节约能源的目标。     

用参数自整定模型在线检测空气处理机组故障

大型现代建筑大都安装了能源管理与控制系统(EMCS),EMCS系统储存的大量监控数据为空调系统的在线故障检测与诊断提供了方便。提出了一种利用参数自整定空调部件模型在线检测变风量空气处理机组故障的方法。利用遗传算法优化模型参数使模型预测数据与实测值数据的残差最小,因此空调部件模型有较高的预测精度。若模型预测数据与实测数据的残差超出了预先设定的阈值,就意味着变风量空气处理机组可能存在故障。针对在实际应用时确定故障检测阈值的困难,给出了用统计方法确定阈值的方法。故障检测方法在真实建筑中进行了应用和验证,结果表明该故障检测方法可以结合EMCS系统准确有效的检测变风量空气处理机组故障。     

Fault diagnosis of air conditioning systems based on qualitative bond graph

The bond graph method represents a unified approach for modeling engineering systems. The main idea is that power transfer bonds the components of a system. The bond graph model is the same for both quantitative representation, in which parameters have numerical values, and qualitative approach, in which they are classified qualitatively. To infer the cause of faults using a qualitative method, a system of qualitative equations must be solved. However, the characteristics of qualitative operators require specific methods for solving systems of equations having qualitative variables. This paper proposes both a method for recursively solving the qualitative system of equations derived from bond graph, and a bond graph model of a direct-expansion, mechanical vapor–compression air conditioning system. Results from diagnosing two faults in a real air conditioning system are presented and discussed. Occasionally, more than one fault candidate is inferred for the same set of qualitative values derived from measurements. In these cases, additional information is required to localize the fault. Fault diagnosis is initiated by a fault detection mechanism which also classifies the quantitative measurements into qualitative values; the fault detection is not presented here.     

Assessing energy-saving measures in buildings through an intelligent decision support model

Indeed, in the recent years, important efforts in applying energy management processes have been focused on the building sector, which demonstrates the increasing energy intensity and energy consumption indexes. The role of the building energy management systems (BEMS) is known and significant in this respect, for the management of the daily energy operations of a typical building. Effective energy management however requires the use of tools and methodologies that support the strategic decision making process of selecting energy saving measures, which are viable and environmental friendly. The aim of this paper is the presentation of an innovative intelligent decision support model for the identification of the need for intervention and further evaluation of energy saving measures in a typical existing building, based on the systematic incorporation of BEMS data (loads, demands and user requirements). The operation of the model is supportive to the decision makers authorized with the energy-efficient performance of the building and responsible for its management (energy auditors and building administration). In addition, the corresponding computerized decision support system and the appraisal of its pilot application to a typical existing office building in Athens, Greece, are presented and discussed.