Energies

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17 pages, 2053 KiB

Open AccessArticle

Estimation of the Heat Loss Coefficient of Two Occupied Residential Buildings through an Average Method

by Irati Uriarte, Aitor Erkoreka, Pablo Eguia, Enrique Granada and Koldo Martin-Escudero

Energies 2020, 13(21), 5724; https://doi.org/10.3390/en13215724 - 2 Nov 2020

Cited by 8 | Viewed by 2495

The existing performance gap between the design and the real energy consumption of a building could have three main origins: the occupants’ behaviour, the performance of the energy systems and the performance of the building envelope. Through the estimation of the in-use Heat [...] Read more.

The existing performance gap between the design and the real energy consumption of a building could have three main origins: the occupants’ behaviour, the performance of the energy systems and the performance of the building envelope. Through the estimation of the in-use Heat Loss Coefficient (HLC), it is possible to characterise the building’s envelope energy performance under occupied conditions. In this research, the estimation of the HLC of two individual residential buildings located in Gainsborough and Loughborough (UK) was carried out using an average method. This average method was developed and successfully tested in previous research for an occupied four-story office building with very different characteristics to individual residential buildings. Furthermore, one of the analysed residential buildings is a new, well-insulated building, while the other represents the old, poorly insulated semidetached residential building typology. Thus, the monitored data provided were filtered in order to apply the abovementioned average method. Even without fulfilling all the average method requirements for these two residential buildings, the method provides reliable HLC values for both residential buildings. For the house in Gainsborough, the best estimated HLC value was 60.2 W/K, while the best approach for Loughborough was 366.6 W/K. Thus, despite the uncertainty sources found during the analysis, the method seems promising for its application to residential buildings. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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30 pages, 6792 KiB

Open AccessArticle

Data-Based RC Dynamic Modelling to Assessing the In-Situ Thermal Performance of Buildings. Analysis of Several Key Aspects in a Simplified Reference Case toward the Application at On-Board Monitoring Level

by Yessenia Olazo-Gómez, Héctor Herrada, Sergio Castaño, Jesús Arce, Jesús P. Xamán and María José Jiménez

Energies 2020, 13(18), 4800; https://doi.org/10.3390/en13184800 - 14 Sep 2020

Cited by 5 | Viewed by 2157

Abstract

This paper reports the application of RC dynamic models for assessing thermal performance of buildings from in-situ tests (obtaining the U value for the walls, and the UA value and gA value for the whole buildings). The following aspects which are relevant to [...] Read more.

This paper reports the application of RC dynamic models for assessing thermal performance of buildings from in-situ tests (obtaining the U value for the walls, and the UA value and gA value for the whole buildings). The following aspects which are relevant to this approach have been systematically analyzed: The effect of the solar radiation on the heat flux through the opaque walls versus the performance of the models including this effect, the optimum number of nodes required to represent the thermal systems, the assignment of inputs and outputs and the length of the test period. Additionally, several options modelling relevant effects using unmeasured variables were studied to evaluate the feasibility to reduce the cost and intrusiveness of the measurement devices required to obtain accurate results. Data series recorded under different experimental conditions were considered to analyze the robustness and validity of the results. The performance of the models for each of these different test conditions is discussed. The uncertainties estimated using the described method for the U values of the opaque walls, and the UA and gA values of the whole building, are, respectively, 2.8%, 4.2% and 2.3%. The feasibility to model relevant effects using unmeasured variables has been demonstrated. A simplified and well-known building has been used as a case study, reinforcing and complementing the validation criteria. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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23 pages, 1204 KiB

Open AccessArticle

Method for Scalable and Automatised Thermal Building Performance Documentation and Screening

by Christoffer Rasmussen, Peder Bacher, Davide Calì, Henrik Aalborg Nielsen and Henrik Madsen

Energies 2020, 13(15), 3866; https://doi.org/10.3390/en13153866 - 28 Jul 2020

Cited by 19 | Viewed by 2948

Abstract

In Europe, more and more data on building energy use will be collected in the future as a result of the energy performance of buildings directive (EPBD), issued by the European Union. Moreover, both at European level and globally it became evident that [...] Read more.

In Europe, more and more data on building energy use will be collected in the future as a result of the energy performance of buildings directive (EPBD), issued by the European Union. Moreover, both at European level and globally it became evident that the real energy performance of new buildings and the existing building stock needs to be documented better. Such documentation can, for example, be done with data-driven methods based on mathematical and statistical approaches. Even though the methods to extract energy performance characteristics of buildings are numerous, they are of varying reliability and often associated with a significant amount of human labour, making them hard to apply on a large scale. A classical approach to identify certain thermal performance parameters is the energy signature method. In this study, an automatised, nonlinear and smooth approach to the well-known energy signature is proposed, to quantify key thermal building performance parameters. The research specifically aims at describing the linear and nonlinear heat usage dependency on outdoor temperature, wind and solar irradiation. To make the model scalable, we realised it so that it only needs the daily average heat use of buildings, the outdoor temperature, the wind speed and the global solar irradiation. The results of applying the proposed method on heat consumption data from 16 different and randomly selected Danish occupied houses are analysed. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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17 pages, 4793 KiB

Open AccessArticle

Error Analysis of QUB Method in Non-Ideal Conditions during the Experiment

by Naveed Ahmad, Christian Ghiaus and Moomal Qureshi

Energies 2020, 13(13), 3398; https://doi.org/10.3390/en13133398 - 2 Jul 2020

Cited by 4 | Viewed by 1894

Abstract

Overall heat transfer coefficient, also known as the intrinsic performance measurement of the building, determines the amount of heat lost by a building due to temperature difference between indoor and outdoor. QUB (Quick U-value of Buildings) is a short-term method for measuring the [...] Read more.

Overall heat transfer coefficient, also known as the intrinsic performance measurement of the building, determines the amount of heat lost by a building due to temperature difference between indoor and outdoor. QUB (Quick U-value of Buildings) is a short-term method for measuring the overall heat transfer coefficient of buildings. The test involves heating and cooling the house with a power step and measuring the indoor temperature response in a single night. Ideally, the outdoor temperature during QUB experiment should remain constant. To compare the influence of variable outdoor temperature, the QUB experiments are simulated on a well-calibrated model with real weather conditions. The experiments at varying outdoor temperature and constant outdoor temperature during the night show that the results in both conditions are nearly similar. A ±2 °C increase or decrease in the outdoor temperature during the QUB experiment can change the results in the measured overall heat transfer coefficient by ±5%. QUB experiments simulated during the months of winter show that the majority of results are ±15% of the steady-state overall heat transfer coefficient. The QUB results during the months of summer show relatively large variation. The large errors coincide with the small temperature difference between indoor and outdoor temperatures before the start of QUB experiment. The median error of multiple QUB experiments during summer can be reduced by increasing the setpoint temperature before the start of QUB experiment. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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16 pages, 7493 KiB

Open AccessArticle

Measurements and Simulation Study of Daylight Availability and Its Impact on the Heating, Cooling and Lighting Energy Demand in an Educational Building

by Joanna Rucińska and Adrian Trząski

Energies 2020, 13(10), 2555; https://doi.org/10.3390/en13102555 - 18 May 2020

Cited by 15 | Viewed by 3311

Abstract

This paper deals with the impact of the use of daylight on the overall energy demand for heating, cooling, and lighting in educational buildings. The energy performance of buildings is currently of the utmost importance as current European regulations, starting from 31st December [...] Read more.

This paper deals with the impact of the use of daylight on the overall energy demand for heating, cooling, and lighting in educational buildings. The energy performance of buildings is currently of the utmost importance as current European regulations, starting from 31st December 2020 impose that all new buildings must meet nearly zero-energy building requirements. This paper presents a study of the illuminance distribution in an educational room obtained from measurements and simulation results using two different models. One of the models, integrated with a thermal simulation software, was used to estimate the impact of daylight on the energy demand. The analysis included the use of various window types, lighting control system, reference point location, and daylight calculation model for a sample room in an educational building. Results of the analysis indicate that, due to the high share of lighting demand (reaching up to 78% of the primary energy balance), there is a need to take into account the efficiency of lighting systems during the design process to correctly determine the actual energy balance of a building, increase the quality of the design of lighting systems, as well as to select the optimal parameters of windows. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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28 pages, 5896 KiB

Open AccessArticle

Identification of the Building Envelope Performance of a Residential Building: A Case Study

by Evi Lambie and Dirk Saelens

Energies 2020, 13(10), 2469; https://doi.org/10.3390/en13102469 - 14 May 2020

Cited by 13 | Viewed by 3384

Abstract

Since households are one of the most energy-intensive sectors in Europe, retrofit of dwellings is promoted to increase energy efficiency. Recent research, however, shows that the energy performance after retrofit does not always meet the target values, which can be caused by amongst [...] Read more.

Since households are one of the most energy-intensive sectors in Europe, retrofit of dwellings is promoted to increase energy efficiency. Recent research, however, shows that the energy performance after retrofit does not always meet the target values, which can be caused by amongst other things, a deviating building envelope performance. This paper compares the theoretical and measured building envelope performance for a real-life case study in post-retrofit state, in order to illustrate the limitations of calculation methods and characterization models. First, the performance is evaluated on building scale by verifying the correspondence between the default theoretical heat loss coefficient (HLC) and the measured HLC, which was determined by following the guidelines formulated within IEA EBC Annex 58 and Annex 71. In order to illustrate the limitations of the standard calculation method in real-life conditions, the theoretical variability of the HLC is evaluated, generated by variating infiltration heat losses and heat exchange with neighboring dwellings. Second, the performance is investigated on a component scale by assessing the theoretical and measured thermal resistances, identified from heat flux tests. Additionally, nonhomogeneous assembled components and air leaks are simulated to verify probable causes for the locally varying measured values and to illustrate the limitations of calculations and characterization methods. The results illustrate the limitations of the calculation methods by the assessment of the strong variability of the theoretical HLC, depending on assumptions regarding infiltration and heat exchange with neighboring dwellings. In addition, component simulations indicated that deficiencies on a component scale could be caused by a nonhomogeneous assembly and air cavity flows of the component. Moreover, a detailed assessment of an unreliable thermal resistance illustrates the limitations of the used characterization method. Finally, a contrast was found between the quite good performance on building scale (15% deviation between the theoretical and measured HLC) and poor performance on a component scale (only one out of nine monitored components met their theoretical target values), which illustrates the complexity of the building envelope performance. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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27 pages, 6158 KiB

Open AccessArticle

The Performance Gap in Energy-Efficient Office Buildings: How the Occupants Can Help?

by Qadeer Ali, Muhammad Jamaluddin Thaheem, Fahim Ullah and Samad M. E. Sepasgozar

Energies 2020, 13(6), 1480; https://doi.org/10.3390/en13061480 - 20 Mar 2020

Cited by 36 | Viewed by 6005

Abstract

Rising demand and limited production of electricity are instrumental in spreading the awareness of cautious energy use, leading to the global demand for energy-efficient buildings. This compels the construction industry to smartly design and effectively construct these buildings to ensure energy performance as [...] Read more.

Rising demand and limited production of electricity are instrumental in spreading the awareness of cautious energy use, leading to the global demand for energy-efficient buildings. This compels the construction industry to smartly design and effectively construct these buildings to ensure energy performance as per design expectations. However, the research tells a different tale: energy-efficient buildings have performance issues. Among several reasons behind the energy performance gap, occupant behavior is critical. The occupant behavior is dynamic and changes over time under formal and informal influences, but the traditional energy simulation programs assume it as static throughout the occupancy. Effective behavioral interventions can lead to optimized energy use. To find out the energy-saving potential based on simulated modified behavior, this study gathers primary building and occupant data from three energy-efficient office buildings in major cities of Pakistan and categorizes the occupants into high, medium, and low energy consumers. Additionally, agent-based modeling simulates the change in occupant behavior under the direct and indirect interventions over a three-year period. Finally, energy savings are quantified to highlight a 25.4% potential over the simulation period. This is a unique attempt at quantifying the potential impact on energy usage due to behavior modification which will help facility managers to plan and execute necessary interventions and software experts to develop effective tools to model the dynamic usage behavior. This will also help policymakers in devising subtle but effective behavior training strategies to reduce energy usage. Such behavioral retrofitting comes at a much lower cost than the physical or technological retrofit options to achieve the same purpose and this study establishes the foundation for it. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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22 pages, 6820 KiB

Open AccessArticle

Data-Based RC Dynamic Modelling Incorporating Physical Criteria to Obtain the HLC of In-Use Buildings: Application to a Case Study

by Heidi Paola Díaz-Hernández, Pablo René Torres-Hernández, Karla María Aguilar-Castro, Edgar Vicente Macias-Melo and María José Jiménez

Energies 2020, 13(2), 313; https://doi.org/10.3390/en13020313 - 8 Jan 2020

Cited by 8 | Viewed by 2300

Abstract

This paper reports the application of RC dynamic models (network of resistances and capacitances analogous to electrical networks) to obtain the heat loss coefficient (HLC) from a dynamic test campaign carried out in an in-use building. It is a well-insulated building located in [...] Read more.

This paper reports the application of RC dynamic models (network of resistances and capacitances analogous to electrical networks) to obtain the heat loss coefficient (HLC) from a dynamic test campaign carried out in an in-use building. It is a well-insulated building located in Gainsborough, U.K. This case study and data were made available to participants in the IEA–EBC Annex 71 project Building Energy Performance Assessment Based on In-Situ Measurements. The analysis reported in this paper is mainly focused on the identification of the main heat transfer contributions and also on the translation of these phenomena to the RC models used to obtain the required HLC. First pre-processing and qualitative analysis were carried out. Afterwards several candidate models were constructed according to different plausible assumptions and approximations. The validity of the results obtained using these models has been evaluated taking into account the agreement among different data series and also the levels of the residuals obtained using the different models. The work concludes obtaining accurate estimates of the HLC from the energy balance including the following relevant contributions: space heating, solar gains, internal gains due to appliances, and internal gains due to metabolic activity. These terms were modelled using the following driving variables: consumption of gas and water, electricity production by the photovoltaic (PV) panels and electricity consumption (modelling internal gains due to appliances and occupancy patterns). Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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24 pages, 5273 KiB

Open AccessFeature PaperArticle

Influence of Initial and Boundary Conditions on the Accuracy of the QUB Method to Determine the Overall Heat Loss Coefficient of a Building

by Naveed Ahmad, Christian Ghiaus and Thimothée Thiery

Energies 2020, 13(1), 284; https://doi.org/10.3390/en13010284 - 6 Jan 2020

Cited by 16 | Viewed by 3563

Abstract

The quick U-building (QUB) method is used to measure the overall heat loss coefficient of buildings during one to two nights by applying heating power and by measuring the indoor and the outdoor temperatures. In this paper, the numerical model of a real [...] Read more.

The quick U-building (QUB) method is used to measure the overall heat loss coefficient of buildings during one to two nights by applying heating power and by measuring the indoor and the outdoor temperatures. In this paper, the numerical model of a real house, previously validated on experimental data, is used to conduct several numerical QUB experiments. The results show that, to some extent, the accuracy of QUB method depends on the boundary conditions (solar radiation), initial conditions (initial power and temperature distribution in the walls) and on the design of QUB experiment (heating power and duration). QUB method shows robustness to variation in the value of the overall heat loss coefficient for which the experiment was designed and in the variation of optimum power for the QUB experiments. The variations in the QUB method results are smaller on cloudy than on sunny days, the error being reduced from about 10% to about 7%. A correction is proposed for the solar radiation absorbed by the wall that contributes to the evolution of air temperature during the heating phase. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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21 pages, 3036 KiB

Open AccessArticle

How Climate Trends Impact on the Thermal Performance of a Typical Residential Building in Madrid

by S. Soutullo, E. Giancola, M. J. Jiménez, J. A. Ferrer and M. N. Sánchez

Energies 2020, 13(1), 237; https://doi.org/10.3390/en13010237 - 3 Jan 2020

Cited by 22 | Viewed by 4494

Abstract

Based on the European energy directives, the building sector has to provide comfortable levels for occupants with minimum energy consumption as well as to reduce greenhouse gas emissions. This paper aims to compare the impact of climate change on the energy performance of [...] Read more.

Based on the European energy directives, the building sector has to provide comfortable levels for occupants with minimum energy consumption as well as to reduce greenhouse gas emissions. This paper aims to compare the impact of climate change on the energy performance of residential buildings in order to derive potential design strategies. Different climate file inputs of Madrid have been used to quantify comparatively the thermal needs of two reference residential buildings located in this city. One of them represents buildings older than 40 years built according to the applicable Spanish regulations prior to 1979. The other refers to buildings erected in the last decade under more energy-restrictive constructive regulations. Three different climate databases of Madrid have been used to assess the impact of the evolution of the climate in recent years on the thermal demands of these two reference buildings. Two of them are typical meteorological years (TMY) derived from weather data measured before 2000. On the contrary, the third one is an experimental file representing the average values of the meteorological variables registered in Madrid during the last decade. Annual and monthly comparisons are done between the three climate databases assessing the climate changes. Compared to the TMYs databases, the experimental one records an average air temperature of 1.8 °C higher and an average value of relative humidity that is 9% lower. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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16 pages, 9539 KiB

Open AccessArticle

Experimental Validation of a Numerical Model of a Ventilated Façade with Horizontal and Vertical Open Joints

by María Nuria Sánchez, Emanuela Giancola, Eduardo Blanco, Silvia Soutullo and María José Suárez

Energies 2020, 13(1), 146; https://doi.org/10.3390/en13010146 - 27 Dec 2019

Cited by 23 | Viewed by 3734

Abstract

Commercial and residential building is one of the four major final energy consumption and end-use sectors. In this sector, cooling loads represent an important part of the energy consumption, and therefore, they must be minimized, improving the energy efficiency of buildings. Ventilated façades [...] Read more.

Commercial and residential building is one of the four major final energy consumption and end-use sectors. In this sector, cooling loads represent an important part of the energy consumption, and therefore, they must be minimized, improving the energy efficiency of buildings. Ventilated façades are one of the most widely used passive elements that are integrated into buildings, precisely with the aim of reducing these loads. This reduction is due to the airflow induced in the air cavity by the buoyancy forces, when the solar radiation heats the outer layer of the façade. In the open joint ventilated facades (OJVF), ventilation is attained through the open joints between the panels composing the outer layer. Despite the steadily growing research in the characterization of this type of system, few studies combine the numerical modelling of OJVF with experimental results for the assessment of the airflow in the ventilated cavities. This paper experimentally validates a numerical simulation model of an OJVF. Firstly, the façade performance has been experimentally assessed in a laboratory model determining the temperatures in the panels and air gap and measuring the flow field at the gap using particle image velocimetry (PIV) techniques. Secondly, a numerical model has been developed using advanced Computational Fluid Dynamics (CFD) simulation tools. Finally, an experimental validation of the numerical model has been done. Experimental and numerical results are compared in different planes inside the ventilated cavity. The discrete ordinates (DO) radiation model and the k-ε renormalisation group (RNG) turbulence model better adjust the simulated results to the experimental ones. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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28 pages, 1516 KiB

Open AccessArticle

Bayesian Calibration with Augmented Stochastic State-Space Models of District-Heated Multifamily Buildings

by Lukas Lundström and Jan Akander

Energies 2020, 13(1), 76; https://doi.org/10.3390/en13010076 - 22 Dec 2019

Cited by 7 | Viewed by 3130

Abstract

Reliable energy models are needed to determine building energy performance. Relatively detailed energy models can be auto-generated based on 3D shape representations of existing buildings. However, parameters describing thermal performance of the building fabric, the technical systems, and occupant behavior are usually not [...] Read more.

Reliable energy models are needed to determine building energy performance. Relatively detailed energy models can be auto-generated based on 3D shape representations of existing buildings. However, parameters describing thermal performance of the building fabric, the technical systems, and occupant behavior are usually not readily available. Calibration with on-site measurements is needed to obtain reliable energy models that can offer insight into buildings’ actual energy performances. Here, we present an energy model that is suitable for district-heated multifamily buildings, based on a 14-node thermal network implementation of the ISO 52016-1:2017 standard. To better account for modeling approximations and noisy inputs, the model is converted to a stochastic state-space model and augmented with four additional disturbance state variables. Uncertainty models are developed for the inputs solar heat gains, internal heat gains, and domestic hot water use. An iterated extended Kalman filtering algorithm is employed to enable nonlinear state estimation. A Bayesian calibration procedure is employed to enable assessment of parameter uncertainty and incorporation of regulating prior knowledge. A case study is presented to evaluate the performance of the developed framework: parameter estimation with both dynamic Hamiltonian Monte Carlo sampling and penalized maximum likelihood estimation, the behavior of the filtering algorithm, the impact of different commonly occurring data sources for domestic hot water use, and the impact of indoor air temperature readings. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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29 pages, 4341 KiB

Open AccessEditor’s ChoiceArticle

Sensitivity of Characterizing the Heat Loss Coefficient through On-Board Monitoring: A Case Study Analysis

by Marieline Senave, Staf Roels, Stijn Verbeke, Evi Lambie and Dirk Saelens

Energies 2019, 12(17), 3322; https://doi.org/10.3390/en12173322 - 28 Aug 2019

Cited by 14 | Viewed by 3016

Abstract

Recently, there has been an increasing interest in the development of an approach to characterize the as-built heat loss coefficient (HLC) of buildings based on a combination of on-board monitoring (OBM) and data-driven modeling. OBM is hereby defined as the monitoring of the [...] Read more.

Recently, there has been an increasing interest in the development of an approach to characterize the as-built heat loss coefficient (HLC) of buildings based on a combination of on-board monitoring (OBM) and data-driven modeling. OBM is hereby defined as the monitoring of the energy consumption and interior climate of in-use buildings via non-intrusive sensors. The main challenge faced by researchers is the identification of the required input data and the appropriate data analysis techniques to assess the HLC of specific building types, with a certain degree of accuracy and/or within a budget constraint. A wide range of characterization techniques can be imagined, going from simplified steady-state models applied to smart energy meter data, to advanced dynamic analysis models identified on full OBM data sets that are further enriched with geometric info, survey results, or on-site inspections. This paper evaluates the extent to which these techniques result in different HLC estimates. To this end, it performs a sensitivity analysis of the characterization outcome for a case study dwelling. Thirty-five unique input data packages are defined using a tree structure. Subsequently, four different data analysis methods are applied on these sets: the steady-state average, Linear Regression and Energy Signature method, and the dynamic AutoRegressive with eXogenous input model (ARX). In addition to the sensitivity analysis, the paper compares the HLC values determined via OBM characterization to the theoretically calculated value, and explores the factors contributing to the observed discrepancies. The results demonstrate that deviations up to 26.9% can occur on the characterized as-built HLC, depending on the amount of monitoring data and prior information used to establish the interior temperature of the dwelling. The approach used to represent the internal and solar heat gains also proves to have a significant influence on the HLC estimate. The impact of the selected input data is higher than that of the applied data analysis method. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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22 pages, 3052 KiB

Open AccessArticle

Advancing Building Fault Diagnosis Using the Concept of Contextual and Heterogeneous Test

by Mahendra Singh, Nguyen Trung Kien, Houda Najeh, Stéphane Ploix and Antoine Caucheteux

Energies 2019, 12(13), 2510; https://doi.org/10.3390/en12132510 - 29 Jun 2019

Cited by 5 | Viewed by 2884

Abstract

Fault diagnosis and maintenance of a whole-building system is a complex task to perform. A wide range of available building fault detection and diagnosis (FDD) tools are only capable of performing fault detection using behavioral constraints analysis. However, the validity of the detected [...] Read more.

Fault diagnosis and maintenance of a whole-building system is a complex task to perform. A wide range of available building fault detection and diagnosis (FDD) tools are only capable of performing fault detection using behavioral constraints analysis. However, the validity of the detected symptom is always questionable. In this work, we introduce the concept of the contextual test with validity constraints, in the context of building fault diagnostics. Thanks to a common formalization of the proposed heterogeneous tests, rule-, range-, and model-based tests can be combined in the same diagnostic analysis that reduces the whole-building modeling effort. The proposed methodology comprises the minimum diagnostic explanation feature that can significantly improve the knowledge of the building facility manager. A bridge diagnosis approach is used to describe the multiple fault scenarios. The proposed methodology is validated on an experimental building called the center for studies and design of prototypes (CECP) building located in Angers, France. Full article

(This article belongs to the Special Issue Building Energy Performance Measurement and Analysis)

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