Building Energy Performance Analysis Research Articles

Thermal Imaging for Detection of Defects in Envelopes of Buildings in Use: Qualitative and Quantitative Analysis of Building Energy Performance

The proposed interdisciplinary method of identifying defects in the building envelope insulation enables the user to quickly assess the scale of heat loss problems in occupied buildings. The method rests upon the quantitative analysis of macroscopic infrared images of the buildings. The method was applied in practice to assess effects of thermal upgrade project in Dźbów housing estate in Częstochowa, a city located in southern Poland. The results confirmed the applicability of the method to monitoring energy performance of buildings in use without intervention into the building’s fabric and without disturbing the occupants.

Modeling occupancy and behavior for better building design and operation—A critical review

People spend more than 90% of their life time in buildings, which makes occupant behavior one of the leading influences of energy consumption in buildings. Occupancy and occupant behavior, which refer to human presence inside buildings and their active interactions with various building system such as lighting, heating, cooling, ventilation, window blinds, and plugs, attract great attention of research with regard to better building design and operation. Due to the stochastic nature of occupant behavior, prior occupancy models vary dramatically in terms of data sampling, spatial and temporal resolution. This paper provides a comprehensive review of the current modeling efforts of occupant behavior, summarizes occupancy models for various applications including building energy performance analysis, building architectural and engineering design, intelligent building operations and building safety design, and presents challenges and areas where future research could be undertaken. In addition, modeling requirement for different applications is analyzed. Furthermore, a few commonly used statistical and data mining models are presented. The purpose of this paper is to provide a modeling reference for future researchers so that a proper method or model can be selected for a specific research purpose.

A green building information modelling approach: building energy performance analysis and design optimization

This study concerning green BIM focuses on the integrated application of Building Information Modelling (BIM) and building performance analysis (BPA) software as tools for the design and analysis of building projects, and employs a sequential decision-making cycle and continuously improving design to achieve an optimal proposal consistent with environmental effectiveness. Taking a new Taichung hotel construction project energy consumption design optimization as an example, this study relied on the steps of (1) Determination of the scope of discussion of the proposal within the building life cycle, (2) Setting of energy conservation targets, (3) Accessing to external climate data, (4) Entering internal settings, (5) Implementation of energy conservation calculation module, (6) Visualization analysis and hot spot tracking (7) Proposal Revision, and (8) Optimal proposal, to verify the green BIM concept. With regard to the setting of energy conservation targets, this study recommends that building energy use intensity (EUI) be used as an energy load measurement unit of integrated performance indicators, and employs performance optimization percentage as a rating criterion. In accordance with this method, green BIM combined with assessment of green building indicators is as a means of facilitating integrated design and analysis decision-making.

건물 에너지 성능 분석을 위한 로컬 기상 데이터 수집 방안

건물 에너지 성능 분석을 위한 로컬 기상 데이터 수집 방안

Sensitivity analysis of building energy performance: A simulation-based approach using OFAT and variance-based sensitivity analysis methods

In this research, one-factor-at-a-time (OFAT) and variance-based sensitivity analysis methods integrate with EnergyPlus through MATLAB to define predominant variables affecting the energy efficiency of buildings in the early phase of building design. To explore the capabilities of the developed method, it is tested on a typical room model; and the impacts of the design variables, including building orientation, window size, overhang system, and the glazing and walls specifications on the building energy demands are studied in four main weather conditions of Iran. The local and global sensitivity analysis of the annual cooling, heating, lighting and total building electricity are carried out. The results show that for our typical case study, the window size is the prevailing parameter on the annual cooling, heating and total building energy electricity while the glazing visible transmittance has the greatest influence on the annual lighting one in all weather conditions. The developed simulation-based sensitivity analysis method demonstrates a useful tool that aids building energy engineers and decision-makers to concentrate on the most important parameters in the initial stages of planning and promote the building energy efficiency.

Energy performance analysis of an office building in three climate zones

Most of the studies encompassing dynamic simulations of multi-storey buildings account only for a few selected zones, to simplify, decrease simulation run-time and to reduce the complexity of the ‘to be simulated’ model. This conventional method neglects the opportunity to see the interaction between different zones as it relates to whole building performance. This paper presents fifteen individual cases of dynamic simulations of a six-storey office building with 160 zones. The energy performance analysis was conducted for three climate zones including Helsinki in Finland, London in the United Kingdom and Bucharest in Romania. For each location, the following three cases were simulated: (i) building as usual simulated according to valid national building codes; (ii) Energy-efficient (EE) case with selected necessary parameters enhanced to reduce total delivered energy demand; and (iii) nZEB case representing partial enhancement of the EE case based on the parametric analysis. The results of nZEB indicate that for Helsinki, it is possible to reduce the space-heating load by 86%, electricity consumed by lighting, appliance, and HVAC by 32%. For London, the heating load is reduced by 95%, cooling load is slightly increased, and electricity demand is decreased by 33%. For Bucharest, 92% of energy in heating can be saved, cooling energy demand was reduced by 60% and electricity consumption by 34%. Based on the nZEB cases for each location, alternative heating and cooling choices of a radiant floor panel system and radiant ceiling panel system were explored. There are small differences in absolute consumption demand for heating, cooling, and electricity for three cases in each location. The specific energy/m2 for heating remained nearly the same in all systems for all three cases in each location. Alternative choices for heating and cooling by using Radiant Ceiling Panel (RCP) and Radiant Floor Panel (RFP) were investigated for all final nZEB cases. Marginal difference in heating energy required for space heating can be seen for London nZEB IHC and London nZEB RCP of 0.8kWh/m2/year and for Bucharest nZEB IHC and Bucharest nZEB RCP case of 1.3 kWh/m2/year. RFP has the availability of large surface area for heat exchange and can provide heating at a low temperature and cooling at high temperature, but requires supporting air based cooling during the humid season. For RCP, the limited temperature exchange surface may increase the airflow rate, but supplies it at a lower temperature for the same load.

Identifying stakeholders and key performance indicators for district and building energy performance analysis

Integrated energy management at both the district and building scales can potentially improve multi-level energy efficiency, but such a solution requires the exchange and analysis of energy performance information from different stakeholders. With the complexities of energy management, there are numerous potential stakeholders and a considerable amount of information to consider. Therefore, a primary challenge is the development of a method that identifies the key stakeholders and extracts key information that supports their performance goals. In this paper, a systematic approach to identify stakeholders and key performance indicators (KPIs) is proposed to draw key information for multi-level energy performance analysis. Firstly, a three-task method for the identification and prioritization of stakeholders is suggested; secondly, a bi-index method to select the KPIs that underpin the stakeholders’ performance goals is defined; finally, the proposed methodology is validated using a case study. The result demonstrates the feasibility of the methodology and illustrates that the selected KPIs contribute to the attainment of key information required to carry out a multi-level energy performance analysis.

Addressing Large-Scale Energy Retrofit of a Building Stock via Representative Building Samples: Public and Private Perspectives

Scientific literature about energy retrofit focuses on single buildings, but the investigation of whole building stocks is particularly worthy because it can yield substantial energy, environmental and economic benefits. Hence, how to address large-scale energy retrofit of existing building stocks? The paper handles this issue by employing a methodology that provides a robust energy analysis of building categories. This is denoted as SLABE, “Simulation-based Large-scale uncertainty/sensitivity Analysis of Building Energy performance”. It was presented by the same authors and is here enhanced to investigate a whole and heterogeneous building stock that includes various categories. Each category is represented via a Representative Building Sample (RBS), which is defined through Latin hypercube sampling and uncertainty analysis. Hence, optimal retrofit packages are found in function of building location, intended use and construction type. Two families of optimal solutions are achieved. The first one collects the most energy-efficient (and thus sustainable) solutions, among the ones that produce global cost savings, thereby addressing the public perspective. The second one collects cost-optimal solutions thereby addressing the private perspective. EnergyPlus is employed as a simulation tool and coupled with MATLAB® for data analysis and processing. The methodology is applied to a significant share of the Italian public administration building stock, which includes several building categories depending on location, use destination and construction type. The outcomes show huge potential energy and economic savings, and could support a deep energy renovation of the Italian building stock.

Assessment of energy utilization and leakages in buildings with building information model energy

Given the ability of building information models (BIM) to serve as a multidisciplinary data repository, this study attempts to explore and exploit the sustainability value of BIM in delivering buildings that require less energy for operations, emit less carbon dioxide, and provide conducive living environments for occupants. This objective was attained by a critical and extensive literature review that covers the following: (1) building energy consumption, (2) building energy performance and analysis, and (3) BIM and energy assessment. Literature cited in this paper shows that linking an energy analysis tool with a BIM model has helped project design teams to predict and create optimized energy consumption by conducting building energy performance analysis utilizing key performance indicators on average thermal transmitters, resulting heat demand, lighting power, solar heat gains, and ventilation heat losses. An in-depth analysis was conducted on a completed BIM integrated construction project utilizing the Arboleda Project in the Dominican Republic to validate the aforementioned findings. Results show that the BIM-based energy analysis helped the design team attain the world׳s first positive energy building. This study concludes that linking an energy analysis tool with a BIM model helps to expedite the energy analysis process, provide more detailed and accurate results, and deliver energy-efficient buildings. This study further recommends that the adoption of level 2 BIM and BIM integration in energy optimization analysis must be demanded by building regulatory agencies for all projects regardless of procurement method (i.e., government funded or otherwise) or size.

Green BIM-based building energy performance analysis

ABSTRACTIn the face of a rapidly changing climate and global energy crisis, this study proposes the concept of green building information modeling (Green BIM), and suggests the use of a decision-making cycle when performing building performance analysis (BPA) to obtain design proposals with optimized environmental effectiveness in response to local climate conditions when BIM is used as a basic tool from the beginning of the design process.Taking building energy performance analysis as an example, in comparison with other domestic and foreign research, the important contributions of the study include: (1)Based on a design decision-making perspective, a Green BIM-based decision-making cycle can integrate the practical steps of BIM and BPA. (2) Furthermore, this study also finds that meteorological data in a format that can be used in BPA is not easy to obtain. Nevertheless, virtual weather station technology developed using cloud technology can enable a building project to obtain simulated meteorological d...

Temperature and humidity adaptive control in multi-enclosed thermal zones under unexpected external disturbances

In this paper a new dynamic simulation model for the building energy performance analysis of multi-enclosed thermal zones, where rigid air temperature and humidity conditions must be kept, is presented. The model was implemented in a suitable computer code (DETECt 2.3.1) developed for research scopes. Such simulation model allows the hygrothermal analysis of buildings with multi-enclosed thermal zones surrounded by larger ones (e.g. display glass cases with valuable artefacts in museum halls, neonatal intensive care units for premature and full-term newborn babies in hospitals wards, etc.). For this purpose, a novel control algorithm, based on a model reference adaptive control scheme, enabling the online adaptation of the control gains, is implemented. Rigid air temperature and humidity conditions can be guaranteed also in case of sudden and rapid variations of hygrothermal loads. Through such new tool innovative techniques and operative strategies for obtaining energy efficiency and indoor comfort of special building spaces can be studied.In order to show the capabilities of the tool and the robustness of the adaptive algorithm, as well as the potentiality of the proposed multidisciplinary approach to the energy-related behaviour in buildings (based on building energy modelling and simulation and control theory), two meaningful case studies have been developed. In particular, they refer to the museums and hospital indoor spaces where enclosed thermal zones have to be kept under stringent hygrothermal conditions.

Artificial neural networks to predict energy performance and retrofit scenarios for any member of a building category: A novel approach

How to predict building energy performance with low computational times and good reliability? The study answers this question by employing artificial neural networks (ANNs) to assess energy consumption and occupants' thermal comfort for any member of a building category. Two families of ANNs are generated: the first one addresses the existing building stock (as is), the second one addresses the renovated stock in presence of energy retrofit measures (ERMs). The ANNs are generated in MATLAB® by using the outcomes of EnergyPlus simulations as targets for networks' training and testing. A preliminary ‘Simulation-based Large-scale sensitivity/uncertainty Analysis of Building Energy performance’ (SLABE) is conducted to optimize the ANNs' generation. It allows to identify the networks' inputs and to properly select the ERMs. The developed ANNs can replace standard building performance simulation tools, thereby producing a substantial reduction of computational efforts and times. This can allow a wide diffusion of rigorous approaches for retrofit design, which are currently hampered by the excessive computational burden. As case study, office buildings built in South Italy during 1920–1970 are investigated. Comparing the ANNs' predictions with EnergyPlus targets, the regression coefficient is between 0.960 and 0.995 and the average relative error is between 2.0% and 11%.

Energy performance analysis of a dormitory building based on different orientations and seasonal variations of leaf area index

The aim of this research is to investigate the effectiveness of vertical vegetation in terms of energy savings for a residential facility situated at KAIST campus. The research has been established through analyzing different building orientations to find out the most suitable combination of vegetation and orientation for reduced heating and cooling energy consumption. A simulation model has been developed where leaf area index, one of the contributing plant physiological parameters for improving building thermal performance, has been incorporated as per seasonal variations. This allowed observing thermal performance patterns of green wall throughout the year. Approximately 60 % savings in heating energy and 31 % increase in overall energy efficiency were achieved with the non-insulated studied building case, and the results showed extreme weather conditions lead to greater energy savings in winter. In cooling season, plant layers were found to be less effective in terms of facade thermal performance especially during relatively higher temperature period, with an average of 17 % cooling energy savings. The North-oriented green wall was observed to be the most effective in increasing heating energy efficiency, while the East-oriented wall was observed to be greatest in cooling energy savings. A higher LAI value proved to be beneficial in improving both heating and cooling energy performance for the studied building.

A longitudinal building fabric and energy performance analysis of two homes built to different energy principles

This paper reports on the building performance monitoring and annual energy demand of two homes built side-by-side over an occupancy period of three years. The study compares the results from on-site monitoring against the assumed parameters and calculations from compliance modelling at design stage. It focuses on the differences and impact of occupancy behaviour, weather conditions, quality of construction and operation which contribute to an increase in energy consumption creating a gap in performance between design and actual. The results from the study show disparities in the fabric performance reflecting on the overall consumption of energy. This longitudinal analysis highlights how building performance needs to be evaluated over longer periods in order to fully understand how homes and their occupants operate and consume energy. The impact of the real performance of homes in Scotland over longer periods needs to become standardised, and a mechanism for feedback into regulatory mechanisms and construction practices applied, if carbon emission targets are to be met.

Study on Solar Radiation Models in South Korea for Improving Office Building Energy Performance Analysis

Hourly global solar radiation in a weather file is one of the significant parameters for improving building energy performance analyses using simulation programs. However, most weather stations worldwide are not equipped with solar radiation sensors because they tend to be difficult to manage. In South Korea, only twenty-two out of ninety-two weather stations are equipped with sensors, and there are large areas not equipped with any sensors. Thus, solar radiation must often be calculated by reliable solar models. Hence, it is important to find a reliable model that can be applied in the wide variety of weather conditions seen in South Korea. In this study, solar radiation in the southeastern part of South Korea was calculated using three solar models: cloud-cover radiation model (CRM), Zhang and Huang model (ZHM), and meteorological radiation model (MRM). These values were then compared to measured solar radiation data. After that, the calculated solar radiation data from the three solar models were used in a building energy simulation for an office building with various window characteristics conditions, in order to identify how solar radiation differences affect building energy performance. It was found that a seasonal solar model for the area should be developed to improve building energy performance analysis.

Code-to-Code Validation and Application of a Dynamic Simulation Tool for the Building Energy Performance Analysis

In this paper details about the results of a code-to-code validation procedure of an in-house developed building simulation model, called DETECt, are reported. The tool was developed for research purposes in order to carry out dynamic building energy performance and parametric analyses by taking into account new building envelope integrated technologies, novel construction materials and innovative energy saving strategies. The reliability and accuracy of DETECt was appropriately tested by means of the standard BESTEST validation procedure. In the paper, details of this validation process are accurately described. A good agreement between the obtained results and all the reference data of the BESTEST qualification cases is achieved. In particular, the obtained results vs. standard BESTEST output are always within the provided ranges of confidence. In addition, several test cases output obtained by DETECt (e.g., dynamic profiles of indoor air and building surfaces temperature and heat fluxes and spatial trends of temperature across walls) are provided.

Dynamic building energy performance analysis: A new adaptive control strategy for stringent thermohygrometric indoor air requirements

In this paper a novel optimal Model Reference Adaptive Control approach, developed to tame the thermohygrometric behaviour of buildings as well as to guarantee the indoor comfort, is presented. The main advantages of the proposed method are: (i) no-need of a priori knowledge of the specific building dynamics due to climate, occupants’ behaviour, building use, envelope features and utility rates; (ii) robustness with respect to a large class of perturbations, external disturbances, nonlinear unmodelled dynamics or parameters uncertainty; (iii) ability to impose desired optimal dynamics; (iv) accurate regulation and fast tracking of indoor air temperature and humidity in the case of stringent requirements in special building spaces (e.g. hospitals, museums, laboratories, etc.).In order to investigate the effectiveness of the proposed method, the developed strategy has been implemented in the new release of a white-modelling building energy performance simulation code, called DETECt 2.3. The tool enables multi-zone building simulation analyses and is capable to dynamically predict: (i) spaces sensible and latent heating and cooling demands and loads; (ii) indoor air temperatures and humidity, as well as building envelope internal and external temperatures; (iii) the performance of phase change materials (PCM) embedded in building enclosures and for any layer configuration; (iv) the thermohygrometric comfort of occupants.In order to analyse the effectiveness and robustness of the proposed control strategy, several case studies have been carried out. They refer to some reference buildings with different geometry, use and construction materials (also including PCM integrated into the building envelope) simulated in different weather conditions. For each case study, both continuous and intermittent control system regimes have been considered. Results confirm the ability of the developed approach to achieve the selected indoor air temperature and humidity conditions in order to guarantee indoor comfort in uncertain conditions. The numerical analysis is complemented with the rigorous analytical proof of asymptotic stability.

Modelling of Thermo-optical Properties of Amorphous and Microcrystalline Silicon Semitransparent PV Layer

Nowadays, one of the most promising renewable energy technology is based on photovoltaic conversion of solar energy. Application of PV systems integrated with building envelope allows electricity to be utilized on site for any functional needs. Building integrated photovoltaic (BIPV) is commonly used in representative, office buildings usually occupied during the day. The large surface area of external walls or roofs is covered with PV panels instead of traditional building materials. In highly glazed buildings, transparent elements are more often being equipped with PV cells placed between two sheets of glass. Moreover, brand new technologies focus currently on homogenous, transparent glass with different transparency.The main aim of the presented study was to analyse transparent PV (TPV) integrated with office windows. The following 10%, 20% or 30% of transparency degree were considered, depending on the required illuminance inside the room. The optical properties were obtained on the basis of literature review and manufactured data. Different types of TPV were defined for the purpose of building energy performance analysis. Numerical model was developed using control volume method. The properties of TPV glass layer were estimated considering thermo- electrical solar energy conversion, taking into account the sun beam angle and temperature of thepanel.The model of single office room with TPV windowpane was analysed numerically. Results obtained for different TPV panels were compared with traditional clear float double glazing. The following two building energy performance parameters were obtained from numerical analysis: electricity produced by TPV and solar heat gains. Based on simulation results, the overall yearly energy performance was presented and compared.

Review Article: Significant Parameters in Building Energy Simulation

A simulation model has been widely used to investigate and predict the energy performance of buildings. However, to achieve more accurate energy result, the input data in the simulation model should be obtained from field measurements. Collecting field measurements is a very time intensive activity. With this limitation, in this work we summarized results of parameters most influential on energy results from 44 papers performing energy simulation model for determining the potential of energy saving and improving the model accuracy in various building types including offices, single rooms, homes, multi-family buildings, and other commercial buildings. It is found that the parameters with influence on energy performance were dissimilar to the parameter that the modelers used for adjusting the model accuracy and determining energy saving. Set point temperature had a large impact on energy results for office and home, while shading and occupancy schedule significantly impacted the energy results for multi-family building and other commercial buildings, respectively. At present, the number of sensitivity analysis related to building energy performance is limited. Future studies should increase a number of sensitivity analysis of building energy performance for different building types.

A new methodology for investigating the cost-optimality of energy retrofitting a building category

According to the Energy Performance of Buildings Directive (EPBD) Recast, building energy retrofitting should aim “to achieving cost-optimal levels”. However, the detection of cost-optimal levels for an entire building stock is a complex task. This paper tackles such issue by introducing a novel methodology, aimed at supporting robust cost-optimal energy retrofit solutions for building categories. Since the members of one building category provide highly different energy performance, they cannot be correctly represented by only one reference design as stipulated by the EPBD Recast. Therefore, a representative building sample (RBS) is here used to consider potential variations in all parameters affecting energy performance. Simulation-based uncertainty analysis is employed to identify the optimal RBS size, followed by simulation-based sensitivity analysis to identify proper retrofit actions. Then post-processing is performed to investigate the cost-effectiveness of all possible retrofit packages including energy-efficient HVAC systems, renewables, and energy saving measures. The methodology is denoted as SLABE, ‘Simulation-based Large-scale uncertainty/sensitivity Analysis of Building Energy performance’. It employs EnergyPlus and MATLAB®. For demonstration, SLABE is applied to office buildings built in South Italy during 1920–1970. The results show that the cost-optimal retrofit package includes the installation of condensing gas boiler, water-cooled chiller and full-roof photovoltaic system.