Search

In recent years many types of radiant systems have been installed in buildings. Meanwhile, practitioners debate on which thermal inertia of radiant systems fit better and which control strategies should be better in buildings, depending on the insulation level and thermal inertia of the structures. In particular, in new and retrofitted buildings, where the envelope presents high levels of insulation, it is argued if it is better to have low or high inertia radiant systems for controlling the indoor operative temperature and avoid overheating, especially in mid-seasons when the outdoor temperature is mild and solar radiation is high. For this purpose a room with three types of insulation level has been analysed combining different types of structures (masonry, and light and timber walls) and three types of radiant systems (classic wet floor, dry floor, and ceiling). Two operation modes have been simulated: fixed supply temperature and variable temperature according to the outdoor temperature. The results looked at the embedded and control efficiency, the energy performance in case of coupling with a water to water heat pump and the long-term possible overheating analysis. The embedded and control efficiency in dynamic conditions has been evaluated and compared with different possible definitions, in particular with steady state conditions, former EN15316-2-2007, and current EN15316-2-2017. New values for the current standard are suggested based on the results of this work, since the former and existing values overestimate the seasonal losses of floor and radiant systems in heating conditions. The paper shows that working at variable temperature according to the outdoor air temperature leads to longer operation time. The temperature, on average, lowers, and coupling the radiant system with a water to water heat pump leads to lower consumptions in the case of variable supply temperature compared to fixed supply temperature over the season. The seasonal coefficient of performance of the whole system, i.e. the heat pump and auxiliary pumps, leads to overall lower energy consumption in the case of variable supply temperature. The simulations did not show any relevant problem of discomfort from December to February. Overtemperature effects in terms of operative temperatures over the dead band of the control systems are not especially due to the radiant system, but they also occur in any case with ideal convective systems. The paper demonstrates that in general the radiant floor systems perform better than radiant ceilings in heating conditions and there is no evidence that dry floor systems perform better than wet screed systems in all the types of buildings regardless of the level of insulation and thermal inertia. [ABSTRACT FROM AUTHOR]

User behaviour influences the energy consumption of domestic properties with different range of variations and this has an effect on the results of building simulations based on default or general values, as opposed to implementing user behaviour. The aim of this paper is to evaluate and quantify the effect of implementing user behaviour in building dynamic simulation to calculate heating and domestic how water energy consumption to reduce the performance gap. The results for space heating and domestic hot water from dynamic building simulations will be compare to actual energy bills for a general building simulation technique and a calibrated building simulation, incorporating user behaviour details. By using user behaviour details to create calibrated building simulations, a correlation to actual energy bills of over 90 % can be achieved for a dataset of 22 properties. This study has shown that by incorporating user behaviour into building simulations, a more accurate estimation of energy consumption can be achieved. More importantly, the methodology approach allows the user behaviour parameters to be collected by means of a questionnaire, providing an easy and low budget approach to incorporate user behaviour into dynamic building simulations to reduce the performance. [ABSTRACT FROM AUTHOR]

This paper provides practical guidelines to the Bayesian calibration of building energy models using the probabilistic programming language Stan. While previous studies showed the applicability of the calibration method to building simulation, its practicality is still impeded by its complexity and the need to specify a whole range of information due to its Bayesian nature. We ease the reader into the practical application of Bayesian calibration to building energy models by providing the corresponding code and user guidelines with this paper. Using a case study, we demonstrate the application of Kennedy and O’Hagan’s (KOH) [1] Bayesian calibration framework to an EnergyPlus whole building energy model. The case study is used to analyze the sensitivity of the posterior distributions to the number of calibration parameters. The study also looks into the influence of prior specification on the resulting (1) posterior distributions; (2) calibrated predictions; and (3) model inadequacy that is revealed by a discrepancy between the observed data and the model predictions. Results from the case study suggest that over-parameterization can result in a significant loss of posterior precision. Additionally, using strong prior information for the calibration parameters may dominate any influence from the data leading to poor posterior inference of the calibration parameters. Lastly, this study shows that it may be misleading to assume that the posteriors of the calibration parameters are representative of their true values and their associated uncertainty simply because the calibrated predictions matches the measured output well. [ABSTRACT FROM AUTHOR]

At present, dynamic simulation and analysis on building thermal environment and energy consumption achieved by computer software become a reality. However, it is found that defined gaps exist between simulation and on-site measurement. To explore the gaps, this paper takes typical air-conditioned university dormitories located in Chongqing as a case study. Simultaneously, the gaps are explored with a DeST-h building energy simulation model and on-site measurement. Indicators including indoor temperature, relative humidity and air conditioning energy consumption under different setting temperature are simulated and measured. Then, a comparison between simulation results and measured data is explored as well as the cause of these gaps. This paper studies thermal environment and energy consumption by combining on-site measurement and numerical simulation, and the conclusion is that the gaps can from occupant behaviour and physical parameters of the indoor and outdoor environment, which provides a reference for thermal environment of the dormitory and building simulation. [ABSTRACT FROM AUTHOR]

Historical and heritage (especially UNESCO) buildings need a specific, peculiar approach regarding energy performance, energy behavior, and indoor microclimate. Comparing a new building with a historical (UNESCO) building, it is evident that the degrees of freedom for implementing energy efficiency in historical buildings are strongly limited. Several constraints about the materials, the geometry, and the structures do not allow a comprehensive enhancement of energy performance or microclimate parameters. In this paper, we describe an energy building performance criterion adopted in order to find out the energy behavior in the Malatestiana Library. The challenge consists of optimizing energy efficiency and microclimate as well as a full preservation of ancient manuscripts. The study adopts Google Sketchup software to model three-dimensional (3D) buildings, and IESVE software to simulate an indoor microclimate. Software building models allow for the evaluation of different types of natural ventilation and section forms, e.g., original, without attic, and without ground floor. The results of the software modeling allow for a comparison of several building use modality effects and the effect of the presence of an attic and ground floor on indoor microclimate parameters in order to conserve and preserve ancient manuscripts. [ABSTRACT FROM AUTHOR]

Uncertainty Quantification (UQ) employing a Monte Carlo Sampling (MCS) method in a building simulation domain has been widely used to account for risks of predicted outputs for robust decision making. However, the stochastic approach for UQ problems requires significant computational burdens compared to the deterministic approach. This paper addresses two surrogate models (Gaussian Process Emulator (GPE) and Polynomial Chaos Expansion (PCE)) which together can be regarded as a meta-model of a Building Performance Simulation (BPS) tool with a high-fidelity model. In the paper, the developed GPE and PCE with different model structures were compared in terms of a prediction capability under different amount of training data and number of inputs. The aim of the comparative study is to identify the relative prediction abilities and model flexibility of GPE and PCE. It was found that the GPE and PCE produce high performance qualities having fast computation speed compared to the developed basis model if new inputs having identical inputs and probability ranges were used. In terms of two-sample Kolmogorov-Smirnov (K-S) hypothesis test, mean values of the minimum p-values of the GPE and PCE were 0.999 and 0.569, respectively, if the number of samplings are over 30 cases. Otherwise, the PCE shows significantly reduced performance quality than the GPE. [ABSTRACT FROM AUTHOR]

Thermal comfort is the main driver of buildings energy consumption; it has been classified by building occupants to be of greater importance compared with visual and acoustic comfort. To respond correctly and quickly to the increase in energy price and pollution, thermal regulations and comfort approaches have emerged. This paper compares the thermal performances and energy demand of a vernacular and a low-income modern dwelling using two major thermal comfort approaches (Givoni's approach and adaptive thermal comfort recommended by The American Society of Heating, Refrigerating and Air-Conditioning Engineers in ASHRAE standards 55-2010) and the energy professional's method presented in the French Thermal Regulations RT2012. It shows the effectiveness of bioclimatic and passive strategies in reducing energy demand, increasing the thermal comfort level for the buildings, and therefore reducing greenhouse emissions. The results show that the vernacular house was comfortable during the warm day, which approved a 100% cooling energy efficiency (the thermal comfort has been achieved in a passive way), contrary to the contemporary dwelling, in which the use of air-conditioning modern systems was essential to meet the occupant needs in terms of thermal comfort. The difference between the houses' energy performances was estimated, including a 39% reduction in energy demand. [ABSTRACT FROM AUTHOR]

Among the various factors that affect building performance, occupant behavior (OB) has received more and more attention and has become a research hotspot in building design and operation in recent years. However, due to the remarkable randomness and diversity of OB in buildings, it is difficult to accurately describe its characteristics using a fixed schedule, which is a normal approach of most energy simulation tools. DeST, a whole building energy simulation tool offers the function of stochastic OB simulation so that the simulation results can be more in line with the actual situation. In the newly released DeST 3.0, the OB modules are developed based on the actual observed OB data and are divided into two parts: occupancy and occupant action modules. The occupancy module is based on the Markov chain, which simulates the occupant movements among the spaces inside and outside the buildings. The occupant action modules are proposed with an environment and event-driven stochastic infrastructure based on a three-parameter Weibull distribution, such as occupant shading, window, and air-conditioning (AC)/heating control behavior modules. This paper presents the OB modules development for coupled simulation in DeST 3.0 and discusses the effects of integrated simulation of occupant behavior on building energy consumption. Firstly, an overview of the current modelling efforts of OB is given, from the trend to the existing foundation. Secondly, the development of OB modules for coupled simulation in DeST 3.0 is introduced in-depth, including co-simulation of AC/heating control behavior, window behavior and shading behavior. Lastly, two case studies that realize coupled simulation using the developed modules are shown, one is the comparison between existing occupancy schedules from GB standards and the developed occupancy simulation, and the other is the comparison between the result of simulating with or without using AC/heating control behavior modules in two bedrooms of the residential building. [ABSTRACT FROM AUTHOR]

Exterior shading devices and outdoor units can be closely coupled since these two building components are commonly installed next to each other. This study uses a coupled EnergyPlus-Fluent modeling approach to examine how a combination of exterior shading and heat rejection from outdoor units can affect the ambient outdoor environment of a building, and how changes in the ambient outdoor environment can influence cooling loads and indoor PM2.5 exposure. Three exterior shading devices were simulated, including horizontal overhangs, vertical overhangs, and vertical fins. Data from wind-tunnel experiments and field measurements were used to ensure the accuracy of the airflow model, energy model, and pollution model developed in this study. Results indicate that horizontal overhangs could almost offset the increase in cooling loads due to increased ambient outdoor temperatures caused by heat rejection. The use of vertical overhangs did not always mean lower demand for space cooling when heat rejection was considered. Heat rejection, horizontal overhangs, and vertical overhangs could help reduce indoor PM2.5 exposure, while indoor air pollution was worse after the implementation of vertical fins. This study shows how exterior shading devices and outdoor units can be coupled to achieve better building energy efficiency and improved occupant health. [ABSTRACT FROM AUTHOR]

The rising energy consumption in residential buildings within the hot summer and cold winter (HSCW) climate zone, driven by occupants' pursuit of improved thermal comfort, necessitates effective energy conservation measures. This study established urban building energy models for 32,145 residential buildings in Changsha City, China, and conducted a comprehensive retrofit analysis of seven energy conservation measures (ECMs). Additionally, the study assessed the impact of residents' conscious energy-saving behaviors concerning air conditioner (AC) control. The research commenced by creating six baseline models representative of the diverse building stock. Identifying seven commonly used ECMs, the study examined the potential of each measure for enhancing energy efficiency. To facilitate the analysis, a dedicated toolkit, AutoBPS-Retrofit, was developed to efficiently modify the baseline model for each ECM. Furthermore, the investigation delved into the investment cost of implementing the ECMs and evaluated their simple payback year (PBP) and net present value (NPV). The results demonstrate that tailored retrofit plans are essential when addressing envelope improvements, varying according to building types and ages. Retrofits targeting lighting systems offer both promising energy savings and favorable economic viability, albeit subject to residents' preferences. Alternatively, upgrading the AC systems emerges as the most energy-efficient approach, yet the economic assessment raises concerns. The study's findings offer practical insights for governments seeking to establish effective carbon reduction goals and policies. Moreover, the research can assist energy-saving institutions, real-estate companies, and stakeholders involved in renovation projects by offering guidance in making informed decisions to enhance energy efficiency in city-scale residential buildings. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic and resulting containment measures have shown that energy consumption in buildings is linked to several factors, such as living habits, occupancy profiles, and heating ventilation and air conditioning (HVAC) systems. This paper addresses the influences of such factors on energy consumption in a residential building, analysing different scenarios (pre-COVID-19, lockdown, post-COVID-19), in terms of discomfort and energy needs, through the new hourly calculation method (UNI EN ISO 52016). Energy and environmental effects were studied in a real case study near Rome by varying occupancy profiles, lighting and appliance schedules, and HVAC systems. Results show that, during the heating period, the lockdown scenario led to the lowest hours of discomfort (−29% on average), but the highest in the cooling period (up to +154%, +28% on average). The same scenario led to reasonable reduction of energy needs for heating (−14%), but also highlighted a significant increase (+60%) for the cooling period. This study underlines how the pandemic has influenced the energy and environmental behaviours in buildings. Moreover, the new hourly calculation method points out the importance of analysing HVAC systems, in terms of hours of discomfort, which could provide results that are more reliable. [ABSTRACT FROM AUTHOR]

Abstract: Although absorption cooling has been available for many years, the technology has typically been viewed as a poorly performing alternative to vapour compression refrigeration. However, rising energy prices and the requirement to improve energy-efficiency is driving renewed interest in the technology, particularly within the context of combined cooling, heat and power systems (CCHP) for buildings. In order to understand the performance of absorption cooling, numerous models are available in the literature. The complexities involved in the thermodynamics of absorption chillers have, however, so far restricted researchers to creating steady-state or dynamic models reliant on data measurements of the internal chiller state, which require difficult-to-obtain, intrusive measurements. The pragmatic, yet fully dynamic model described in this paper is designed to be easily calibrated using data obtained from the measurements of inflows and outflows to a chiller, without resorting to intrusive measurements. The model comprises a series of linked control volumes featuring both performance maps and lumped mass volumes, which reflect the underlying physical structure of the device. The paper describes the modelling approach, theory and limitations, along with an example of the implementation of the model in the ESP-r code complete with calibration and an application to a specific example. [Copyright &y& Elsevier]

The use of Building Energy Models (BEM) has become widespread to reduce building energy consumption. Projection of the model in the future to know how different consumption strategies can be evaluated is one of the main applications of BEM. Many energy management optimization strategies can be used and, among others, model predictive control (MPC) has become very popular nowadays. When using models for predicting the future, we have to assume certain errors that come from uncertainty parameters. One of these uncertainties is the weather forecast needed to predict the building behavior in the near future. This paper proposes a methodology for quantifying the impact of the error generated by the weather forecast in the building's indoor climate conditions and energy demand. The objective is to estimate the error introduced by the weather forecast in the load forecasting to have more precise predicted data. The methodology employed site-specific, near-future forecast weather data obtained through online open access Application Programming Interfaces (APIs). The weather forecast providers supply forecasts up to 10 days ahead of key weather parameters such as outdoor temperature, relative humidity, wind speed and wind direction. This approach uses calibrated EnergyPlus models to foresee the errors in the indoor thermal behavior and energy demand caused by the increasing day-ahead weather forecasts. A case study investigated the impact of using up to 7-day weather forecasts on mean indoor temperature and energy demand predictions in a building located in Pamplona, Spain. The main novel concepts in this paper are: first, the characterization of the weather forecast error for a specific weather data provider and location and its effect in the building's load prediction. The error is calculated based on recorded hourly data so the results are provided on an hourly basis, avoiding the cancel out effect when a wider period of time is analyzed. The second is the classification and analysis of the data hour-by-hour to provide an estimate error for each hour of the day generating a map of hourly errors. This application becomes necessary when the building takes part in the day-ahead programs such as demand response or flexibility strategies, where the predicted hourly load must be provided to the grid in advance. The methodology developed in this paper can be extrapolated to any weather forecast provider, location or building. [ABSTRACT FROM AUTHOR]

Abstract Numerous occupant behavior models, typically stochastic ones, have been built to quantify the effect of occupants on building energy simulation, which however are supposed to go through a rigorous validation, or evaluation process to claim that they are qualified to be used in the application. Current contributions relevant with occupant behavior modeling in literature have been resorting to statistical metrics rather than those orienting on their application, causing the disputation in interpreting the accuracy of the occupant behavior models when they are actually used in simulation. Furthermore, the stochasticity of occupant behavior models necessitates statistical evaluation of the model accuracy, instead of the comparison between actual data and a single-run simulated data. This paper proposes a methodological framework for model evaluation from an application-oriented perspective, with lighting behavior as a case study. The metrics for evaluating lighting behavior models are identified according to different application scenarios, while the comparison between the measurement and simulation is done by introducing the statistical hypothesis testing. Analogous analyses on other behaviors can be conducted in the future, which altogether would foster more rigor and application significance in occupant behavior model evaluation. [ABSTRACT FROM AUTHOR]

Buildings consume a significant amount of energy worldwide in maintaining comfort for occupants. Building energy management systems (BEMS) are employed to ensure that the energy consumed is used efficiently. However these systems often do not adequately perform in minimising energy use. This is due to a number of reasons, including poor configuration or a lack of information such as being able to anticipate changes in weather conditions. We are now at the stage that building behaviour can be simulated, whereby computer programs can be used to predict building conditions, and therefore enable buildings to use energy more efficiently, when integrated with BEMS (i.e. simulation assisted control [1]). In this paper we demonstrate a low cost BEMS that uses building simulation to predict optimised electrical heating startup control points. Those that use electricity for heating in Scotland, where this study was based, tend to be fuel-poor, hence there is a strong case for optimisation, particularly when electricity costs nearly three times as much as the equivalent unit of gas for heating applications. The proposed system demonstrated a 50% energy saving in the reduced heating time compared to scheduling when retrospectively evaluated. [ABSTRACT FROM AUTHOR]

Most building energy simulation (BES) tools need detailed inputs for the modeling process because of the nature that building is a complex system and evaluating its performance usually involves many factors and uncertainties. In this research, a lightweight building energy simulation tool – SimBldPy, is proposed. The proposed simplified hourly method in this paper includes additional thermal resistances of the zone internal floor and internal walls coupled with adjacent zone temperature. Two DOE reference building types (one residential and one office) located in Philadelphia and San Francisco are used in the research to verify the performance of the tool. Its performance and validity in simulating hourly energy use with different heating and cooling set points in each zone, under various climate conditions, and with multiple ECMs being applied to the building, have been tested and verified with EnergyPlus. This tool and modeling method could be used for rapid modeling and assessment of building energy for a variety of ECM options. By using this tool in modeling an on-campus building in University of Pennsylvania, it is shown that the calibrated building model in SimBldPy can be used to model the energy use of an existing building. With low cost in computation, the tool is able to provide rapid modeling and assessment of building energy use (BEU) for parametric studies. [ABSTRACT FROM AUTHOR]

Developing BEPS models which predict energy usage to a high degree of accuracy can be extremely time consuming. As a result, assumptions are often made regarding the input data required. Making these assumptions without introducing a significant amount of uncertainty to the model can be difficult, and requires experience. Even so, rules of thumb from one geographic region are not automatically transferrable to other regions. This paper develops a methodology which can be used to determine useful guidelines for defining the most influential input data for an accurate BEPS model. Differential sensitivity analysis is carried out on parametric data gathered from five archetype dwelling models. The sensitivity analysis results are used in order to form a guideline minimum set of accurately defined input data. Although the guidelines formed apply specifically to Irish residential dwellings, the methodology and processes used in defining the guidelines is highly repeatable. The guideline minimum data set was applied to practical examples in order to be validated. Existing buildings were modelled, and only the parameters within the minimum data set are accurately defined. All building models predict annual energy usage to within 10% of actual measured data, with seasonal energy profiles well-matching. [ABSTRACT FROM AUTHOR]

Building retrofits provide a large opportunity to significantly reduce energy consumption in the buildings sector. Traditional building retrofits focus on equipment upgrades, often at the end of equipment life or failure, and result in replacement with marginally improved similar technology and limited energy savings. The Integrated System (IS) retrofit approach enables much greater energy savings by leveraging interactive effects between end use systems, enabling downsized or lower energy technologies. This paper presents a case study in Hawaii quantifying the benefits of an IS retrofit approach compared to two traditional retrofit approaches: a Standard Practice of upgrading equipment to meet minimum code requirements, and an Improved Practice of upgrading equipment to a higher efficiency. The IS approach showed an energy savings of 84% over existing building energy use, much higher than the traditional approaches of 13% and 33%. The IS retrofit also demonstrated the greatest energy cost savings potential. While the degree of savings realized from the IS approach will vary by building and climate, these findings indicate that savings on the order of 50% and greater are not possible without an IS approach. It is therefore recommended that the IS approach be universally adopted to achieve deep energy savings. [ABSTRACT FROM AUTHOR]

With increased use of variable refrigerant flow (VRF) systems in the U.S. building sector, interests in capability and rationality of various building energy modeling tools to simulate VRF systems are rising. This paper presents the detailed procedures for model calibration of a VRF system with a dedicated outdoor air system (DOAS) by comparing to detailed measured data from an occupancy emulated small office building. The building energy model is first developed based on as-built drawings, and building and system characteristics available. The whole building energy modeling tool used for the study is U.S. DOE’s EnergyPlus version 8.1. The initial model is, then, calibrated with the hourly measured data from the target building and VRF-DOAS system. In a detailed calibration procedures of the VRF-DOAS, the original EnergyPlus source code is modified to enable the modeling of the specific VRF-DOAS installed in the building. After a proper calibration during cooling and heating seasons, the VRF-DOAS model can reasonably predict the performance of the actual VRF-DOAS system based on the criteria from ASHRAE Guideline 14-2014. The calibration results show that hourly CV-RMSE and NMBE would be 15.7% and 3.8%, respectively, which is deemed to be calibrated. The whole-building energy usage after calibration of the VRF-DOAS model is 1.9% (78.8 kWh) lower than that of the measurements during comparison period. [ABSTRACT FROM AUTHOR]

Sensitivity analysis has been widely used in building energy assessment to provide reliable analysis of importance ranking for input variables in buildings. Most of previous studies used one single batch simulation models to obtain sensitivity indicators. To conduct robust analysis, this paper implements a sequential sensitivity analysis to assess the convergence of sensitivity indicators for two global sampling-based sensitivity analysis methods (standardized regression coefficients and meta-modelling Sobol) in an office building. The results indicate that this sequential method can be more effective and robust. In contrast, a single batch sensitivity method for building energy assessment may lead to non-convergence results due to smaller number of simulation models or over-convergence results due to larger number of simulation models. It is also found that the convergence rate for standardized regression methods are slower than that for the meta-modelling Sobol method. [ABSTRACT FROM AUTHOR]

To design energy-efficient buildings, energy assessment programs need to be developed for determining the inside air temperature, so that thermal comfort of the occupant can be sustained. The internal temperatures could be calculated through computational fluid dynamics (CFD) analysis; however, miniscule time steps (seconds and milliseconds) are used by a long-term simulation (i.e., weeks, months) that require excessive time for computing wind effects results even for high-performance personal computers. This paper examines a new method, wherein the wind effect surrounding the buildings is integrated with the external air temperature to facilitate wind simulation in building analysis over long periods. This was done with the help of an equivalent temperature (known as Tnatural), where the convection heat loss is produced in an equal capacity by this air temperature and by the built-in wind effects. Subsequently, this new external air temperature Tnatural can be used to calculate the internal air temperature. Upon inclusion of wind effects, above 90% of the results were found to be within 0–3 °C of the perceived temperatures compared to the real data (99% for insulated cavity brick (InsCB), 91% for cavity brick (CB), 93% for insulated reverse brick veneer (InsRBV) and 94% for insulated brick veneer (InsBV) modules). However, a decline of 83–88% was observed in the results after ignoring the wind effects. Hence, the presence of wind effects holds greater importance in correct simulation of the thermal performance of the modules. Moreover, the simulation time will expectedly reduce to below 1% of the original simulation time. [ABSTRACT FROM AUTHOR]

Applying phase change material (PCM) for latent heat storage in sustainable building systems has gained increasing attention. However, the nonlinear thermal properties of the material and the hysteresis between the two-phase change processes make the modelling of PCM challenging. Moreover, the influences of the PCM phase transition and hysteresis on the building thermal and energy performance have not been fully understood. This paper reviews the most commonly used modelling methods for PCM from the literature and discusses their advantages and disadvantages. A case study is carried out to examine the accuracy of those models in building simulation tools, including four methods to model the melting and freezing process of a PCM heat exchanger. These results are compared to experimental data of the heat transfer process in a PCM heat exchanger. That showed that the four modelling methods are all accurate for representing the thermal behavior of the PCM heat exchanger. The model with the DSC Cp method with hysteresis performs the best at predicting the heat transfer process in PCM in this case. The impacts of PCM phase change temperature and hysteresis on the building energy-saving potential and thermal comfort are analyzed in another case study, based on one modelling method from the first case study. The building in question is a three-room apartment with PCM-enhanced ventilated windows in Denmark. The study showed that the PCM hysteresis has a larger influence on the building energy consumption than the phase change temperature for both summer night cooling applications and for winter energy storage. However, it does not have a strong impact on the yearly total energy usage. For both summer and winter transition seasons, the PCM hysteresis has a larger influence on the predicted percentage of dissatisfied (PPD) than the phase change temperature, but not a strong impact on the transition season average PPD. It is therefore advised to choose the PCM hysteresis according to whether it is for a summer night cooling or a winter solar energy storage application, as this has a significant impact on the system's overall efficiency. [ABSTRACT FROM AUTHOR]

Overheating in residential building is a challenging problem that causes thermal discomfort, productivity reduction, and health problems. This paper aims to assess the climate change impact on thermal comfort in a Belgian reference case. The case study represents a nearly zero energy building that operates without active cooling during summer. The study quantifies the impact of climate change on overheating risks using three representative concentration pathway (RCP) trajectories for greenhouse gas concentration adopted by the Intergovernmental Panel on Climate Change (IPCC). Building performance analysis is carried out using a multizone dynamic simulation program EnergyPlus. The results show that bioclimatic and thermal adaptation strategies, including adaptive thermal comfort models, cannot suppress the effect of global warming. By 2050, zero energy buildings will be vulnerable to overheating. [ABSTRACT FROM AUTHOR]

This paper presents the study of the performance of building-integrated photovoltaic (BIPV) applied on vertical building envelope as overhang shading devices on energy saving. In Indonesia, where solar energy is abundant, the utilization of PV system as renewable energy is very potential, especially in remote area. However, in the urban core of Indonesia, the utilization of PV system is not yet economically viable. In this study, six BIPV models with different design of PV panel shading devices were simulated using weather file of Jakarta, an urban core of Indonesia. The results show that installing fewer PV panel shading devices on building façade with greater distance is more effective than installing more PV panel shading device with less distance. The LCOE (levelized cost of electricity) of all models that is lower than the national grid electricity cost indicates that BIPV could be economically profitable if it is designed properly. [ABSTRACT FROM AUTHOR]

The role of occupants is important as building energy consumption is significantly attributed to their behaviour. Given the diverse activities within, and high levels of personal control over the indoor environment, occupants’ behaviour is one of the key uncertainties in predicting energy use in the residential sector. With an aim to better understand residential adaptive thermal comfort behaviours, longitudinal field observations were conducted with smartphone surveys and simultaneous temperature measurements in a sample of Australian homes (n = 42). This paper derives statistical models to enable predicting of the percentage of adaptive strategies in use (e.g. operation of air-conditioners, heaters, fans and windows), as a function of temperature. The analysis on our Sydney sample indicated that an outdoor temperature of 25 °C was the most favourable condition, inclusive of all seasons investigated throughout the 2-year monitoring period, maximising the use of natural ventilation and simultaneously minimising the householders’ dependence on their home air-conditioning system. This study also revealed personal and demographic characteristics that can have a significant impact on the householder’s decision to use their air-conditioning system. [ABSTRACT FROM AUTHOR]

Pitched-roof buildings make up a considerable proportion of architectural roof styles. Precise estimation of solar energy potential on pitched roofs is thus crucial to the sustainable development and renewable energy consumption of human habitats. Conventional solar radiation measurements usually adopt Light Detection and Ranging (LiDAR) data, which can only be extracted from existing buildings. There has been relatively little research assessing solar radiation on pitched roofs. This paper develops a pixel-based approach to estimation of solar energy potentials over pitched roofs based on the pretext of architectural design drawings. A typical Australian house with nine roofs is then chosen for implementation through a case study. The solar radiation on a certain cell of a shadow map is mathematically formulated for each pixel unit. Its yields over a certain time period are calculated by considering multiple instantaneous solar irradiances and visually presented through image processing. The resulting solar radiation maps, especially a coloured 3D map, reveal the roofs’ radiation distribution including effects from objects on the roofs such as chimneys. Radiation contour lines are mapped to obtain installation ranges for solar devices. This study will benefit commercial energy investors, residents and urban planners in the efficient use of renewable energy sources through accurate prediction of solar radiation potential and identification of areas receiving high radiation over sloping roofs. [ABSTRACT FROM AUTHOR]

The area of projected shadow on building facades may play a role of paramount importance in the prediction of solar energy conversion and building thermal and energy performance. Algorithms for solar shading calculations may directly affect the accuracy of results obtained by building energy simulation tools. In addition, the consideration of uncertain design parameters imply an estimative of a confidence interval of solar fraction results that determine the reliability as well as the improvement of shading calculation models. In this way, this paper presents a methodology for uncertainty and sensitivity analysis applied to the prediction of sunlit area on building exterior surfaces with shading devices. From a single building model, the solar fraction was investigated for two cities and four typical days. According to the obtained results, more than 20% of all simulation time steps have uncertainties equal or higher than 5% on the solar fraction calculation at 95% confidence level. The maximum values of the uncertainties occur in warmer months, which could significantly impact the building energy balance. Three inputs have higher influence on the uncertainties on solar fraction results: (1) latitude, (2) orientation and (3) width of overhang fins. Perturbation of only 5° on the building orientation may imply important uncertainties on solar fraction, which is normally neglected by designers. The results highlight the importance of assessing the uncertainty of inputs in algorithms such as the one to calculate the surface solar fraction that is an important prerequisite of the final building energy balance. [ABSTRACT FROM AUTHOR]

The paper describes a systematic framework that uses exergoeconomic theory integrated into ‘building energy retrofit’ (BER) design. An exergoeconomic module, based on the SPECO method, has been embedded into ‘EXRETOpt’, a recently developed retrofit-oriented exergy simulation tool based on EnergyPlus. Both active and passive technologies were analysed using two calibrated archetype non-domestic buildings as case studies (an office and a primary school). A novel cost-benefit indicator which accounts for building exergy destruction cost, retrofit annual capital cost, and project annual revenue is presented. This indicator is employed to account for best exergoeconomic performance technologies and to further develop deep BER packages. Compared to typical practice, exergoeconomics combined with cost-benefit provides a powerful tool for exploration and design improvement of building energy systems. In both cases, final product cost for heating and cooling processes were substantially reduced. In addition, the office case presented improvements in energy use by 67%, CO2 emissions by 53%, thermal comfort by 22%, exergy destructions by 42%, and the overall building exergy efficiency was improved from 14.8% to 20.0%. The school case presented similar results with an improvement of building exergy efficiency from 8.2% to 11.1%, and the potential to generate income due to current government incentives. [ABSTRACT FROM AUTHOR]

Nearly 40% of primary energy consumption is related to the usage of energy in Buildings. Energy-related data such as indoor air temperature and power consumption of heating/cooling systems can be now collected due to the widespread diffusion of Internet-of-Things devices. Such energy data can be used (i) to train data-driven models than learn the thermal properties of buildings and (ii) to predict indoor temperature evolution. In this paper, we present a Grey-box model to estimate thermal dynamics in buildings based on Unscented Kalman Filter and thermal network representation. The proposed methodology has been applied in two different buildings with two different thermal network discretizations to test its accuracy in indoor air temperature prediction. Due to a lack of a real-world data sampled by Internet of Things (IoT) devices, a realistic data-set has been generated using the software Energy+, by referring to real industrial building models. Results on synthetic and realistic data show the accuracy of the proposed methodology in predicting indoor temperature trends up to the next 24 h with a maximum error lower than 2 °C, considering one year of data with different weather conditions. [ABSTRACT FROM AUTHOR]

Variable refrigerant flow (VRF) systems vary the refrigerant flow to meet the dynamic zone thermal loads, leading to more efficient operations than other system types. This paper introduces a new model that simulates the energy performance of VRF systems in the heat pump (HP) operation mode. Compared with the current VRF-HP models implemented in EnergyPlus, the new VRF system model has more component models based on physics and thus has significant innovations in: (1) enabling advanced controls, including variable evaporating and condensing temperatures in the indoor and outdoor units, and variable fan speeds based on the temperature and zone load in the indoor units, (2) adding a detailed refrigerant pipe heat loss calculation using refrigerant flow rate, operational conditions, pipe length, and pipe insulation materials, (3) improving accuracy of simulation especially in partial load conditions, and (4) improving the usability of the model by significantly reducing the number of user input performance curves. The VRF-HP model is implemented in EnergyPlus and validated with measured data from field tests. Results show that the new VRF-HP model provides more accurate estimate of the VRF-HP system performance, which is key to determining code compliance credits as well as utilities incentive for VRF technologies. [ABSTRACT FROM AUTHOR]

Traditionally, in building energy modeling (BEM) programs, occupant behavior (OB) inputs are deterministic and less indicative of real world scenarios, contributing to discrepancies between simulated and actual energy use in buildings. This paper presents a new OB modeling tool, with an occupant behavior functional mock-up unit (obFMU) that enables co-simulation with BEM programs implementing functional mock-up interface (FMI). The components detailed in the development of the obFMU include an overview of the DNAS (drivers-needs-actions-systems) ontology and the occupant behavior eXtensible Markup Language (obXML) schema, in addition to details on the creation of the obFMU that contains the co-simulation interface, the data model and solvers. To demonstrate functionality of the tool, three examples of occupant behaviors were simulated, including: (1) turning on and off lights, (2) opening and closing windows, and (3) turning on and off the air conditioners. The obFMU can be used via co-simulation with all building simulation programs that implement the FMI, thus users are not limited to a particular tool. Another advantage is the use of obXML schema to represent occupant behavior, standardize the description of occupant behavior enabling information exchange. [ABSTRACT FROM AUTHOR]

Occupant behavior is now widely recognized as a major contributing factor to uncertainty of building performance. While a surge of research on the topic has occurred over the past four decades, and particularly the past few years, there are many gaps in knowledge and limitations to current methodologies. This paper outlines the state-of-the-art research, current obstacles and future needs and directions for the following four-step iterative process: (1) occupant monitoring and data collection, (2) model development, (3) model evaluation, and (4) model implementation into building simulation tools. Major themes include the need for greater rigor in experimental methodologies; detailed, honest, and candid reporting of methods and results; and development of an efficient means to implement occupant behavior models and integrate them into building energy modeling programs. [ABSTRACT FROM AUTHOR]

The paper presents the results of the analysis of the impact of various ventilation systems on the energy consumption performed for one Polish museum building that was built in 1929–1930. Simulations were carried out with the use of two computer codes: CONTAM and ESP-r. Multi-zone models including the exhibition rooms and the staircase were prepared. The simulations were made of synthetic weather data for one of the Polish towns for two months of the heating season. Twenty-four hour variability of internal heat gains was taken into account. The results show clearly that the natural ventilation system (which is currently used in the building) enables the air exchange with fresh air on the first floor only. The air infiltration on the upper levels is close to zero. Rebuilding the ventilation system generates changes in the energy demand of the building. It is presented how the heat demand increases with the increase of the ventilation air flow and what is the impact of the air infiltration on the heat demand for different variants of ventilation. [ABSTRACT FROM AUTHOR]

The paper presents the results of 1-year measurement of indoor environment parameters (temperature, relative humidity, CO 2 concentration) in exhibition rooms of one Polish museum in various periods of the year, and the results of simulation on thermal model of this building. The influence of a temperature control scheme in museum rooms on heating and cooling demand was analysed. The actual state (poor control of internal temperature) and ideal control of internal temperature were analysed – two cases in the winter and two cases in the summer. Simulations were performed by ESP-r program. The multi-zone model of the building was validated based on measurement data. Measurements and simulations revealed significant variations in the temperature in the rooms of the museum. The analysis showed that the maintaining internal temperature at constant level of 20 °C in winter reduces monthly heat demand in most of the exhibition rooms. Obtained effect is 5–16% depending on the premises. Provision the raise of a temperature by 1 K results in the increase of heat consumption by 6%. Maintenance of a desired internal temperature, which does not exceed 24 °C in the summer, requires the provision of coolness to the museum premises. [ABSTRACT FROM AUTHOR]

Abstract: This paper aims to validate and improve three cross and single-sided natural ventilation models implemented in a whole-building hygrothermal and energy simulation program. The tested models are the British Standard for cross ventilation, the de Gids and Phaff's and Larsen's for single-sided ventilation. Airflow rates obtained by those models have been compared to the measurements performed in two full-scale buildings: one single room house located in a wind tunnel facility and one real three-storey building. Results show a large variation of airflow rates provided by the different models. The Larsen's model can be improved if coupled to the CPCALC algorithm, providing better results for both wind tunnel and on-site experiments. [Copyright &y& Elsevier]

Abstract: Passive Houses have gained popularity the last 10years as a way of improving the energy efficiency in the housing stock. The combination of a highly insulating building envelope and large solar heat gains summertime can, however, result in excessive temperatures. The aim of this paper is to evaluate a comfort cooling strategy for attaining good indoor climate summertime while maintaining good energy efficiency. The studied strategy is a night cool storage with phase change material (PCM). To evaluate this, a Matlab code was used for the analysis of climate files along with the thermodynamical properties of PCM storages and then used with IDA Indoor Climate and Energy for building simulations. The building model is based on an actual Passive House in the district of Lambohov in Linköping, Sweden, where continuous logging of temperatures are available. Without comfort cooling the simulations show excessive temperatures summertime, which is consistent with the field measurements from the actual house. The results show that the PCM can remove a substantial share of the degree hours with excessive temperatures. [Copyright &y& Elsevier]

This study has investigated the feasibility of three different solar-assisted air conditioning systems for typical medium-sized office buildings in all eight Australian capital cities using the whole building energy simulation software EnergyPlus. The studied solar cooling systems include: solar desiccant-evaporative cooling (SDEC) system, hybrid solar desiccant-compression cooling (SDCC) system, and solar absorption cooling (SAC) system. A referenced conventional vapor compression variable-air-volume (VAV) system has also been investigated for comparison purpose. The technical, environmental, and economic performances of each solar cooling system have been evaluated in terms of solar fraction (SF), system coefficient of performance (COP), annual HVAC (heating, ventilation, and air conditioning) electricity consumption, annual CO2 emissions reduction, payback period (PBP), and net present value (NPV). The results demonstrate that the SDEC system consumes the least energy in Brisbane and Darwin, achieving 56.9% and 82.1% annual energy savings, respectively, compared to the conventional VAV system, while for the other six cities, the SAC system is the most energy efficient. However, from both energy and economic aspects, the SDEC system is more feasible in Adelaide, Brisbane, Darwin, Melbourne, Perth, and Sydney because of high annual SF and COP, low yearly energy consumption, short PBP and positive NPV, while for Canberra and Hobart, although the SAC system achieves considerable energy savings, it is not economically beneficial due to high initial cost. Therefore, the SDEC system is the most economically beneficial for most of Australian cities, especially in hot and humid climates. The SAC system is also energy efficient, but is not as economic as the SDEC system. However, for Canberra and Hobart, reducing initial cost is the key point to achieve economic feasibility of solar cooling applications. [ABSTRACT FROM AUTHOR]

Realistic models of occupant behaviour in relation to air-conditioner (a/c) use are fundamentally important for developing accurate building energy simulation tools. In Australia and elsewhere, such simulation tools are inextricably bound both in legislation and in the design of new technology, electricity infrastructure and regulatory schemes. An increasing number of studies in the literature confirm just how important occupants are in determining overall energy consumption, but obtaining the data on which to build behaviour models is a non-trivial task. Here data is presented on air-conditioner usage derived from three different types of case study analyses. These are: (i) use of aggregate energy consumption data coupled with weather, demographic and building statistics across Australia to estimate key predictors of energy use at the aggregate level; (ii) use of survey data to determine characteristic a/c switch on/off behaviours and usage frequencies; and (iii) use of detailed household level sub-circuit monitoring from 140 households to determine a/c switch on/off probabilities and their dependence on different building and occupant parameters. These case studies are used to assess the difficulties associated with translation of different forms of individual, aggregate and survey based information into a/c behaviour simulation models. Finally a method of linking the data gathering methodologies with the model development is suggested. This method would combine whole-of-house "smart"-meter data measurements with linked targeted occupant surveying. [ABSTRACT FROM AUTHOR]

Following development and validation of the SOLENE-microclimat tool, the underlying model was used to compare the impacts of various "greening strategies" on buildings' summer energy consumption and indoor comfort. This study distinguishes between direct and indirect impacts by successively implementing the test strategies on both the studied building and surrounding ones; it also considers insulated vs. non-insulated buildings. Findings indicate that green walls have a direct effect on indoor comfort throughout the entire building, whereas the effect of green roofs is apparently primarily confined to the upper floor. Moreover, the indirect effect of a green wall is greater, mainly due to the drop in infrared emissions resulting from a lower surface temperature. It has also been proven that the indirect effects of green walls and surrounding lawns can help reduce the loads acting on a non-insulated building. [ABSTRACT FROM AUTHOR]

The electricity sector foresees a significant change in the way energy is generated and distributed in the coming years. With the increasing penetration of renewable energy sources, smart algorithms can determine the difference about how and when energy is produced or consumed by residential districts. However, managing and implementing energy demand response, in particular energy flexibility activations, in real case studies still presents issues to be solved. This study, within the framework of the European project "SABINA H2020", addresses the development of a multi-level optimization algorithm that has been tested in a semi-virtual real-time configuration. Results from a two-day test show the potential of building's flexibility and highlight its complexity. Results show how the first level algorithm goal to reduce the energy injected to the grid is accomplished as well as the energy consumption shift from nighttime to daytime hours. As conclusion, the study demonstrates the feasibility of such kind of configurations and puts the basis for real test site implementation. [ABSTRACT FROM AUTHOR]