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Highlights • Definition of passive envelope indexes and caracterization of libraries in La Plata. • Environmental monitoring: achievement of preventive conservation indexes. • Correlation between passive envelope indexes and preventive conservation indexes. • Determination of the most influential passive envelope indexes for the achievement of preventive conservation indexes. Abstract The common approach for libraries to preserve their paper-based collections from irreversible deterioration is by controlling quantitative parameters, such as temperature and relative humidity. Variations of these parameters for preventive conservation can be expressed by the "performance index" (PI) and the "amplitude index" (AI). Building envelope is the first filter of the external climate, buffering the external weather fluctuations and maintaining the building's indoor climate stable. Its shape, window areas and envelope materials are the most influential parameters. As they capture the relationship of a few geometric and physical variables with the building's performance, the envelope characteristics can be expressed as certain passive envelope indexes. This paper studies the relationship of certain passive envelope indexes and the preventive conservation indexes for books for several libraries and archives located in La Plata, Argentina. The results show the impact of every passive envelope index upon the preventive conservation indexes. The compactness, heaviness, adjacency to spaces and adjacency to ground have a positive linear correlation meanwhile transparency and global transmittance are parameters with a negative correlation. In general, the most influential parameter is the relative area adjacent to other spaces, followed by global transmittance, transparency, heaviness, relative area adjacent to ground and compactness. [ABSTRACT FROM AUTHOR]

Much research has been focused on maintaining stable humidity conditions in buildings housing heritage collections while reducing energy use. Moisture buffering by collections themselves can have a marked effect on the stabilisation of relative humidity (RH), the key parameter for preservation. Modelling of moisture transport using COMSOL Multiphysics was applied to transform three-dimensional paper and wooden objects into their one-dimensional representations, without changing the moisture uptake and release characteristics. The results were coupled to the modelling of indoor microclimate and energy consumption in collection storage spaces with the use of WUFI ® Plus software. The study revealed the crucial impact of air exchange rate of the building on the stability of indoor RH and the humidification and dehumidification loads required to maintain it. In the adequately air-tight library store, a sizeable paper collection was found to reduce the RH fluctuations from ±9% to ±6% around the yearly average and the energy consumption due to the humidification and dehumidification load by 38% when compared with the empty space, for a high-quality climate control scenario. In turn, a wooden collection, occupying a realistic fraction of a museum store was not large enough to significantly narrow down the RH variations and reduce the energy consumption. [ABSTRACT FROM AUTHOR]

• A novel agent-based model (ABM) was developed to explore occupant behaviors in the context of built environment. • Relevant data was collected using customized sensor nodes and paper-based survey in a test bed building. • A validation study was conducted to test the occupant behavior model with the methods of visualization and calculation of quantification metrics for performance evaluation. • The proposed research framework has the potential to improve both building energy efficiency and occupant comfort during the life cycle of a building. Occupant behaviors are one of the dominant factors that influence building energy use. Traditional building energy modeling programs use typical occupant schedules that often do not reflect actual situations. Robust occupant behavior modeling that seamlessly integrates with building energy models will not only improve simulation performance, but also provide a deeper understanding of occupant behaviors in buildings. This paper presents a development and validation approach to a novel occupant behavior model in commercial buildings. A robust agent-based modeling (ABM) tool, namely Performance Moderator Functions server (PMFserv), is used as the basis of the occupant behavior model. The ABM considers various occupant perceptions and interactions with window, door, and window-blinds based on the environmental conditions. An elaborate agent-based model that represents an office space in an existing building is developed. This is followed by a validation study of the ABM through the use of embedded sensors that capture the indoor ambient conditions and a survey to record actual occupant behaviors. By comparing the recorded behavior data with ABM output, this paper discusses the proposed ABM's prediction ability, limitations, and extensibility. Finally, the paper concludes with the potential of integrating the occupant behavior model with building energy simulation programs. [ABSTRACT FROM AUTHOR]

• This paper presents a comprehensive review of cross ventilation research in buildings. • The advantages and disadvantages of different research methods are compared. • The ventilation models of cross ventilation are reviewed. • The influencing parameters of cross ventilation are summarized. • The future perspectives of cross ventilation research and practical applications are proposed. There is a growing body of literature that recognizes that natural ventilation plays a vital role in indoor air quality, thermal comfort and building energy consumption. This paper systematically reviews the previously published research of the most efficient and typical natural ventilation type - cross ventilation, aiming to present the main research topics in contemporary research and provide an agenda for future studies. The methodologies, airflow pattern, ventilation models and influencing parameters of cross ventilation were comprehensively summarized and discussed. The chained analysis and data-driven methods are the potential approaches to study cross ventilation more efficiently. The comparisons of different ventilation models of cross ventilation help to better understand the basic mechanisms that drive the cross ventilation airflow. [ABSTRACT FROM AUTHOR]

Abstract The assessment of building energy performance through dynamic simulations has been increasing significantly in recent years since it represents a key strategy for the correct design of highly efficient buildings. Results of dynamic energy simulations are affected by many uncertainties, and its reliability depends on the accuracy of the input variables. One of the most influential variables is the climate surrounding the building, a reason why the use of accurate weather data files is essential, but experimental datasets are not always available. In this context, this paper analyses numerical weather datasets obtained from different regional climate models by comparing them with real data; in addition, it evaluates their impact on the energy performance of a historical building in Asunción through dynamic simulations. The database of five different weather data sources is compared with observed meteorological data in order to assess their accuracy through statistical analyses. Moreover, some methodologies to estimate diffused and direct components of the global solar radiation are evaluated, with the objective of solving the problem of missing direct and diffused solar data components from the meteorological codes. Subsequently, weather data files are generated to quantify the influence of measured/simulated meteorological data on the evaluation of building energy performance. The results obtained in this paper show that the simulated meteorological data agree very well with real observations for the year under study. Also, the simulations of the building energy performance delivered similar values to those obtained using the real weather dataset. Therefore, the regional climate models can represent a reliable tool for building energy performance assessment, and mainly for the calibration of building energy models when measured weather data is not available. [ABSTRACT FROM AUTHOR]

Abstract Over the last decade, building engineers have begun implementing sensible-latent de-coupled air-conditioning systems in non-residential buildings in hot-humid climates. Typically, a de-coupled system consists of a dedicated outdoor air sub-system for ventilation and high-temperature radiant cooling sub-system for space cooling. This approach has lowered cooling energy demands and fan energy consumption in buildings. However, the complete energy saving potential of de-coupled systems, specifically high-temperature space cooling sub-systems, can only be realized by using low-lift chillers that supply chilled water which matches the high-temperature radiant cooling application. This paper discusses the results of a retro-installation of a prototype modular low-lift chiller to provide high-temperature chilled water (at 17 °C) to the radiant cooling units. The paper presents temperature and cooling load profiles, control methodology and energy efficiency improvements of the low-lift cooling system. The paper also further discusses the influence of various parameters on the performance of the chiller. Despite having a cooling capacity of only 20 kW, the modular low-lift chiller is consistently able to achieve a Coefficient of Performance (COP) of 8. By operating at a low-lift (20 K) compared to a high-lift (29 K), the sensible cooling electrical consumption (at the chiller) is reduced by 23% despite being compared to a high-lift low-temperature chiller with 100 x higher cooling capacity. When normalized for cooling capacities, this reduction is between 29–30%. The project is the first known installation of low-lift cooling for building comfort control in hot-humid climates, and first reported publication of low-lift cooling in a real-life scenario - i.e., non-laboratory conditions or modelling exercise. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a new method entitled "BBEE (Building Blocks Energy Estimation)" for estimating energy performance at the district level is proposed. It consists of two branches, namely the BBEE algorithm and an energy database of a typical zone. This method is used to keep architects and urban planners informed of the energy performance of their design by clustering zones and looking up corresponding energy intensities from the database. Because the related energy databases are preexisting, energy performance modeling and simulation are not required from the user. On the other hand, the database is set up and continuously replenished by parameterization simulations with a basic model of typical zones. This task was separated from the estimation process and operated by experts, which shortened the process and reduced modeling errors. As a case study, an urban district with eight buildings was estimated under three climate conditions separately following the proposed BBEE method. Results were compared with the full-model simulation using a simulation tool called DeST. The difference in annual heating demand between estimation and simulation was reported as less than 6% in all three cases. The potential applications and limitations of the proposed BBEE method are discussed at the end of this paper. Although further improvements are still required, the new estimation method could be helpful for energy performance estimation at the district level at the early stage of design. [ABSTRACT FROM AUTHOR]

Abstract In 2011, the Danish government published an energy strategy for Denmark where one of the main targets are that Denmark should be a fossil-free society by 2050. Calculations show, that in order to reach this goal it is necessary to reduce the energy consumption of the existing building stock by 50% on average. Since a 50% reduction is obviously not possible for all buildings, those that can should aim for a so-called "deep energy renovation", i.e. reducing the energy consumption to a level corresponding to that of new buildings or even more. This paper describes two case studies where multi-story apartment buildings have undergone deep energy renovation. "Traneparken" where the expected energy use after renovation aimed at a level corresponding to that of a new building according to the Danish Building Regulations from 2015. "Sems Have" where the aim was to go even further and meet the requirements expected for new buildings in 2020, i.e. corresponding to the Danish "nearly zero energy"-definition according to the EPBD. The paper reports on calculations and measurements of energy savings, the economy of the projects and looks at the added benefits or co-benefits that residents, housing association and society in general have achieved in addition to significant energy savings. [ABSTRACT FROM AUTHOR]

Highlights • A total of 925 papers were searched and 106 articles were screened for deep review. • Green buildings generally performed better than the conventional counterparts. • A significant gap between the designed and operational energy use was found. • The key findings of objective IEQ and occupant satisfaction were summarized. • The performances of green buildings in China and the U.S. were compared. ABSTRACT This paper aims to review the published researches on post-occupancy performance of green buildings in terms of energy use, indoor environment quality (IEQ) and occupant satisfaction. A total of 925 related papers were searched and 106 articles were screened for deep review. The study also compared the actual operating performance of green buildings in China and the United States, with information collected from previous research. The findings of literature review can be summarized as follows: 1) Though with some exceptional cases, the energy performance of green buildings was on average better than the conventional counterparts with similar climate conditions; 2) A significant gap between the designed and operational energy consumption was found, and lots of green buildings saved less energy than expected; 3) No clear relationship between the actual energy use and the green building certification level could be observed; 4) The actual IEQ conditions of green buildings were not comparable in different countries due to the variance in design criterions and operation modes; 5) Green buildings generally had higher occupants' satisfaction level than conventional buildings, although the subjective data from the U.S. did not support this inference. Furthermore, this study proposed two areas worthy further investigations in the field of post-occupancy evaluation on green buildings, including new data collection technologies and performance optimization at the comprehensive level. [ABSTRACT FROM AUTHOR]

Highlights • A new experimental procedure to test PCM-enhanced components is presented. • A modified Dynamic Heat Flow Meter Apparatus is used to perform the tests. • The thermal conductivity of PCMs is measured in different phases (solid-liquid). • Indications to solve the issues related to building PCM-specimens are provided. Abstract The implementation, in Building Performance Simulations (BPS) tools, of robust models capable of simulating the thermophysical behaviour of a Phase Change Material (PCM) represents a fundamental step for an appropriate thermal evaluation of buildings that adopt PCM-enhanced envelope components. Reliable and robust measuring procedures are essential, at a material and component level, to provide experimental data for the empirical validation of software tools. The traditional laboratory tests that are generally used for the validation of models present some limitations, because PCMs are usually subjected to conditions that may be very different from the real boundary conditions of the building components in which PCMs are applied. Furthermore, in many experimental full-scale mockups, the relatively small quantity of installed PCM and the combination of several thermal phenomena do not allow software tools to be tested in a reliable way. In this paper, an experimental procedure, based on a modified Heat Flow Meter Apparatus, has been developed to test the behaviour of PCM-enhanced components; the procedure, which is based on the measurement of the sinusoidal response, has been set up to provide data for the comparison and testing of numerical models and of BPS tools. Moreover, general indications and guidelines are provided to solve some issues related to building specimens that contain bulk PCM in order to obtain a more accurate measurement of their performance. The experimental results presented in this paper were obtained from two different bulk PCMs (organic and inorganic). It was found that it is important to evaluate different PCM typologies and different thermophysical boundary conditions, including partial and full phase transitions, to test simulation codes that implement PCM modelling functions. In fact, some phenomena, such as hysteresis and subcooling effects are more evident when partial phase transition takes place. The results related to the characterization of the thermal conductivity of a paraffin-based PCM have shown a significant increase (up to 42%) of the equivalent thermal conductivity from a solid to a liquid state, with an upward heat flux, thus highlighting that further investigations and improvements are needed to measure the equivalent thermal conductivity in the different PCM phases. [ABSTRACT FROM AUTHOR]

Highlights • Redefine and classified "building energy performance gap". • Identify the important role of life-cycle and stakeholders. • Identify, classify and discuss the root causes of "building energy performance gap". • Discuss the corresponding strategies to close the gap. • Identify eight areas and topics requiring future research. Abstract The reliability, security, and sustainability of energy generation and supply are of global importance and the building sector accounts for up to 32% of total energy consumption, which makes it a key player in the domain. Previous research has identified that the actual energy consumption in buildings could be as much as 2.5 times of the predicted or simulated. This large building energy performance gap (BEPG) between the predicted and actual consumption has caused a significant problem for building energy supply and demand management and therefore have attracted increasing attention from researchers around the world. These researches have resulted in a large number of publications over the last decade. However, research has not reached the phase where the root causes of BEPG could be effectively identified, managed, and eliminated. There remains a lack of systematic and comprehensive review of the current literature to understand the current state of play, and set directions for future research. To fill this gap, in this paper, a thorough survey and review of BEPG research was carried out. The paper collected and analyzed 227 relevant publications and developed a framework for better understanding previous BEPG research. Subsequently, an in-depth analysis of BEPG research was conducted to explore its causes and corresponding strategies (including design concept, "hard" technologies and "soft" measures). Not only the interaction among causes but also the strengths and limitations of corresponding strategies were discussed in detail. Future research is finally recommended based on the limitations of exist strategies, including (1) building energy performance life-cycle thinking; (2) energy performance information integrity; (3) big data collection and analytical method; (4) stakeholders' attributions, decision criteria and behavior; (5) stakeholder interactions; (6) modelling and simulation validation; (7) multidisciplinary approach; and (8) building system flexibility. [ABSTRACT FROM AUTHOR]

Highlights • The state-of-the-art research of energy demand flexibility of demand responsive building is reviewed. • The energy demand flexibility measures range from renewable energy to HVAC, energy storage, building thermal mass, appliances, and customer behavior are introduced. • Systematic methodology framework to evaluate energy demand flexibility in buildings are developed. Abstract This paper classifies and discusses the energy flexibility improvement strategies for demand responsive control in grid-interactive buildings based on a comprehensive study of the literature. Both supply and demand sides are considered. The flexibility measures range from renewable energy such as photovoltaic cells (PV) and wind to heating, ventilation, and air conditioning (HVAC) systems, energy storage, building thermal mass, appliances, and occupant behaviors. Currently, owing to the highly developed smart appliances and sensing communication techniques, DR is considered as an essential measure for improving energy flexibility in buildings without much additional investment. With the help of advanced demand response (DR) control strategies and measures, buildings can become more flexible in terms of power demand from the power grid. In this way, buildings achieve a better ability to balance differences in energy supply and demand. Furthermore, a synergistic approach with various measures is advisable, e.g., the use of energy storage technologies with PV and passive DR methods. This paper summarizes the measures for improving the flexibility of commercial and residential buildings, and develops a systematic methodology framework to evaluate energy demand flexibility in buildings. [ABSTRACT FROM AUTHOR]

Abstract In order to reduce the energy consumption for cooling in our buildings, the use of passive cooling solutions is necessary. One of these solutions is natural ventilative cooling, where airflows generated by single-sided natural ventilation, until today have mainly been calculated from the De Gids & Phaff equation in the European Standard EN 15242:2007. In the revised standard EN 16798-7:2017, a new version of the equation for single-sided natural ventilation is released. The work in this paper will compare the results from the new equation with earlier equations for single-sided ventilation and hold them up against wind-tunnel measurements, full-scale measurements and CONTAM calculations to clarify whether and why the new equation is to be preferred for future design solutions for single-sided natural ventilation and ventilative cooling. Due to the implementation in calculation standards and regulations, the new calculation model should underestimate rather than overestimate the airflow rates, so as to remain on the safe side when estimating ventilative cooling potential. The work in this paper concludes that the new simple direct calculation model in EN 16798-7:2017 predicts the airflows through windows in a more conservative way than earlier equations, by representing an average of the airflow rate in the building that is generally on the safe side. The accuracy of the EN 16798-7:2017 equation was found by comparison to wind tunnel measurements to be 29% but with underestimations in 88% of the cases investigated. For the CONTAM calculations, it was found that the use of the new EN 16798-7:2017 equation (with room based height for the stack effect) slightly underestimates the airflow rate as desired, as soon as the temperature difference across the opening is above 0°C. Based on the comparisons presented in this paper, the authors consider the new calculation model in EN 16798-7:2017 well suited for the use in calculation standards to integrate natural ventilative cooling effects from single-sided ventilation. [ABSTRACT FROM AUTHOR]

Highlights • This paper uses building structural attributes such as shapes of buildings, relative compactness(RC), glazing area(GA), roof area(RA), surface area(SA), wall area(WA), orientation(OR), overall height(OH) and glazing area distribution(GAD) for prediction of heating and cooling load. • The paper explores the data set and features to get insights with feature correlation, mutual information their association strengths etc and their relation with heating and cooling load. • The paper proposes novel group of methods based on emerging machine learning method extreme learning machine(ELM) which has shallows architecture. • The paper proposes novel method based on ELM variant online sequential extreme learning machine(OSELM) for heating and cooling load prediction in online and adaptive environment. This model also helps when data is trained in chunk by chunk fashion. • The paper demonstrates several models based on combination of learning mode, activation function and features sets and compare their results with existing work extensively. Abstract In the present day environment, smart buildings require optimization of energy consumption through monitoring, consumption prediction and making policy decisions accordingly. Attributes related to building design and structure play a vital role in heating load(HL) and cooling load(CL) of the building which directly affects the energy performance of the buildings. For prediction of HL and CL, emerging machine learning approaches can help in improving accuracy and efficiency in real time. This paper provides improvements in energy load assessment of the buildings. It is the first is the in-depth study and analysis of design and structural attributes and their correlation with HL and CL, the novel methods based on ELM and its variants online sequential ELM(OSELM) to predict HL and CL. This study also proposes OSELM based online/real-time prediction when data is coming in stream The total 24 models have been developed including 12 models based on ELM and 12 models based on OSELM with different feature sets and activation functions. Models have been compared on the basis of accuracy, computational performance and efficiency with few existing models. The experimental results show that the proposed models learn better and outperform other popular machine learning approaches such as the artificial neural network(ANNs), support vector machine(SVM), radial basis function network(RBFN), random forest(RF) and existing work in the energy and building domain. [ABSTRACT FROM AUTHOR]

Occupant behaviour on air conditioning directly influences building energy consumption. Current building energy simulation typically assumes that occupants operate air conditioners ideally ignoring the stochastic characteristic of occupant behaviour, which leads to a large deviation of predicted energy performance from real consumption. This paper proposed a methodology framework for modelling occupants’ stochastic behaviour on air conditioning. This method combined measured data, statistical analysis and logistic regression to derive stochastic behaviour models that give the probability of when and above which temperature occupants may turn on air conditioning, at what temperature they may set and when they may turn off air conditioning. The behaviour models developed in this paper were further incorporated in widely used building simulation engine—EnergyPlus. The accuracy of the developed simulation model was validated against field measurement. Using this model, the cooling energy performance was simulated and compared with results from building energy standard based settings. The result shows that simulation using settings according to building energy standard over-predicts cooling load and total cooling energy requirements by 113% and 5.6 times respectively, which are very large discrepancies and may lead to a misunderstanding of energy savings potential of energy efficiency measures. The methodology developed in this paper has generality and can be extended and applied in other buildings for constructing behaviour models of air conditioning. The limitations of the current research as well as future research works were also discussed. [ABSTRACT FROM AUTHOR]

Solar-based radiant heating systems represent a sustainable, and relatively low-cost, technology to raise the temperature of the interior thermal mass of our buildings. Through the use of direct absorption solar thermal collectors, the same working fluid which absorbs the solar energy can be used to transfer the energy for storage in the thermal mass of the structure using a network of pipes embedded in concrete floors. This study investigates a promising working fluid which can be used in such systems – one which is based on multi-walled carbon-nanotubes suspended in normal base fluids. A major stumbling block affecting the wide spread use of carbon-nanotube nanofluids is their low dispersion stability at elevated temperatures, which significantly reduces the absorption capabilities of the nanofluids and could lead to clogging of the pumps used to circulate the fluids. In this paper, we report on a scalable UV-ozone (UVO) treatment technique to produce highly stable dispersions for the elevated temperatures experienced by working fluids in radiant heating systems. To probe suitability of UVO treated multi-walled carbon-nanotube (MWCNTs) for solar-assisted radiant heating systems, this paper investigates the effects of exposure time and temperature on stability, optical absorbance properties, the extent of functionalisation, and the photothermal conversion performance of UVO-treated MWCNT nanofluids. No agglomeration or degradation of the MWCNTs was observed at elevated temperatures (up to 150   °C), highlighting the stability of proposed nanofluids. [ABSTRACT FROM AUTHOR]

Green roofs can decrease the energy consumption and improve air quality and durability associated with a roofing material. Previous studies have conducted simulations of the energy performance of green roofs over a limited period, and important parameters such as leaf area index (LAI) was set at a constant value. To develop an energy performance model for a green roof with a variable LAI which is suitable for annual simulation, this paper proposes a method to integrate a seasonally variable LAI equation into a green roof model based on an improved Dickinson's equation. After verification with measured data, this equation has a more accurate temperature setting for calculating seasonally variable LAI, the average error and average relative error are improved from 0.34 to 0.09 and 39.3 to 7.1%, respectively. Thus, it can be applied in different climatic regions. To determine the differences of annual energy performance of green roof, this paper compares simulation results of constant and variable LAI values for a two-story building in Shanghai, China. The simulation is conducted on the EnergyPlus platform. The results show that the simulations of temperature, heat flux, and heat load of the building for green roof modeling differ considerably for a constant and a variable LAI. In summer, the calculated latent heat flux is usually underestimated and the sensible heat flux is usually overestimated. Moreover, if the selected LAI value is higher than that of actual data in winter, the calculated latent heat flux is overestimated and the sensible heat flux is underestimated. The simulation results are more relevant for a seasonally variable LAI. [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]

When modeling the energy performance of existing buildings, model calibration always serves as an essential and necessary step to ensure the accuracy and applicability of building models. Model calibration for detailed energy models, which is also known as calibrated simulation (CS), refers to the process of tuning model's input parameters to narrow down the mismatch between the simulation result and the real-monitored data of building energy consumptions. Two major problems of current CS are: (1) a successful calibration requires HVAC domain knowledge of modelers. (2) Traditional building calibration process is labor-intensive and time-consuming. To solve these problems, a normative energy modeling based quick auto-calibration approach is proposed in this study. This approach is able to reduce the modeling time and simplify the calibration procedures. Firstly, this paper demonstrates the working principles and the credibility of Normative Energy Modeling (NEM). Then, the methodology of the proposed quick auto-calibration approach is elaborated. The energy performance model of a large hotel located in Shanghai, China with NEM is used as a case study to investigate the effectiveness of the proposed quick auto-calibration approach. The simulation result of the case study suggests that the proposed approach can significantly simplify the procedures of model calibrations while still achieve a good accuracy specified by ASHRAE Guideline 14 [1]. Besides, the results further confirm that such method requires much less time and computational power for modeling, compared with other counterparts (e.g., “Autotune” calibration [2]). With the advantage of speed and accuracy, the auto-calibration proposed in this paper is promising to be applied in both engineering and research field. [ABSTRACT FROM AUTHOR]

In this paper, the problem of dispatching the operation of a distribution feeder comprising a set of heterogeneous resources is investigated. The main objective is to track a power trajectory, called the dispatch plan , which is computed the day before the beginning of operation. In this paper, we propose a method to optimally compute the dispatch plan so as to optimize the operation of the feeder while making sure to allocate enough local reserves to absorb deviations of the realizations. Indeed, during real-time operation, due to the stochasticity of part of the resources in the feeder portfolio, tracking errors need to be absorbed in order to track the committed dispatch plan. This is achieved by modulating the power consumption of a utility-scale battery energy storage system and of the heating, ventilation and air conditioning system of a commercial controllable building. To this end, a hierarchical controller is designed to coordinate these two controllable entities while requiring a minimal communication infrastructure. Due to the inherent different response times of these systems, the power injection of the electrical battery is controlled at a sub-minute time-scale so as to absorb high-frequency tracking errors and, therefore, deliver the dispatch service. At a slower time-scale, the controllable building is controlled to maintain the state of charge for the electrical battery at a scheduled level by means of a model predictive controller. The model predictive controller is designed in order to account for both comfort and operational constraints of the controllable building, as well as power limits for the electrical storage. The effectiveness of the proposed control framework is demonstrated by means of both an extensive simulation analysis, as well as a set of 12 full day experimental results on the 20 kV distribution feeder in the campus of the Swiss institute of technology in Lausanne, that is comprised of: 1) A set of uncontrollable resources represented by five office buildings (350 kWp) and a roof-top photovoltaic installation (90 kWp), 2) a set of controllable resources, namely, a grid-connected electrical storage (720 kVA–500 kWh), and a fully-occupied multi-zone office building (45 kWp). [ABSTRACT FROM AUTHOR]

A simple way to reduce energy consumption is to minimize heating use during unoccupied periods. This implies the possibility of adjusting the room temperature setpoint. However, systems with a large thermal capacity cannot follow sudden setpoint changes because of their thermal inertia. A model predictive control (MPC) allows the harnessing of this inertia in order to reduce heating costs and improve comfort. This advanced control technique is based on disturbances anticipation (occupation, weather conditions) and requires a model of the system which has to be controlled. Therefore, the use of such controller needs a reliable model that describes well the dynamics of the room on upcoming days. This paper presents a method for the selection of the model (type, level of complexity) to be implemented in a MPC controller to anticipate the control of a long time response floor heating system on a real building. The demonstration room and embedded systems serving as experimental support are presented. Short measurement periods are carried out to identify the model parameter values minimizing the gap between model output and measurement. Gray-box models based on electrical analogy and state-space representation are proposed. They are constructed from physical knowledge and then identified by choosing the most appropriate measurement series. A sensitivity analysis method (Morris) is used to improve the quality of the identified model which satisfies control criteria with two specific validation measurement series. In a complementary paper, the predictive controller integrating the selected model is compared to more conventional management strategies in simulation and on-site with the experimental building. [ABSTRACT FROM AUTHOR]

The main purpose of this research is to evaluate the thermal-comfort environment in an office building served by a liquid-desiccant and indirect-and-direct evaporative-cooler-assisted 100% outdoor-air system (LD-IDECOAS). This research presents a method for evaluating the thermal environment via a series of energy simulations using the TRNSYS 17 program, integrated with an engineering equation-solver (EES) program. The supply air (SA) temperature is estimated according to the LD-IDECOAS seasonal operation modes proposed in previous research. The indoor-air conditions are estimated under the assumption that the relative humidity of room air was maintained at the set values by auxiliary humidification systems. Then, the predicted mean vote (PMV) values are estimated using the given indoor environment conditions. In this paper, the indoor-air conditions and PMV values for each LD-IDECOAS operation mode are represented. A detailed analysis of the impact of the indoor-air conditions on the PMV is provided in this paper. Furthermore, the simulation results for LD-IDECOAS were compared with those for a conventional variable-air-volume (VAV) system to evaluate the thermal environment in a building served by LD-IDECOAS. The PMV values with LD-IDECOAS showed that the thermal environment in a conditioned space is generally in compliance with ASHRAE Standard 55. Consequently, it is concluded that using LD-IDECOAS in an office building can produce energy savings with an acceptable level of thermal comfort. [ABSTRACT FROM AUTHOR]

[Display omitted] • A split-degree days index is proposed for building energy use/climate classification. • Split-degree days index is shown to better estimate solar radiation and humidity data. • The estimation of building energy end-uses is improved using the split-degree days. • Split-degree days also showed improved results for high thermal mass and 24-hr models. • Split-degree days index maintains a high accuracy for varying base temperatures. Degree days have been widely used in different applications in buildings, such as estimating building energy use and climate classification for building energy standards. However, there are limitations with the use of conventional degree days that result in inaccuracies in estimating building energy consumption using degree day-based methods. This paper proposes a new method, the split-degree day method, that shows substantially improved results in the accuracy of the building energy use estimation compared to the conventional degree day methods. The analysis in 801 locations in the U.S. using regression models showed that the new, proposed split-degree day method in this paper, compared to the conventional degree day method, better accounts for the weather parameters and more accurately estimates end-uses. The split-degree days showed an improvement of over 5% in the accuracy of the total annual energy use prediction, 8% for predicting the heating energy use, 0.3% for predicting the cooling energy use, and 33% for predicting the fan energy use. Additionally, the analysis showed improved results for the model with higher thermal mass and the model with a 24-hour operating schedule. These improvements were due to the fact that the split-degree day method includes more information related to the weather characteristics of a location, which is missing in a conventional degree day calculation procedure that relies on aggregated data at daily intervals. Furthermore, as opposed to the conventional degree days, the accuracy of the estimations using the split-degree days are shown to maintain their high accuracy when the base temperature deviates from the optimal base temperature. The proposed method can be used as a more accurate alternative to the conventional degree days in different applications, including but not limited to building climate classification, building energy estimation, and weather normalization for building energy savings calculation. [ABSTRACT FROM AUTHOR]

[Display omitted] • 33 worldwide open datasets of city-level building energy consumption are summarized. • Representative applications of 198 papers using the collected datasets are analyzed and compared. • Policy implications are presented for using the open datasets to support policymaking. • Useful non-energy datasets about weather, building features, urban forms, and occupant-related factors are recommended. • Solutions to privacy issues are explored, including anonymizing methods and proper data aggregation. Data related to building energy use fuels the research and applications on building energy efficiency, which is an essential measure to address global energy and environmental challenges. However, in most cities, there is a lack of comprehensive and publicly accessible building energy use datasets with necessary temporal and spatial granularities to support urban building energy modeling, regional energy planning, city-level building performance benchmarking, and policymaking on building energy efficiency. Data owners and governments are facing challenges in determining which and how building energy use data should be disclosed at the city level and how to protect data privacy. This review paper provides insights to answer these questions based on a comprehensive and critical review of worldwide open datasets and their applications in the built environment context. Detailed information about the collected 33 building energy datasets is summarized and categorized. Studies identified into 11 subdomains using these open datasets are critically analyzed and compared. Potential policy implications based on the studies are also proposed. Moreover, non-energy datasets that are frequently used in research relevant to urban building energy use are also introduced. Solutions to privacy issues are discussed to address concerns from data publishers. Finally, significant conclusions are made to support the proper disclosure of city-level building energy data. This review study is valuable to urban building energy data disclosure, urban building energy modeling, and data-driven energy policymaking. [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]

[Display omitted] • Carbon emissions are explored in China's building operations from provincial perspective. • GDIM is employed to factorize ten affecting factors of CO 2 emissions in building sub-sectors. • CO 2 emissions of building sub-sectors are predicted with dynamic simulation. • The contribution of provinces to the change and peak of national emissions are discussed. Carbon emissions from building operations have a critical impact on achieving carbon peaking goal in China. However, the provincial emission performance in building operations are quite different and it is still unidentified how they affect the national emission change and peaking target, making national emission reduction target hard to implement at the provincial level. This paper explores the driving factors leading to emission changes and examines the prospective emission peaks in China and China's provinces by adopting generalized Divisia index method (GDIM) and the combination of scenario analysis and Monte Carlo simulation. Furthermore, the regional emission heterogeneity and the contribution of provinces to the change and peak of national emissions are discussed to identify regions and provinces that should be focused on emission monitoring. Results show that in China and most Chinese provinces, energy consumption of commercial buildings, energy consumption and floor space of urban residential buildings besides income improvement, and the per capita CO 2 emissions of rural residential buildings contributed greatly to emission growth. Under current policies, commercial and urban residential buildings in most provinces would fail to reach their emission peaks ahead of schedule. The urban residential buildings in the northern region, commercial and rural residential buildings in the eastern region caused higher CO 2 emissions. At the provincial level, Shandong, Shanxi and Hebei made the top contribution to total emissions of commercial, urban residential and rural residential buildings, respectively. Shandong and the provinces in north China of urban residential buildings and four provinces including Shandong, Guangdong, Hebei and Zhejiang of commercial and rural residential buildings had the significant impact on the uncertainty of the peaking time of CO 2 emissions. These findings provide a strong decision-making reference for Chinese government to formulate targeted regional emission reduction policies in building operations. [ABSTRACT FROM AUTHOR]

This paper examines the provision of demand-side ancillary services using building thermodynamics and heating ventilation and air-conditioning (HVAC) systems. In particular, we consider the secondary frequency control service where the load has to declare a power capacity and a nominal power at the beginning of the regulation period and then in real-time track the received regulation signal around its declared nominal power. A hierarchical control scheme is proposed in this paper. The local building controllers at the lowest level track the temperature setpoints received from the thermal flexibility controller which maximizes the flexibility of building’s thermal consumption. At the highest level, the electrical flexibility controller controls the HVAC system while maximizing the flexibility provided to the grid. The two flexibility control layers are based on robust optimization methods. A control oriented model of a typical HVAC system is developed, and simulations are carried out to demonstrate the efficacy of the proposed approach. Results show that extra flexibility may be attained by exploiting the coefficient of performance (COP) of the chiller. Furthermore, occupant comfort increases as a consequence of providing ancillary services. [ABSTRACT FROM AUTHOR]

This paper presents the building stock model CESAR (Combined Energy Simulation And Retrofitting), which is based on bottom-up modelling methodology for the development of sustainable energy transformation strategies for the buildings in Swiss districts. CESAR is composed of two sub-models: a Demand Model (DM) and a Retrofitting Model (RM). The DM is tasked with identifying the current energy demand of buildings in districts. It builds on geo-referenced information and available census data, and its flexibility allows it to be applicable to any kind of residential neighbourhood within Switzerland. The DM is based on an automated bottom-up modelling technique, which employs the dynamic building energy simulation software tool EnergyPlus as its simulation core to generate hourly energy demand profiles of individual buildings taking the interactions with neighbouring buildings (e.g. shading and solar inter-reflections) into account. Once current energy demands are calculated by the DM, the RM further offers the possibility to apply a set of energy transformation scenarios, based on the Swiss Energy Strategy 2050, to generate future demand and emission projections of districts including key economic indicators. Besides that, the building energy performance under climate change projections can be evaluated. In this paper, the tool is applied on three case study districts, an urban, suburban and rural area, within Switzerland and different transformation scenarios according to the Energy Strategy are investigated. Results revealed significant differences between the two implemented transformation scenarios, the Business as Usual (WWB) and the New Energy Policy (NEP). While in the WWB scenario, only a small number of buildings reaches the intended targets for primary energy and GHG emissions until 2050, the NEP scenario induces a much higher transformation of the districts. Besides that, the significance of the impact of global warming on future cooling demand is shown. [ABSTRACT FROM AUTHOR]

The use of radiant technology in attics aims to reduce the radiation component of heat transfer between the attic floor and roof decks, gables, and eaves. Recently, it has been shown that EnergyPlus underestimates the savings using radiant technologies in attic spaces. The aim of this study is to understand why EnergyPlus underestimates the performance of radiant technologies and provide a solution strategy that works within the current capabilities of EnergyPlus. The analysis uses three attic energy models as a baseline for comparison for EnergyPlus. Potential reasons for the discrepancies between the attic specific energy models and EnergyPlus are isolated and individually tested. A solution strategy is proposed using the Energy Management System (EMS) capabilities within EnergyPlus. This solution strategy produces similar results to the other attic specific energy models. This paper shows that the current capabilities of EnergyPlus are sufficient to simulate radiant technologies in attics. The methodology showcased in this paper serves as a guide for engineers and researchers who would like to predict the performance radiant technology in attics using the whole building energy software, EnergyPlus. [ABSTRACT FROM AUTHOR]

Many countries request to adopt measures for improving the buildings energy efficiency, for reducing the carbon emissions and for increasing the renewable energy use. The paper presents tools and procedures to support decision making according to the IEA-EBC Annex 56 project, “Cost-Effective Energy and Carbon Emissions Optimization in Building Renovation”. The first part of the paper describes the methodology proposed by the Annex for maximizing effects on reducing carbon emissions and primary energy use while considering the cost-effectiveness of related measures that consists in comparing renovation packages based on the results of a life cycle cost assessment. The optimization process focuses on the overall added values achieved in a renovation process, which means to identify the global quality improvement and further additional benefits (here called co-benefits) like comfort improvement (thermal, natural lighting, indoor air quality, acoustics, etc.), that allow to increase the value of the building. The second part describes the A56opt-tool, the tool developed (an excel file) as support for calculations based on the Annex 56 methodology in order to compare and to evaluate different packages of renovation measures. The kind of information needed as input, how to fill it in the worksheet and the whole process for optimization focus on the single output of each calculation till the identification of the optimal solution are also described. The last part presents the application of the methodology and calculation of the project in a case study, in order to show step by step the operative calculation process. [ABSTRACT FROM AUTHOR]

Occupant behavior is viewed as a main source causing the building energy performance gap between the predicted and the actual consumption. The nature of occupants’ energy behavior research requires a combination of social science and natural science, which indicates that a mixed methods design would be useful. However, researchers often do not know when and how mixed methods approach should be used. To fill this gap, this paper first reviewed the research methods adopted in 230 relevant articles published in the past decade. The results show that 83.48% of articles applied quantitative methods, followed by mixed methods (5.22%) and qualitative methods (0.87%) with rest being pure review or conceptual papers. This shows that researchers in the field of occupant behavior mainly adopt the objectivist philosophical position. Subsequently, an in-depth analysis of research methodologies was conducted in relation to worldviews and philosophical assumptions, and the advantages and disadvantages of qualitative and quantitative methods were discussed. Finally, a mixed methods research design framework was proposed as a point of departure for researchers to gain a comprehensive understanding of mixed methods design. It is expected that this framework could help researchers develop a proper mixed methods research design according to the nature of their research problem. [ABSTRACT FROM AUTHOR]

As demand response and energy flexibility are often suggested as key principles to facilitate high levels of renewable energy sources into energy markets, different studies evaluated the potential impact of energy flexibility in buildings. Nonetheless, due to differences in definition and quantification methodologies for energy flexibility, comparing results between such studies is difficult. With a review and applied evaluation of existing definitions and quantification methodologies this paper aims at assessing the applicability, benefits and drawbacks of each quantification methodology. The conducted review shows that energy flexibility definitions found in the literature have their particularities despite sharing the same principle that energy flexibility is the ability to adapt the energy profile without jeopardizing technical and comfort constraints. The survey of quantification methodologies reveals two main approaches to quantify energy flexibility. A first approach quantifies energy flexibility indirectly using past data and assuming a specific energy system and/or energy market context. The second approach directly predicts the energy flexibility that a building can offer to the energy system in a bottom-up manner. While applications for both approaches were identified, this paper focuses on the latter. By applying methodologies that follow this second approach to a common case study, three common properties of energy flexibility were observed: i) the temporal flexibility; ii) the amplitude of power modulation; iii) and the associated cost. [ABSTRACT FROM AUTHOR]

The aim of this paper is to evaluate and illustrate the energy saving potential of the façade addition on existing and low energy performing block buildings in different climatic contexts. To achieve this purpose, the paper illustrates some outstanding case studies on deep renovation through façade and volumetric additions, as reference possible solutions towards energy renovation. To further assess the energy potential of these transformations, the same solutions have been applied to a reference building in Bologna. In particular, a selected apartment of typical building block has been investigated and simulated in detail, to identify the buildings’ energy requirement and propose different retrofitting hypotheses towards nearly Zero Energy Buildings (nZEBs). Simulations of these different hypotheses resulted in corresponding diverse energy performances, from the very low grade of performance in “as built” scenario, up to nearly zero energy demand, for selected technological solutions applied in specific climatic contexts. To further estimate the energy impact the same apartment has been “extracted” from its original climatic context and energy simulations have been also carried out in two different climatic zones. Obtained results prove that façade additions are a very powerful solution towards the aim of zero energy in existing buildings. [ABSTRACT FROM AUTHOR]

This paper describes the results of experimental tests and computer simulation modelling aimed at evaluating the performance of an electrochromic (EC) window with respect to solar radiation control and the relative impact on the energy consumption of buildings of the residential type for two typical Italian climates. The research is carried out by a test-cell equipped with a small area EC double glazing unit and by a simulation program of buildings’ energy behaviour in transient regime. The experimental results show that EC devices which modulate solar radiation mainly by absorption, like the one investigated in this paper, generate secondary solar heat gains which entails a 20% decrease of the maximum potential energy flux reduction. Also, this effect could rise the temperature of the internal glass pane of the glazing to levels for which risk of thermal discomfort for the occupants may occur. The computer simulation modelling involves a residential building unoccupied during a large fraction of daytime in weekdays. The savings potential of the investigated EC window are calculated relative to a conventional clear float double glazing unit. Results show that the EC glazing may lead to a considerable decrease of the cooling energy demand (and of the total building energy consumption) in cooling dominated climates. The energy saving benefits become less marked in heating dominated climates and, for low values of the window-to-wall ratio, can be overcame by the increase in lighting and heating energy requirements that results in an increase of the total building energy demand. [ABSTRACT FROM AUTHOR]

In a traditional building design process (TDP), design variables are fixed sequentially, as opposed to integrated design process (IDP) which tends to avoid sequential design phases to create more sustainable buildings. First, a reference building is introduced and an energy model based on TRNSYS is presented to determine the energy consumption and comfort in the building. The model is validated based on energy bills, certified simulations and literature. Then, the paper performs an extended sensitivity analysis (SA) of 30 design variables with respect to different performance criteria related to energy consumption and comfort, based on a TRNSYS model. Three SA techniques were used, namely standard regression coefficients (SRC), partial rank correlation coefficients (PRCC) and Sobol indices. Results show that all three techniques yielded a similar ranking of the importance of the variables for most model outputs. Interactions between variables were identified with second-order Sobol indices. In the second part of this paper, a traditional design framework was adopted in which sets of variables were fixed sequentially. A SA was performed at each phase of the process, assuming fixed values for parameters chosen in previous design phases. Results show that fixing variables during the phases of a traditional design process tends to reduce the probabilities of finding low-energy consumption designs. Moreover, the influence of some variables was found to change during the design phases. [ABSTRACT FROM AUTHOR]

The development of innovative materials aiming to achieve energy savings is a main focus in the building technology sector. In this context, aerogel-enhanced products are often indicated as promising materials for increasing the thermal resistance of the building envelope. In particular, aerogel blankets have already started showing their effectiveness in retrofitting projects, while the development and adoption of aerogel-enhanced renders and aerogel-incorporating glazing systems is progressing. Based on the state of the art, this paper describes several new aerogel-enhanced systems that have been developed over the last few years at Ryerson University in Toronto, ON. In particular, the paper presents the recent results regarding aerogel-enhanced plasters, lightweight concretes, blankets, and glazing systems. Thermal characterization tests of these new materials confirm the superior performance for building retrofits. For example, the thermal conductivity of plasters with more than 80%vol. aerogel is below 0.025 W/(mK), a tenth of the respective value for traditional plasters, while mortars with more than 30%vol. aerogel show a thermal conductivity as low as 0.23 W/(mK). The newly presented aerogel-based systems are then assessed for the retrofitting project of an educational building located in Toronto. An extensive energy audit was conducted through measurements of the envelope thermal characteristics, the building airtightness, and several indoor environmental parameters. The audit helped to build an accurate energy model that was used for analyzing the energy consumptions of the building and assessing several energy saving measures. The study showed that high thermal resistance values could be obtained installing thin aerogel-enhanced products in the opaque and transparent envelope, with overall building energy savings up to 34%, with limited impacts and interruptions on the building functionality and internal usable space. However, the high costs of aerogel-enhanced products made their payback times of several decades and represented a barrier for the adoption of most of the systems presented in this paper. [ABSTRACT FROM AUTHOR]

This paper deals with the minimization of a building's external wall thermal transmittance, with the aim of improving the energy efficiency of the building. The wall's thermal transmittance must abide by the current legislation, but also suit the limitations of other construction parameters, mainly budget and thickness, but also time limit, workforce, number and thickness of the layers and availability of materials depending on the approach. The optimization is achieved formulating an Integer Linear Programming (ILP) problem involving the parameters mentioned above. Therefore, any available ILP solver can be run to obtain the best combination of the different materials and thicknesses for the layers, in order to minimize the thermal transmittance. This paper presents a case study of a common but representative external wall consisting of 6 layers, with more than 670,000 possible combinations of materials and their thicknesses. The study concludes with a comparison of the lowest thermal transmittance obtained for a selection of budget and thickness combinations for the mentioned wall. [ABSTRACT FROM AUTHOR]

The development of control strategies is a challenge for optimal use of low-temperature heat in complex energy systems. In the energy system of the considered building, several different combinations of active system components lend themselves to supply a given energy demand. Within preceding research, we transformed the considered building into a multi-functional test bench for control techniques that offers optimal conditions for the demonstration and evaluation of control strategies. This paper describes a control strategy for the complex heat pump system based on operation modes. It enables us to integrate a geothermal field into the system with respect to exergetic principles. The paper presents results of the control strategy's first year of operation. It correlates between active operation modes and the respective electrical consumption of the building. We derive the potential of the implemented operation modes for demand response applications. A mode-based control strategy enables the robust and efficient operation of complex building energy systems. We show that the integration of renewable energy sources becomes easy and flexible. [ABSTRACT FROM AUTHOR]

Calorimetric methods for the performance assessment (e.g. for the determination of the solar factor) of transparent building components have been largely applied in indoor laboratories under steady-state conditions and in outdoor test cells under dynamic boundary conditions provided by real weather. In the latter case the accuracy of the measurements depends significantly on the temporary storage of energy in the test cell envelope. An analysis by Pagliano et al. (2017) developed a dedicated lumped thermal model in Matlab environment in order to improve the design of calorimeters for the measurement of the solar factor by minimizing the energy storage effects in the envelope of the calorimeter and estimating precisely their entity. The developed model was based on literature studies on buildings’ dynamic energy simulations and adopted some common hypotheses used by existing building energy simulation software tools. However, when modelling light-mass and highly insulated buildings, such as test cell facilities, small variations in the power inputs can generate significant variations of the internal temperatures, challenging for the model to follow accurately. In order to verify the accuracy of the developed model in predicting the thermal behaviour of an outdoor test cell, an extensive validation work has been carried out. In particular, this paper summarises (i) an experimental validation carried out using a data set from the BESTLab facility, located at the research centre Électricité de France R&D Les Renardières (FR) and (ii) an intermodel comparison between the code developed in the Matlab environment and TRNSYS, a well-established building energy simulation tool. Concerning the validation at the BESTLab, the results show that the model is able to predict the temperature evolution of the internal air and of the internal surfaces of the envelope with good accuracy, with residuals lying within a range of ± 1 °C; reasons for discrepancies between measurements and predictions are discussed in the paper. As regards the intermodel comparison, the correspondence between the two software tools is generally good, with residuals lying most of the time within a range of ± 0.5 °C. The residuals are lower for the intermodel comparison, partly because input values are in this case not affected by uncertainty. Although TRNSYS and the developed Matlab code adopt some similar assumptions and simplifications, they also present some modelling differences that are highlighted in the paper. [ABSTRACT FROM AUTHOR]

While IEA EBC Annexes usually are focused on R&D about single energy technologies, their broad scale use in practice is of even higher importance to contribute to global energy goals. This practical application of low-carbon technologies on community scale has been the subject of Annex 51, carried out from 2010 to 2013. In this Annex, evaluating 25 community energy case studies of the 10 participating countries, a ‘Guidebook on Successful Urban Energy Planning’ has been extracted from these evaluations to directly address practical urban/energy planners and municipal decision makers. The main content of the Guidebook with respect to planning approaches is summarized in this paper, distinguishing between the different planning fields of ‘urban energy planning’, which is addressing whole cities and communities, and ‘local energy planning’, oriented to neighbourhoods or building clusters. The necessary link between both is emphasized, considering a city as an interconnected energy system requiring a holistic approach rather than a compartmented consideration. As a side effect, a general method to calculate the primary energy performance of buildings and neighbourhoods employing different energy systems, including energy efficiency or energy conservation technologies, was derived. Using appropriate system characteristics, such as seasonal performances, this approach can be applied for every energy system, and for every building or neighbourhood. It is presented in this paper supplying an example from one of the case studies. [ABSTRACT FROM AUTHOR]

The seawater source heat pump (SWHP) is a renewable energy utilization system. The beach well infiltration intake system (BWIS) effectively improves the stability, reliability, and energy efficiency of SWHP systems in cold climate areas. BWIS research requires a multidisciplinary approach that involves both hydrogeology and heat transfer theory. There are many factors influencing the energy consumption and life-cycle costs of the systems, with each factor having many possible values. This paper aims to determine the degree of influence of ten representative factors of BWIS: specific heat capacity of rock-soil, rock-soil density, thermal conductivity of rock-soil, void fraction of rock-soil, rock-soil permeability, beach well radius, site length, site width, row number of beach wells, and column number of beach wells. In this paper, a BWIS seepage and heat transfer model is established. Based on the model, an orthogonal design optimization method is presented and analyses are conducted for heat pump unit energy consumption, seawater pump energy consumption, and economic cost for various conditions using MATLAB code. The results indicate that a greater number of beach wells is not always better and the number and placement of beach wells should be scientifically and objectively optimized by the orthogonal design method. The optimization method can scientifically guide engineering design for BWIS and offset the design deficiency that results from the current practice of only using a hydrogeological report of randomly selected test wells. [ABSTRACT FROM AUTHOR]

With around 1–2% annual replacement of the UK’s housing stock, housing retrofit must play a major role in reducing future energy use and CO 2 emissions. This paper presents a whole-house approach for energy retrofit for five houses located in South Wales. This ‘systems based’ approach combines reduced energy demand, renewable energy supply and battery storage. The paper describes a combination of energy modelling, using the building energy model HTB2, and field measurements to analyse the performance of the houses before and after retrofit. The results indicate that significant reductions in energy use, CO 2 emissions and energy costs can be achieved using a whole house approach, combining energy efficiency with building integrated renewable energy generation and energy storage. CO 2 emission reductions are estimated to be in the range of 50–75%, with cost savings of £402 to £621 per year. The cost of carrying out the retrofitting ranges from £23,852 to £30,510. Although retrofits are still relatively expensive in relation to their annual cost savings, there are multiple benefits relating to reducing fuel poverty, reducing electricity grid stress and contributing to national CO 2 emission reduction targets. Also, as costs of measures are further reduced and energy prices likely to rise in future, the cost balance will change more in favour of whole house retrofit. The paper demonstrates the advantages in using a combination of energy simulation and field monitoring to investigate the performance of buildings in use, which in this case concerns the impact of carrying out energy retrofits in housing. [ABSTRACT FROM AUTHOR]

Several studies have shown that the actual thermal performance of buildings after construction may deviate significantly from its performance anticipated at design stage. As a result, there is growing interest in on site testing as a means to assess real performance. The IEA EBC Annex 58-project ‘Reliable Building Energy Performance Characterisation Based on Full Scale Dynamic Measurements’ focused on on site testing and dynamic data analysis methods that can be used to characterise the actual thermal performance and energy efficiency of building components and whole buildings. The research within this project was driven by case studies. The current paper describes one of them: the thermal characterisation of a round robin test box. This test box can be seen as a scale model of a building, and was built by one of the participants. During the project, its fabric properties remained unknown to all other participants. Full scale measurements have been performed on the test box in different countries under real climatic conditions. The obtained dynamic data has been distributed to all participants who had to characterise the thermal performance of the test box’s fabric based on the provided data. The paper compares the result of different techniques, ranging from a simple quasi-stationary analysis to advanced dynamic data analysis methods, which can be used to characterise the thermal performance based on on-site collected data. [ABSTRACT FROM AUTHOR]

Combined cooling, heating and power (CCHP) is a promising technology to provide energy for various energy consumers for its good economic, energy and environmental performance. However, the widely promotion of CCHP is hindered by its complex design and varying performance under different situations. In this paper, the influence of energy demands, operation strategy and thermal energy storage strategy on optimal design and performance of CCHP systems is studied by using statistical methods 13,472 energy demand samples for 16 types of building across 7 climate zones in the U.S. are used in the paper. On the whole, building energy demands are the most influential factor. Among the building types, the performance of large hotel, hospital and outpatient healthcare is outstanding. Among the climate zones, CCHP systems have better performance in cold and very cold climate zones. For operation strategies, the ATCSR and PESR values of the FTL mode are averagely less than those of the FEL mode, and the differences between the two modes for ATCSR and PESR are on average 0.25% and 1.03%, respectively. Besides, the use of thermal energy storage can improve the integrated performance of CCHP. In the FEL-TES mode, the average increments of ATCSR and PESR are 0.82% and 0.79%, respectively. In the FTL-TES mode, the average increments of ATCSR and PESR mode can reach 3.42% and 3.46%, respectively. The relationship between building energy demand indexes and the design and performance parameters of the CCHP is also explored by stepwise regression method to build regression models and determine the most effective parameters. [ABSTRACT FROM AUTHOR]

Reducing energy consumption in buildings and increasing renewable production are key goals of European policies to achieve a sustainable and competitive low-carbon economy by 2020 and beyond. Non-residential buildings constitute a heterogeneity sector characterized by high energy consumption and various building types, sizes and energy characteristics over Europe. This paper presents the overall results of the data collected by the GreenBuilding Programme (GBP), launched in 2006 to promote and improve energy efficiency in new and existing European non-residential buildings. The GPB involved building owners willing to adopt energy efficiency measures to decrease energy consumption of their buildings by of at least 25%. Based on voluntary participation, hundreds of partners joined the project, which collected data from more than a thousand buildings of different age, size, use and type (such as offices, hotels, and industry). This paper provides an overview of the Programme and its main results up to its completion in 2014. The paper focuses on building characteristics, energy performance, efficiency measures and energy savings, which are globally estimated to be around 985 GWh/year. A more detailed focus is then given to office buildings, which represent the most frequent building category in the Programme. Case studies are presented to show best practices in various countries with consolidated energy efficiency policy strategies. The paper categorises the main technological measures related to envelope, appliances and systems. It shows how a wide range of technologies are becoming an integral part of buildings and how technology plays a major role in exploiting the massive potential benefits of reducing building energy consumptions. The analysis of the results generates a reliable snapshot of European non-residential building stock. [ABSTRACT FROM AUTHOR]

This paper provides a study of the optimal scheduling of building operation to minimize its energy cost under building operation uncertainties. Opposed to the usual way that describes thermal comfort using a static range of air temperature, the optimization of a tradeoff between energy cost and thermal comfort predicted mean vote (PMV) index is addressed in this paper. In order to integrate the calculation of the PMV index with the optimization procedure, we develop a sufficiently accurate approximation of the original PMV model which is computationally efficient. We develop a model-based periodic event-triggered mechanism (ETM) to handle the uncertainties in the building operation. Upon the triggering of predefined events, the ETM determines whether the optimal strategy should be recalculated. In this way, the communication and computational resources required can be significantly reduced. Numerical results show that the ETM method is robust with respect to the uncertainties in prediction errors and results in a reduction of more than 60% in computation without perceivable degradation in system performance as compared to a typical closed-loop model predictive control. [ABSTRACT FROM AUTHOR]

Energy pile is a novel ground heat exchanger (GHE) of ground source heat pump (GSHP) system, and the spiral coils are set into pile to form this type of GHE. However, the on-site heat transfer experiments combined with engineering projects are not much, and the corresponding validation of model is a little. This paper describes both heat transfer experiments and models of energy pile. During the experiments, some parameters of circulating fluid of spiral coils are recorded, and meanwhile the thermal resistors are installed at the pile’s surface to observe the temperature response induced by spiral coils. The heat transfer models of energy pile are explained and the corresponding characteristics are investigated. Afterwards, the comparisons between experimental data and model’s results are made to explore the differences, the difference is small and therefore the heat transfer models can be validated. Thus, the validation is a significant contribution and the model can provide guideline for project design; the research of the paper is helpful to promote further development of GSHP system. [ABSTRACT FROM AUTHOR]

There has been general recognition within the construction industry that there is a discrepancy between the amount of energy that buildings actually use and what designers considered that they should use. This phenomenon is termed “The Performance Gap” and is normally associated with new buildings. However, existing and older buildings contribute a greater amount of operational carbon. In response to the Performance Gap, CIBSE have developed the TM54 process which is aimed at improving energy estimates at design stage. This paper considers how the TM54 process can also be used to develop energy management procedures for existing buildings. The paper describes an exercise carried out for a university workshop building in which design energy use has been compared with the actual building energy use and standard benchmarks. Moreover, a sensitivity assessment has been carried out using different scenarios based on operation hours of building/equipment, boiler efficiency and impact of climate change. The analysis of these results showed high uncertainty in estimates of energy consumption. If carbon challenges are to be met then improved energy management techniques will require a more systematic approach so that facilities managers can identify energy streams and pinpoint problems, particularly where they have assumed responsibility for existing buildings which often have a legacy of poorly metered fuel consumption. [ABSTRACT FROM AUTHOR]

Energy efficiency is one of the main pillars of the European energy strategy and it involves all the economic sectors. The present study proposes an analysis of the energy saving opportunities available in the Italian hotel sector, which has a relevant importance in the national context. The paper introduces a comprehensive model of the Italian hotel sector developed in the LEAP (Long-range Energy Alternatives Planning) environment. The first aim is to estimate the baseline of the consumption, then to evaluate the maximum potential energy saving and, finally, to assess the implementation of a realistic energy efficiency scenario. The paper demonstrates that it may be possible to achieve primary energy savings of 1.6 TWh (13%) in 2030 by implementing financially sustainable energy efficiency measures. [ABSTRACT FROM AUTHOR]