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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]

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 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]

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]

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]

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]

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]

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]

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]

In recent decades there has been a growing awareness regarding energy consumption in buildings. Unfortunately, at a time when all building actors should get involved in the challenge to reduce energy consumption, designers cannot rely on effective tools to help them in their decision making process concerning airtightness. This literature review allows the identification of two important issues: new airtightness predictive models are complex to develop and existing airtightness predictive models do not meet the needs of designers and contractors. This paper is divided into three main parts in addition to the introduction and the conclusion. The first part deals with the key concepts of infiltration and airtightness, the second part with influencing factors and the third part with airtightness predictive models. These different chapters highlight a need for standardization regarding the metrics used for data presentation, parameters definition and statistical quantification. The lack of standardization hinders the development of a new airtightness predictive tool for designers and contractors. Along with the problem of standardization, supervision and workmanship are parameters that are difficult to model. Their significant impact can explain why designers and contractors find some existing models unreliable. This paper concludes that none of the existing models can be used in their present form as design tools. Further work should focus on the standardization of data presentation and on the development of a new airtightness predictive model. The first step in the development of such a model is to draw an appropriate classification of “air paths.” [ABSTRACT FROM AUTHOR]

Facing the challage of energy conservation and emission reduction in the building sector, most energy saving strategies of central heating only focus on the performance improvement of building envelope, ignoring the impact of energy use behavior. This paper proposed a building energy conservation strategy based on energy use behavior analysis, which provides a perspective for in-depth exploration of building energy conservation. After investigating a typical university in the northern China, the energy use behaviors were characterized and two different DeST energy consumption models before or after considering energy use behavior were established. By comparing the results calculated by these two models, the impact of energy use behavior analysis on building energy consumption was quantitatively analyzed. The results show that the heating energy consumption and carbon emission can be reduced by 23.28% and 23% respectively through the proposed strategy based on energy use behavior. Therefore, the analysis of energy use behavior can provide a theoretical basis for heating operators to make decisions on energy supply regulation. With central cooling and heating further popularizing in the future, the research methodology of this paper has more extensive reference value for energy conservation and emission reduction strategies in the building sector. [ABSTRACT FROM AUTHOR]

• Obtaining the optimal interpolation method for adjacent sites. • Proposing the method for revising meteorological data at city scale. • Verifying the accuracy of the method by energy consumption simulation. In the development process of building energy conservation design, the correct provision of local Typical Meteorological Year (TMY) data is a prerequisite and basic work to evaluate building energy consumption, which directly affects the fine use of outdoor data for building energy conservation. Based on the recorded and observed data of meteorological stations in China, the acquisition and correction methods of TMY were studied by mathematical statistics and target searching, and the building energy consumption simulation of urban office buildings was conducted to verify the accuracy of the method, including:(1) Reviewed the generation method for TMY and the acquisition of data.(2) Based on the existing TMY data, the best spatial interpolation method of adjacent stations is studied by using the standard deviation method, and the selection method of the best number of stations on a large regional scale is given.(3) An improved method of urban environment TMY is proposed. The dry bulb temperature and relative humidity of the building site are corrected to generate TMY under Urban Heat Island (UHI) effect. The research in this paper improves the coverage and accuracy of urban TMY data and supplies basic research support for building energy-saving designs. [ABSTRACT FROM AUTHOR]

Extensive research works have been carried out over the past few decades in the development of simulation tools to predict the thermal performance of buildings. These validated tools have been used in the design of the building and its components. However, limited simulation tools have been developed for modeling of district energy systems, which can potentially be a very laborious and time-consuming process. Besides many associated limitations, providing a realistic demand profile of the district energy systems is not a straightforward task due to high number of parameters involved in predicting a detail demand profile. This paper reports the development of a simplified model for predicting the thermal demand profile of a district heating system. The paper describes the method used to develop two types of simplified models to predict the thermal load of a variety of buildings (residential, office, attached, detached, etc.). The predictions were also compared with those made by the detailed simulation models. The simplified model was then utilized to predict the energy demand of a variety of districts types (residential, commercial or mix), and its prediction accuracy was compared with those made by detailed model: good agreement was observed between the results. [ABSTRACT FROM AUTHOR]

Many retrofit projects are being carried out in existing buildings to reduce energy consumption. However, the energy consumptions before and after retrofit need to be known in order to evaluate such retrofit projects. Even though the energy consumption after retrofit can be determined through measurement, the energy consumption before retrofit cannot be known. This study is to more easily estimate energy usage prior to the retrofit. Generally, dynamic simulation or regression model should be used to estimate the energy consumption of buildings before retrofit. However, existing regression models have no way to calibrate the model if it is inaccurate. In this paper, we use a clustering technique to improve the accuracy of the regression model. The estimation of energy consumption before retrofit is referred to as “baseline model” and the inverse model is used to create this baseline model. The inverse model is created through monthly data, daily data, and other similar data. In this study, the inverse model was created through daily data and the baseline model was derived from it. The conventional change-point Model and the cluster inverse model presented in this paper were compared and evaluated with the criteria presented through M&V (Measurement and Verification). The results suggest that the cluster inverse model which reflects the characteristics of data is more appropriate when the baseline model is derived from daily data. [ABSTRACT FROM AUTHOR]

HVAC systems in buildings are composed of many subcomponents which consume energy in huge amounts. In recent years, energy consumption becomes very important aspect due to the lack of energy resources and environmental reasons. In terms of energy consumption, the components of HVAC systems account for large portion of total energy used in buildings. Therefore optimization of energy consumption in HVAC applications is an essential requirement in terms of thermodynamic and economic point of views. Besides, the efforts for decreasing energy consumption turn into economic recovery. It also provides benefits for human health and cleaner environment. In this paper, as originality, thermodynamic and economic analyses of an existing social and cultural building which has a heating and cooling area of 8852 m 2 are presented by comparing of a conventional HVAC and a VRF system. A novel contribution is given to the open literature by comparing two systems with actual data measured from the existing system. The other originality is to apply and test a VRF system to a complex-structured building. This study is a rare one which contains insulation, heating and cooling accounts of a building together. In this paper, VRF system is modelled to the existing building for the comparison of the conventional HVAC system. Both systems have been compared in terms of heating and cooling capacity, initial, operation and maintenance costs. It is found that the VRF system is more economic and efficient such that the VRF system is found to have 44% cost profit when compared with the conventional HVAC system. [ABSTRACT FROM AUTHOR]

Lowering the embodied carbon dioxide equivalent (embodied CO 2 e) of buildings is an essential response to national and global targets for carbon reduction. Globally, construction industry is developing tools, databases and practices for measuring embodied CO 2 e in buildings and recommending routes to reduction. While the TC350 developed standardized methods for the assessment of sustainability aspects in construction works and Environmental Product Declarations, there is no consensus on how this should be carried out in practice. This paper evaluates the current construction industry practice through a review of both academic and professional literature, and through focus groups and interviews with industry experts in the field. Incentives in the available building codes, standards, and benchmarks are also analysed, as are the existing methodologies, tools and datasets. The multiple data sources are used to identify the barriers to the effective measurement and reduction of embodied CO 2 e in practice. This paper recommends that Governments mandate for improved data quality and support the development of a transparent and simplified methodology. [ABSTRACT FROM AUTHOR]

Application of building integrated photovoltaic (BIPV) technology in the building envelope gives an aesthetical and modern appearance. BIPV is a practical, innovative and promising technology for net zero emission buildings. This paper introduces the best in class of the BIPV products and their properties along with international guidelines and testing standards. BIPV products for rooftops, façades and windows have been highlighted in this paper. The properties of BIPV products incorporate solar PV efficiency, V oc , I sc , P max and fill factor (FF). The life cycle sustainable assessment of BIPV module has been reviewed by examining energy payback time and GHG emission. [ABSTRACT FROM AUTHOR]

This paper reviews occupancy based model predictive control (MPC) for building indoor climate control. Occupancy behavior in buildings is stochastic and complex in nature. With better understanding of occupancy presence in rooms and spaces, advanced controls, such as MPC, can be designed to achieve a more energy efficient operation, compared to more traditional control methods, while comfort is maintained. This paper starts with an overview of traditional controls implemented in buildings, and importance of occupancy based controls. Various control-oriented building modeling methods including physics-based and data-driven models are reviewed. Later on, a comprehensive review of MPC in terms of control theory, objective functions, constrains, optimization methods, system characteristics and various types of MPC is presented conducted. In principle, MPC finds an optimal sequence of control commands to optimize an objective function, considering system model, disturbances, predictions and actuation constraints. Lastly, occupancy based controls including commonly used rule-based and latest model-based controls are reviewed. In addition, a few experimental studies are presented and discussed. The paper presents a holistic overview of occupancy-based MPC for building heating, ventilation, and air conditioning (HVAC) systems, and discusses current status and future challenges. The purpose of this paper is to provide a guideline forresearchers who would like to conduct similar studies to have a better understanding of established research methods. [ABSTRACT FROM AUTHOR]

Harvesting daylight for improving building energy performance has become an important issue in recent years. Most energy simulation tools use a Daylight Factor (DF) based algorithm to capture the complexity of daylight behaviors. However, DF has a limitation for fully accounting realistic daylight conditions, and several modifications or integrations with other supporting tools were developed to compensate for this limitation. This paper uses the Kriging method to predict daylight conditions for a whole year, and couples this method with energy simulation tools. Kriging is a group of geo-statistical techniques used to interpolate the value of a random field at an unobserved location from discrete observed values at nearby locations. In previous research, the Kriging method showed promising outcomes; that result was significantly better than current daylight modeling in energy simulation tool, and very close to the results from advanced physics-based daylight simulation tool. However, Kriging also comes with certain limitations that require further investigation. One major hurdle was Kriging’s long computational time compared to current daylight models in energy simulation tools. For this reason, this paper aims to find possibilities to reduce computational time to realistic levels that can be applicable in practice. Furthermore, it proposes a method to integrate Kriging-based daylight model with an energy simulation tool that can plot hourly indoor light distribution. This proposal obtains more realistic results than current energy simulation daylight models, while reducing computational expense. [ABSTRACT FROM AUTHOR]

Abstract To achieve energy efficient Heating, Ventilation and Air Conditioning (HVAC) systems in buildings it is essential to enhance the designs of their various integrated mechanical and electrical components and to control and operate plant optimally. More efficient HVAC systems lead to a significant reduction in power consumption in buildings, which is significant bearing in mind that buildings consume over 40% of the total power consumption in many developed countries. This Special Issue on energy efficient HVAC systems was open to all contributors in the field of heating, ventilation and air conditioning systems in buildings. The invitation was for novel and original papers which extend and advance our scientific and technical understanding of efficient energy HVAC systems including Heat Pumps, water heating and cooling systems in buildings, efficient air conditioning systems, efficient component designs, energy storage (heating and cooling) and regenerative processes. In the event, all these topics were covered in the very wide-ranging submissions accepted but interesting papers on other aspects of HVAC systems and operation were also received. [ABSTRACT FROM AUTHOR]

Significant energy savings can be achieved by operating heating, ventilation, and air conditioning control systems with indoor occupancy measurement information. This paper presents a novel plug-and-play occupancy sensing method which will enable temporal minimization of building energy consumption to meet building usage behavior without privacy concerns. The proposed wireless occupancy sensing platform is based on long-wave infra-red (LWIR) focal-plane arrays (FPAs), or thermal imagers, that detect thermal energy rather than visible light. We developed an advanced sensor package consisting of multiple thermal imagers with low-cost optical enhancements to increase field of view and increase sensitivity to occupant detection (filtering building clutter). These imagers can be coupled with radio frequency and ultrasonic-based radar to enhance data collection at key occupant zone boundaries to improve accuracy. Standard filtering and estimation techniques from the image processing and computer vision communities are introduced to overcome the accuracy issues suffered by traditional PIR based sensing, especially when occupants remain relatively still. Accurate low-level counting of individuals can be achieved with minimal impact on privacy. The proposed occupancy detection method can work as a retrofit to enable real-time understanding of the building operational state and usage behavior. Sensor data obtained from real test building zones was used to test the efficacy of the method. [ABSTRACT FROM AUTHOR]

Highlights • The paper studies the impact of urban parks on reducing urban temperature. • Findings reveal that urban park construction reduces building energy consumption. • There is a limit distance to the reduction of energy consumption due to urban parks. • Change of urban characteristics due to park construction affects energy consumption. Abstract A change in the thermal environment of an urban area affects health, living conditions, and energy consumption. In urban planning, urban parks are one of the methods for improving the thermal environment and saving cooling energy. Urban park construction can mitigate temperature, but it also causes urban development by increasing local attractiveness. To achieve efficient energy saving through parks in urban planning, the purpose of this study is to investigate the relationship between building energy consumption and urban characteristics both before and after the construction of an urban park. This study targeted Seoul's Gyeongui line forest, which was recently converted into a linear park on the former railway as an urban regeneration project. We analyzed the relationship between energy consumption and urban characteristics using a regression model, focusing on the changes before and after the construction. In this study, urban characteristics include environment, building physical characteristics, and economic variables. The results show that the construction of the urban park reduced not only temperature but also building energy consumption. The energy reduction effect of the park was limited to a marginal distance. Meanwhile, the urban park construction caused land prices to rise and prompted new development, and this changed the urban characteristics of the area and affected energy consumption. Despite changes in urban characteristics, urban park planning is an effective methods of reducing the energy consumption involved in cooling urban areas. We recommend comprehensive consideration of the urban factors when making park policy to reduce urban temperature and energy consumption. [ABSTRACT FROM AUTHOR]

Abstract In recent years, technological advances have substantially extended the capabilities of building automation. Despite the achieved advances, evidently, automation have not been widely adopted by occupants in buildings. To enhance automation adoptability, automation procedure in buildings should involve determination of user's preferred automation levels, in different conditions and control contexts and learning preference dynamics in time. In line with this motivation, in this paper we introduce a building automation that learns occupant's preferences continuously to fully or partially control the service systems in buildings based on a set of dynamic rules that are generated with the insight about user's preferences and activities. The algorithmic components of our proposed automation include (1) dynamic command planning, (2) adaptive local learning, and (3) iterative global learning. In order to evaluate these algorithms, we used a combination of real and synthetic user activity and preference data from an office with five occupants and an apartment with one occupant. Based on our results from evaluation of adaptive local learning, after a certain number of days (i.e., 8.5 days in average) the accuracy of predicting participants' preference reached to an acceptable value (i.e., above 85%). About 24% to 75%, 5% to 45%, and 6% to 49% of the total daily energy consumption of the participants could be saved using full automation, adaptive automation and inquisitive automation, respectively. Our results for evaluating iterative global learning algorithm showed that adaptive automation has the highest sum of the rewards from achieved benefit and user satisfaction and inquisitive automation has the second highest reward values. Full automation and no automation came in third and last spots, respectively. [ABSTRACT FROM AUTHOR]

Highlights • A methodology is introduced to rank a set of buildings based on energetic performance of occupants. • Ranking is done in two levels, each one gives specific information about occupants of a single building. • The underlying factors that create the ranks are examined to give occupants clues on how to improve their rank and reduce energy consumption. Abstract Identifying the impacts of occupants on building energy consumption has become an important issue in recent years. This is due to the interrelationship of influencing factors such as urban climate, building characteristics, occupant behavior, and building services and operation, which makes it challenging to identify the role of occupants in energy consumption. The research problem in this study lies in the fact that the occupants of a building may not be cautious regarding energy savings, and there exists no ground to assess their energy consumption behavior. One solution is the development of a systematic comparison procedure between similar buildings. This paper introduces a new procedure for comparison between occupants of several buildings to show the rank of each building among others and suggest occupants on reducing their energy consumption and improving their rank. The proposed framework is developed based on multiple data-mining methods, including clustering, association rules mining, and neural networks. The proposed methodology is composed of two levels. The first considers the amount of energy usage by occupants after filtering effects unrelated to the occupant behavior. The second ranks the buildings in terms of achieved and potential savings during the time under investigation. To demonstrate the application, the methodology was applied on a set of monitored residential buildings in Japan. Results suggest that the proposed method enhances the evaluation of buildings' energy-saving potential by revealing the occupants' contribution. It also provides diverse and prioritized strategies to help occupants manage their energy consumption by revealing the building energy end-use patterns. Graphical abstract Image, graphical abstract [ABSTRACT FROM AUTHOR]

Highlights • Our equivalent wall method uses the structure factors and harmonic heat fluxes. • The method is tested on three 2-D thermal bridges. • The comparison is based on numerical simulations results. • For a realistic, severe or step evolution of outside temperature, results are precise. • Equivalent walls results are much better than those for a classic 1-D evaluation. Abstract This paper presents a mixed method to determine a 1-D three-layer wall having the same static and dynamic behaviours as a multidimensional thermal bridge. It is based on the calculations of thermal resistance, heat capacity, structure factors and an objective function using harmonic heat fluxes features. This mixed method is applied to three 2-D details. The heat flux through inner surface is analysed over time for a step solicitation and for given boundary conditions: a sinus evolution of the inside temperature and a severe or a more realistic evolution of the outside temperature. Results are really satisfactory, evolution of heat flux through the thermal bridge is close to that of the corresponding equivalent wall. For an outside temperature profile (T e) close to real data, the error on integral value of heat flux is less than 1% in each case. The results for equivalent walls are significantly better than for a classic 1-D evaluation: for a severe evolution of T e the average error is 6 to 28 times lower in the tested cases. [ABSTRACT FROM AUTHOR]

Abstract Sensitivity analysis (SA) can be applied to building energy models (BEM) to identify which input parameters that drive the majority of the model output variation. The screening-based Morris method is often applied for this purpose; however, consideration regarding the effect of the user-defined number of levels (p) and trajectories (r) on the obtained results are rare. This paper investigates how the choice of p and r affects the outcome of a SA using the Morris method on a high fidelity BEM. The results indicates that the Morris method was not able to replicate the ranking from the variance-based Sobol' method no matter the choice of r and p. It was, however, able to identify groups of input parameters (parameter clusters) most sensitive to the model output variability, but it required significantly more r than usually applied in studies featuring the Morris method. The reason is that marginal differences in absolute values of elementary effects (the sensitivity indices of the Morris method) for some input parameters may lead to a change in ranking position several times as the number of r increases. Users of the Morris method must therefore not be predetermined on the size of the parameter cluster; instead, they must make a visual assessment of the convergence of the parameter ranking to qualitatively determine the appropriate size of parameter cluster. The final recommendation for future studies deploying the Morris method for SA applied to a high fidelity BEM is to choose p ≥ 4 as it seems to lead the analysis towards a more truthful ranking, and then run simulations in steps of r = 100 when making the visual assessment to determine convergence and the size of parameter cluster. The identified need for more r questions the general notion that the Morris method is a computationally efficient screening method in terms of absolute time use. However, the Morris method is still much more computational efficient than a Sobol'-based analysis if the purpose of the SA is to identify a cluster of input parameters most sensitive to the model output variability. [ABSTRACT FROM AUTHOR]

Highlights • The first city-level building energy efficiency benchmarking system for China. • A model considering the influence of operation parameters on energy consumption. • A systematic methodology of building energy benchmarking is proposed. • The model is a valuable analysis support tool for building energy managers. Abstract The city-level public building energy efficiency benchmarking system has an important guiding value for building energy-saving work, especially for Beijing, with its high energy-consumption density and both long heating and air-conditioning periods. This paper analyzed the characteristics of large-scale office buildings in Beijing and gives a detailed description of the process of establishing a public building energy efficiency benchmarking system for large-scale office buildings in Beijing, China, including data investigation and verification, Energy Usage Intensity(EUI) calculation, determining independent and dependent variables, developing and testing the benchmarking model, and deriving the benchmarking rating table. Then the first city-level public office building energy efficiency benchmarking system in China is established based on 88 large-scale office buildings in Beijing. The results showed that the model's performance index R2 is 0.667 and gives a good representation. The process has a strong potential for replication for other cities in China and even for a national energy-consumption evaluation system. [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]

In Germany, policy-induced energy efficiency improvements typically aim at reducing primary energy consumption. Private households, on the contrary, pursue the maximization of wellbeing or, in microeconomics jargon, the maximization of utility of the occupants. There is a marked difference between upfront-calculated energy performance ratings (EPRs) and actual heat energy consumption (HEC). From an energy and environmental policy point of view, deviations of energy consumption from ex ante calculated EPRs is problematic, as it jeopardizes their usefulness for (prospective) homeowners, policy-makers and researchers relying on EPRs as a guidance. The EPR-HEC gaps reported are, apart from deviations from the mean aggregate values (i.e. heterogeneity), often attributed to anticipated or unanticipated behavioral effects. From an energy economist's point of view, energy rebound induced by lowered costs per unit of energy service due to increased energy efficiency is one explanation. The related literature almost entirely treats building-specific EPRs as universal standards, trying to explain the empirically observed discrepancies. In this paper, we investigate to what extent the current EPR scheme in place in Germany today can address behavioral issues. To this end, based on two different multi-family housing data sets for Germany and regression analysis, we empirically investigate the deviations between EPRs used in the regulatory norms and the HEC levels observed in reality. We find evidence that it is not necessarily the behavioral dimension, but rather the static and mostly technically guided calculation of the EPRs itself that accounts for the major part of the deviations. We conclude that there is indeed a need for further improvements in the field of EPR regulation and methodology. [ABSTRACT FROM AUTHOR]

This paper presents an evaluation method for a multi-chiller system’s operation performance. It develops the near-optimal performance map as the evaluation benchmark covering all different cooling conditions of the multi-chiller system. For that map, a new data-based chiller power model using a dedicated set of coefficients for each of different cooling conditions is developed to supplement load-power data into the history operation data of the multi-chiller system. According to the evaluation benchmark, an evaluation index I s ˜ , is defined to show the potential improvement in the operation performance of the multi-chiller system. The near-optimal performance map is also used to analyze the distribution of the multi-chiller system’s operation conditions. To validate the proposed evaluation method, three operation strategies for an existed multi-chiller system are evaluated. The data-based chiller power model is proved accurate enough in the use of the evaluation. According to the evaluation results, the three strategies are compared and advised. The validation demonstrates that the proposed method is capable to evaluate the operation performance of the multi-chiller system. [ABSTRACT FROM AUTHOR]

Virtual in-situ sensor calibration (VIC), using Bayesian MCMC with system models, can be applied to large-scale building sensor networks in order to calibrate multiple working sensors including virtual and physical sensors. Using the calibration strategies herein, VIC methods work to overcome various systematic errors (from simple to troublesome) that cannot otherwise be handled by a conventional calibration. Thus, it is important to understand and evaluate the VIC strategies in a whole system with various error conditions to ensure reliable performance of VIC in the operational stage. This study applied individual calibration strategies to a whole building system (a LiBr–H 2 O refrigeration system), and their effectiveness and limitations in solving the VIC problem were evaluated for the calibration of each type of working sensor under the various error conditions that cause negative effects. The combined strategies are also suggested to improve calibration accuracy by overcoming the individual limitations. This paper (1) explains how to formulate the individual and combined VIC strategies with Bayesian MCMC, (2) shows their capability to handle negative effects and limitations, and (3) demonstrates how combined strategies surmount the individual limitations for a high accuracy in various error conditions. [ABSTRACT FROM AUTHOR]

In hot and humid climate such as in Japan and south east Asia, dehumidification in summer is really important for air conditioning. Temperature and humidity independent control (THIC) of air conditioning system can handle sensible heat and latent heat separately, and provide good indoor environment and achieve energy conservation. Desiccant air handling unit is one of the major solution for THIC of air conditioning system. It needs hot water to regenerate sorbent which absorbs moist in the air. Combined heat and power can supply hot water at almost constant temperature for desiccant air handling system and also contribute to the business continuity plan of commercial buildings. However, there are still uncertainties about the factors which affect energy performance of desiccant air handling unit and the optimum design and operations in hot and humid climate. The objectives of this paper are to prove factors which affect energy performance of desiccant air handling unit by measurement analysis and show optimum condition of the desiccant air handling unit under various room conditions by simulation. Measurement analysis shows that energy performance of desiccant air handling unit depends not only on the inlet air condition to dehumidification wheel but also on designed supply air humidity. Furthermore, simulation results show the optimum inlet air condition entering dehumidification wheel under various supply air absolute humidity which is determined by design room conditions. These results provide useful information of desiccant air handling unit during design and operation phase of buildings in hot and humid climate. [ABSTRACT FROM AUTHOR]

Buildings are responsible for 40% of global energy use and contribute towards 30% of the total CO 2 emissions. The drive to reduce energy consumption and associated greenhouse gas emissions from buildings has acted as a catalyst in the increasing installation of meters and sensors for monitoring energy use and indoor environmental conditions in buildings. This paper reviews the state-of-the-art in building energy metering and environmental monitoring, including their social, economic, environmental and legislative drivers. The integration of meters and sensors with existing building energy management systems (BEMS) is critically appraised, especially with regard to communication technologies and protocols such as ModBus, M-Bus, Ethernet, Cellular, ZigBee, WiFi and BACnet. Findings suggest that energy metering is covered in existing policies and regulations in only a handful of countries. Most of the legislations and policies on energy metering in Europe are in response to the Energy Performance of Buildings Directive (EPBD), 2002/91/EC. However, recent developments in policy are pointing towards more stringent metering requirements in future, moving away from voluntary to mandatory compliance. With regards to metering equipment, significant developments have been made in the recent past on miniaturisation, accuracy, robustness, data storage, ability to connect using multiple communication protocols, and the integration with BEMS and the Cloud – resulting in a range of available solutions, selection of which can be challenging. Developments in communication technologies, in particular in low-power wireless such as ZigBee and Bluetooth LE (BLE), are enabling cost-effective machine to machine (M2M) and internet of things (IoT) implementation of sensor networks. Privacy and data protection, however, remain a concern for data aggregators and end-users. The standardization of network protocols and device functionalities remains an active area of research and development, especially due to the prevalence of many protocols in the BEMS industry. Available solutions often lack interoperability between hardware and software systems, resulting in vendor lock-in. The paper provides a comprehensive understanding of available technologies for energy metering and environmental monitoring; their drivers, advantages and limitations; factors affecting their selection and future directions of research and development – for use a reference, as well as for generating further interest in this expanding research area. [ABSTRACT FROM AUTHOR]

Building energy models (BEMs) are typically used for design and code compliance for new buildings and in the renovation of existing buildings to predict energy use. The increasing adoption of BEM as standard practice in the building industry presents an opportunity to extend the use of BEMs into construction, commissioning and operation. In 2009, the authors developed a real-time simulation framework to execute an EnergyPlus model in real time to improve building operation. This paper reports an enhancement of that real-time energy simulation framework. The previous version only works with software tools that implement the custom co-simulation interface of the Building Controls Virtual Test Bed (BCVTB), such as EnergyPlus, Dymola and TRNSYS. The new version uses an open standard interface, the Functional Mockup Interface (FMI), to provide a generic interface to any application that supports the FMI protocol. In addition, the new version utilizes the Simple Measurement and Actuation Profile (sMAP) tool as the data acquisition system to acquire, store and present data. This paper introduces the updated architecture of the real-time simulation framework using FMI and presents proof-of-concept demonstration results which validate the new framework. [ABSTRACT FROM AUTHOR]

Occupants account for a significant impact on building performance through their interactions with zone level building components. Empirically-derived occupant models, despite their potential to represent occupants’ impact in building performance simulation (BPS), have minimal penetration in design and code compliance processes. Instead, occupants are represented with static schedules or simple deterministic triggers. The objective of this paper is to better understand the influence of assumptions made in representing occupant interactions with building components over a BPS model's energy use and comfort predictions, as well as their ability to promote better design decisions. To this end, the energy and daylight performance of a generic perimeter office space in Ottawa, Canada were evaluated using a set of comprehensive performance metrics. Results indicate that representing dynamic occupant–building interactions lead to different energy predictions from the static schedules. The maximum difference in the total electricity use was for window-to-wall area ratios (WWR) of 20%, which was about 30% higher with the stochastic cases than the blind-open static cases. WWR 60% and 40% generally yielded the lowest lighting electricity use with the static and stochastic cases, respectively. This paper emphasizes the importance of incorporating empirically-derived dynamic occupant models for simulation-aided design and code compliance. [ABSTRACT FROM AUTHOR]

This paper deals with the quantification of the uncertainties due to wind in building pressurisation tests. The steady wind model error stems from the heterogeneous pressure distribution around the building. We have analysed this error based on a simplified one-zone building model with one leak on the windward side and one on the leeward side of the building. Our model gives an analytical expression of this error that depends on the leakage distribution and pressure coefficients. Using test and reference pressures at 50 Pa in this model, standard measurement protocol constraints contain the steady wind model error within about 3% and 11% with wind speeds below 6 m s −1 and 10 m s −1 , respectively. At 10 Pa, the error is in the range of 35% and 60% at 6 m s −1 and 10 m s −1 , respectively. This paper also includes an estimate of the combined uncertainty including other sources of errors which can be used to assess the relevance of measurement protocols. Under idealised conditions, using 50 Pa as reference pressure and a default flow exponent, it can be expected a combined expanded uncertainty of 6%–12% for wind speeds of 6–10 m s −1 , respectively. [ABSTRACT FROM AUTHOR]

Whole-house ventilation, which is defined as systems that supply and exhaust or relieve ventilation air for a residence, has been a mandatory provision since the announcement of IECC 2012. As a result, an increasing numbers of publications and standards are now addressing residential ventilation in terms of performance and efficiency. In addition, loudness is increasingly addressed in standards and guidelines, especially in the last decade as it is now considered to be a significant factor for certified performance ratings of ventilation fans. Because of the above interest in fan performance, this paper provides statistics of bathroom ventilation fan tests and their results for an almost decade-long period from 2005 to 2013. Also, the paper interprets these statistics with regards to the recent development of residential ventilation standards and guidelines. In order to investigate year-to-year changes, this paper first evaluates changes in loudness ratings for the test period 2005–2013, and its relevance to applicable standards, including ASHRAE 62.2. Then, noticeable transitions in loudness and efficacy in specific time frames are investigated. The test results of DC-motor high-efficiency bathroom fans are also compared to AC-motor fans. Relationships between performance variables and loudness are investigated, and formulated by developing regression models. [ABSTRACT FROM AUTHOR]

Current trend in the field of civil engineering is building energy-saving and environmentally friendly constructions. One of ways of achieving these trends is using new, progressive construction materials, which are friendly to the environment, have good end-use properties and which are also for reasonable price. Another way is building plant facades and roofs. Plants are capable of regulating temperature and humidity in such constructions. Their advantage is positive influence on healthy living in large cities, where the beneficial properties of plants can be used, like capability of retaining fine dust particles, reducing the level of noise and protecting the structure from weather effects. The paper describes possible connection of both above mentioned modern technologies and gives results of research and development of insulation materials based on natural fibers; in particular technical hemp, flax and jute and their application into buildings with plant facades and roofs. The paper also mentions hydrothermal behavior of the developed materials, including computational simulation of behavior of the optimal hemp fiber based material after building into a structure with plant facade. [ABSTRACT FROM AUTHOR]

Smart building systems are opening up new markets, nevertheless the implementation of these novel technologies still lacks suitable and proven whole engineering solutions in complex buildings. This paper presents a detailed approach for the ventilation control of an underground space, as an example of application of the developed solution to a very harsh environment but also highly demanding in terms of energy consumption. The underground spaces are characterized by a particular thermal behavior, because of the continuous and huge thermal exchange they have with the outside, via the openings and the ground surrounding the majority of the building. The main objective of the developed methodology is to reduce energy consumption of ventilation control while maintaining acceptable comfort levels: succeeding in achieving this twofold goal in a real station and the generalization of the approach are the most relevant contributions of the paper. The developed solution is based on a Model-based Predictive Control algorithm used together with a proper monitoring platform. The model predictive control is based on a Bayesian environmental prediction model, which works in cooperation with a weather forecast web service, schedule-based predictions about trains and external fans and an occupancy detection system to appraise the real amount of people. The prediction model develops scenarios useful to allow the controller acting in advance in order to adapt the system to the current and future conditions of use, taking profit of the knowledge of the real ventilation demand. Finally, the proposed control architecture is applied to the Passeig de Gràcia metro station in Barcelona as a case study, validating the usefulness of the proposed approach and obtaining more than 30% of energy savings in the ventilation system, while maintaining the pre-existing comfort levels. The saving percentage values estimated by simulation are confirmed by the direct measures continuously taken on site through energy-meters. [ABSTRACT FROM AUTHOR]

The smart grids are modern electric power grid infrastructure for enhanced efficiency and reliability through automated control, high-power converters, modern communications infrastructure, sensing and metering technologies, and modern energy management techniques based on the optimization of demand, energy and network availability. The role of buildings in this framework is very crucial. This paper addresses critical issues on smart grid technologies and the integration of buildings in this new power grid framework. The main objective of this paper is to provide a contemporary look at the current state of the art in the potential of buildings and communities to be integrated in smart grids as well as to discuss the still-open research issues in this field. The challenges for the building sector are discussed and future research prospects are analysed. [ABSTRACT FROM AUTHOR]

The selection of a thermal comfort model for establishing indoor optimal hygrothermal conditions during the hot period has a major impact on energy consumption of Net Zero Energy Buildings in hot climates. The objective of this paper is to compare the influence of using different thermal comfort models for zero energy buildings in hot climates. The paper compares the impact of applying Fanger's model, Givoni's model, the ASHRAE 55 adaptive comfort model and the EN 15251 adaptive comfort model on energy consumption and comfort performance. Using both the building performance simulation tools ZEBO and EnergyPlus for energy simulation, an existing prototype of a residential apartment module is used to evaluate energy performance and thermal comfort in two parametric series. The first one is the result of coupling natural ventilation and mechanical cooling and the second one is guided coupling natural ventilation, mechanical cooling and ceiling fans. This study shows that the percentage of energy consumption difference meeting the comfort criteria according to ISO 7730 in comparison to EN 15251, ASHRAE 55 or Givoni's model varied up to 16%, 21% and 24.7%, respectively for the presented case study. More energy savings can be expected for buildings in hot climates with greater cooling demands. [ABSTRACT FROM AUTHOR]

Built-up areas tend to comprise a variety of buildings with diverse and complex shapes, functions and construction characteristics. This variety is the source of significant challenges when calculating building energy use at the building stock level. Moreover, the process of developing stock models usually requires large amounts of data that are frequently scarce, nonexistent or at least not publicly available. Under these circumstances, defining a limited set of reference buildings representing the stock is useful to study the actual energy consumption and the potential effects of different energy conservation measures. This paper presents a new method for developing typical residential reference buildings at district level for bottom-up energy modeling purposes. By means of widely and freely available satellite images, an information database of building shapes is created and a clustering analysis of the geometrical features is performed to define a number of archetypes representative of the heating and cooling energy demand of the district. The method is tested and demonstrated through the case study of the Yuzhong District in Chongqing (China) by comparing the Energy Use Intensity (EUI) of the archetypes derived in this way against detailed dynamic simulations. Results show very small differences in the estimated stock energy consumption (+0.03% in heating energy consumption and +2.97% in cooling energy consumption). [ABSTRACT FROM AUTHOR]

The thermo-hygrometric treatment related to the air change in buildings requires a relevant quota of the total energy demand of HVAC systems, especially when the ventilation demand is significant. A correct energy saving strategy therefore should always focus on the use of suitable techniques to reduce this energy consumption. As proved by the modern theories on comfort, less strict values can be accepted for the internal humidity set points without compromising indoor comfort conditions. In addition, Demand Controlled Ventilation (DCV) gives the opportunity to reduce energy requirements. This paper investigates the opportunities offered by the installation of a DCV system and a Building Management System (BMS) able to perform long term monitoring of the HVAC system in a real case study. This refers to a historic building in Venice in the area of the harbour and recently transformed into a modern university facility. Starting from the experimental data recorded by BMS, an optimization of the control strategies and simple tuning actions of the DCV controller were possible. Results validate the use of more flexible set points of indoor relative humidity and long term on-line tuning even in absence of self-learning control systems, as well as they highlight the achievement of remarkable energy savings thanks to these actions. The research demonstrates the fundamental contribution of successive control performance assessments by long term monitoring to individuate possible weaknesses in DCV system management. [ABSTRACT FROM AUTHOR]

The foundations of all methodologies for the measurement and verification (M&V) of energy savings are based on the same five key principles: accuracy, completeness, conservatism, consistency and transparency. The most widely accepted methodologies tend to generalise M&V so as to ensure applicability across the spectrum of energy conservation measures (ECM’s). These do not provide a rigid calculation procedure to follow. This paper aims to bridge the gap between high-level methodologies and the practical application of modelling algorithms, with a particular focus on the industrial buildings sector. This is achieved with the development of a novel, machine learning supported methodology for M&V 2.0 which enables accurate and reliable quantification of savings. A novel and computationally efficient feature selection algorithm and powerful machine learning regression algorithms are employed to maximise the effectiveness of available data. The baseline period energy consumption is modelled using artificial neural networks, support vector machines, k-nearest neighbours and multiple ordinary least squares regression. Improved knowledge discovery and an expanded boundary of analysis allow more complex energy systems be analysed, thus increasing the applicability of M&V. A case study in a large biomedical manufacturing facility is used to demonstrate the methodology’s ability to accurately quantify the savings under real-world conditions. The ECM was found to result in 604,527 kWh of energy savings with 57% uncertainty at a confidence interval of 68%. 20 baseline energy models are developed using an exhaustive approach with the optimal model being used to quantify savings. The range of savings estimated with each model are presented and the acceptability of uncertainty is reviewed. The case study demonstrates the ability of the methodology to perform M&V to an acceptable standard in challenging circumstances. [ABSTRACT FROM AUTHOR]

Prior knowledge of occupants’ thermal comfort can facilitate informed control decision of ambient thermal-conditioning in a building environment. This paper investigates the possibility to predict human thermal state (Comfort/Discomfort) from the information of physiological parameters. As gender difference has been widely linked with thermal comfort perception, a four-fold objective is adopted: first, investigating gender differences in subjective thermal perception; second, investigating gender differences in physiological response under different thermal states; third, identifying those physiological features that have the potential to predict thermal state, and fourth, establishing a data-driven thermal state prediction model for each gender group using the identified features. Human subject experiments were conducted, during which five physiological responses (hand skin temperature ST h , hand skin conductance SC h , pulse rate PR, blood oxygen saturation SpO 2 , blood pressure BP) and four subjective responses (thermal comfort, thermal preference, humidity sensation, airflow sensation) were recorded in conjunction with a thermal sensation survey while environmental conditions varied from cold/cool to neutral levels (18°C − 27 ∘ C). Additionally, derivative features namely change rate (FOG) and mean squared gradient (MSG) of each physiological parameter were examined. Rigorous statistical analysis and subsequent predictive modeling utilizing Random Forest algorithm were implemented. Results demonstrate significant gender difference in several subjective and physiological responses. The features identified for males (SpO 2 -MSG/ST h /ST h -FOG/ST h -MSG/SC h /SC h -FOG/SC h -MSG) and females (ST h -FOG/ST h -MSG/SC h /SC h -MSG/PR/PR-MSG) could accurately predict 92.86% and 94.29% of thermal states, respectively. This study indicates that the thermal state of a person can be identified by monitoring physiological parameters from non-intrusive body locations using wearable sensing technology. [ABSTRACT FROM AUTHOR]

A major challenge facing the buildings sector is the absence of continuous commissioning and the lack of performance monitoring and evaluation leading to buildings energy performance gaps between predicted and actual measured performance. Aiming to better characterize, evaluate and bridge these gaps, the paper proposes an online building energy performance monitoring and evaluation tool ObepME, serving as a basis for fault detection and diagnostics and forming a backbone for continuous commissioning. A calibrated building dynamic energy model is developed and employed to automatically run on a daily basis and simulate the building transient performance for the previous day. The simulated energy consumption results form a baseline to which the actual collected data are compared to evaluate the dynamic energy performance gap. The OU44 University building in Denmark is considered as a case study to implement the proposed framework. A holistic energy model was developed in EnergyPlus and calibrated employing data from various building meters, collected weather conditions, generated occupancy schedules and systems operational parameters and set-points. The calibrated model was employed in the ObepME tool to automatically and continuously monitor and evaluate the OU44 building energy performance, on the level of the whole building and individual energy systems consumption, throughout the period from February to mid-March 2017. The reported dynamic energy performance gap was around −2.85%, −3.47% and 5.48% for heating, total electricity and ventilation system electricity consumption. In addition, specific observations were made on a daily basis in terms of the overall electricity, heating, lighting and ventilation energy consumption as highlighted by the ObepME tool. The ObepME tool is currently running automatically as a part of the OU44 building continuous commissioning and performance evaluation aiming to identify possible discrepancies and deviations paving the way for a methodical preventive fault detection and diagnostics process on various levels in the building. [ABSTRACT FROM AUTHOR]

This paper presents the development of a symbolic transformation based strategy with interpretability and visualisation for building energy performance assessment. The strategy was developed using shape definition language based symbolic transformation and hierarchical clustering. Advanced visualisation techniques including dendrogram, heatmap and calendar view were used to assist in understanding building energy usage behaviours. A comparison of this proposed strategy with a Symbolic Aggregate approXimation (SAX) based strategy was also performed. The performance of the proposed strategy was tested and evaluated using the three-year hourly heating energy and electricity usage data of a higher education building. The result demonstrated that the proposed strategy can identify distinct building energy usage behaviours. The visualisation techniques used also assisted the information discovery process. The discovered information helped to understand building energy usage patterns. The comparison of the proposed strategy with the SAX based strategy showed that the proposed strategy outperformed the SAX based strategy for the case building tested in terms of the variations in building energy usage. This proposed strategy can also be potentially used to evaluate the operational performance of building heating, ventilation and air-conditioning (HVAC) systems. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive review of the open literature on motivations, methods and applications of linking stratified airflow simulation to building energy simulation (BES). First, we reviewed the motivations for coupling prediction models for building energy and indoor environment. This review classified various exchanged data in different applications as interface data and state data , and found that choosing different data sets may lead to varying performance of stability, convergence, and speed for the co-simulation. Second, our review shows that an external coupling scheme is substantially more popular in implementations of co-simulation than an internal coupling scheme. The external coupling is shown to be generally faster in computational speed, as well as easier to implement, maintain and expand than the internal coupling. Third, the external coupling can be carried out in different data synchronization schemes, including static coupling and dynamic coupling. In comparison, the static coupling that performs data exchange only once is computationally faster and more stable than the dynamic coupling. However, concerning accuracy, the dynamic coupling that requires multiple times of data exchange is more accurate than the static coupling. Furthermore, the review identified that the implementation of the external coupling can be achieved through customized interfaces, middleware, and standard interfaces. The customized interface is straightforward but may be limited to a specific coupling application. The middleware is versatile and user-friendly but usually limited in data synchronization schemes. The standard interface is versatile and promising, but may be difficult to implement. Current applications of the co-simulation are mainly energy performance evaluation and control studies. Finally, we discussed the limitations of the current research and provided an overview for future research. [ABSTRACT FROM AUTHOR]