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Abstract The power grid has seen record demand for frequency regulation capacity in recent years due to the increased employment of renewable energy resources worldwide. Building thermal loads are flexible and thus, can be used as regulation reserves with proper control strategies. Previous studies have shown that building HVAC equipment can provide high-quality power grid regulation service with PJM performance scores of up to 0.98 and buildings' participation in the regulation market could bring significant economic benefits for building owners. However, the power flexibility in buildings is not persistent and the available HVAC regulation capacity has significant hour-by-hour variation due to building load and other operating constraints. This paper presents a regulation capacity reset strategy for HVAC regulation control that identifies the available regulation capacity and baseline power on the fly with real-time load and operation data. The strategy relies on a steady-state HVAC performance model derived from manufacturer performance data and implements a pseudo-optimization that seeks the maximum regulation capacity while respecting all operating constraints. The proposed strategy was implemented on a variable-speed rooftop unit (RTU) and validated with laboratory tests in psychrometric chambers. The test results show that the proposed reset strategy is effective in providing consistent high-quality regulation service with negligible impact on the indoor temperature control; the zone temperature deviation from the setpoint was within 0.3°C for all the performed tests. The reset strategy was also simulated with a prototypical building diurnal load model to quantify the integrated regulation capacity for a typical summer day. Simulation results indicate the integrated HVAC regulation capacity throughout a summer day equals approximately 1/4 of the daily electrical energy use; and the estimated daily regulation credit can offset up to 26% of the daily HVAC electricity cost based on PJM historical prices. [ABSTRACT FROM AUTHOR]

Highlights • Thermal quadrupoles formalism is applied for modelling transient heat transfers in building walls with a semi-infinite assumption. • Front face response curves of multi-layered walls are analysed to estimate the thermal properties of the wall. • Experiments are carried out on two classical multi-layered building walls using artificial thermal excitations. • The proposed method reduces the evaluation time less than 10 hours. Abstract Thermal performances of building walls are significant for energy conservation. However, very few non-destructive evaluation methods exist to quantitatively diagnose the building walls in situ due to the walls' large thickness. Moreover, most of the existing methods are inconvenient to implement in situ and take a long characterization time. This paper studies transient heat transfer to estimate the wall's thermal properties based on the thermal quadrupoles modelling. Semi-infinite boundary condition is assumed at the rear face of the wall. With this assumption, only the front face response of the wall is considered. The evaluation time is then effectively reduced within a few hours, and the diagnosis in situ is simplified without the measurement on the rear face of the wall. Experiments are carried out on two traditional multi-layered building wall cases using heating lamps. With the measured surface temperatures and heat fluxes, the unit-pulse response and unit-step response at the front surface of the investigated wall are reconstructed through a deconvolution approach and a TSVD (Truncated Singular Value Decomposition) inversion. The unit-step response curve is directly characterized by the thermal resistance, thermal effusivity and heat capacity of the wall, thus allowing us to estimate the wall properties. The characterization time for the two cases is less than 10 hours. [ABSTRACT FROM AUTHOR]

Highlights • Heat cost allocators can be used to indicate if radiators have malfunctions. • The method can provide an insight into the heating system operation. • Deviations between measurements and model results were seen in some cases. • Further verification of the method should be carried out. • Frequent data transmission and additional measurements can improve model accuracy. Abstract Proper heating system operation in buildings is a vital area for the realization of low-temperature district heating with supply and return temperatures of 55°C and 25°C respectively. But the operating area of the district heating companies usually only extends to the substations at the entry of the buildings, and very little is known about the actual use and distribution of heat inside the buildings. This paper describes one possible method for district heating companies or building technicians to monitor heating system operations, and thereby identify heating system malfunctions, inside apartment buildings. The method uses data from existing electronic heat cost allocators to locate radiators with high return temperatures. The method was tested by comparing data from heat cost allocators with detailed measurements of radiator return temperatures in an apartment building in Frederiksberg, Denmark. The investigations indicate that data from the heat cost allocators can be used to identify radiators with continuously high return temperatures, and thereby locate severe problems with e.g. hydraulic balancing in heating systems. However, the method needs further development and tests to ensure the accurate identification of the various heating system malfunctions and their effect on overall heating system efficiency. [ABSTRACT FROM AUTHOR]

Highlights • Energy use for DHW accounts from 16% to 50% of total heat requirement. • Method to estimate mean hourly and daily profile of DHW from total heating readings. • Method gives good results when DHW share in total heating demand is minimum 50%. • Better understanding of users' practice related to DHW and space heating is crucial. Abstract During recent years, the research in reduction of energy use in buildings has focused primarily on decrease of space heating needs, energy for ventilation and recently cooling, whereas domestic hot water (DHW) has been overlooked. In 2013, the energy use for DHW was estimated at 16% of total heat requirement in EU28 households, but in new energy-efficient buildings this share is documented to be around 40–50%. Generally, however, there is limited knowledge of DHW. This paper presents a simple methodology, which enables calculation of the mean hourly and the daily profiles of DHW demand from hourly values of the building total heat demand, and thus contributes to gaining a better understanding of the DHW usage. The method is validated with data from single-family houses and apartments and afterwards applied to dataset consisting of hourly total heat consumption readings from 38 single-family houses delivered by district heating. The method gives satisfying results when the DHW usage during summer is at least at the same level as the space heating demand, which is the case in apartments and in the energy-efficient houses. The standard deviation was used as preliminary classification criterion for deciding if the method can or cannot be applied. Two limits were found σ > 240 for apartments and σ < 800 for single-family houses. [ABSTRACT FROM AUTHOR]

Abstract Measuring and tracking building energy use and other data is essential for cities, utilities, and service providers. Currently, buildings are conceived as "places/locations" and therefore are identified with a street address or with a single geographic coordinate point (latitude and longitude). However, the address-based system is insufficient to uniquely identify buildings, and to append and join data from disparate sources due to address name duplicates, incorrect entries, and lack of an input format standard. As a result, essential building energy data for energy efficiency policy decision making is difficult to leverage. The Unique Building Identifier (UBID) was developed as a natural key to match building energy and attribute data between databases and to facilitate matching across datasets. Our methodology converts a two-dimensional building footprint into a unique alphanumeric code based on an open source grid reference system. The UBID is designed to be easily overlaid on publicly available, web-based mapping platforms and enable fast and accurate spatial matching with minimal computational resources. In this paper, we present the UBID methodology, discuss the use cases in energy efficiency, and present the results of tests in three major US cities (San Francisco, Chicago, and New York City) to verify the uniqueness and effectiveness of the proposed building identifier. [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 • Impacts of fouling and ambient temperature on ASHP's performances were studied. • Increased fouling level and ambient air temperature led to poorer performances. • An equivalent temperature rise due to fouling was proposed and evaluated. • An improved simulated fouling approach was experimentally validated. Abstract Air source heat pumps (ASHPs) have been widely used for providing buildings with heating in winter and cooling in summer. In certain locations, with an increased level of air pollutions, fouling of the outdoor coil in a space cooling ASHP unit may appear, which affects the operating performances of the ASHP unit. Furthermore, the operating performances of an ASHP unit can also be affected by ambient air temperature (T a). In this paper, a field study on the effects of outdoor coil fouling at different T a on the operating performances of a field space cooling ASHP unit is presented. The study results demonstrated that the operating performances of the field ASHP unit were significantly affected by the changes in both T a and percentage of fouled outdoor coil surface (PFOCS). For example, at T a = 30 °C, the variation in PFOCS from 0 to 100% led to a reduction in COP for the field ASHP unit from 2.7 to 2.0. At a fixed PFOCS of 60%, the changes in T a from 26 to 33 °C resulted in a reduction in COP from 2.6 to 2.1. In order to more conveniently investigate the combined impacts of fouling on the operating performances of an ASHP unit at different T a , an equivalent ambient air temperature rise (ETR) was proposed. Based on the measured and evaluated operating parameters of the field ASHP unit at different T a and PFOCS values, ETR values at 0 - 40%, 40 - 60%, 60 - 100% and 0 - 100% PFOCS ranges were evaluated. These ETR values implied that defouling of a fouled outdoor coil may be initiated when PFOCS was at 40 - 60%. With the ETR values for the full PFOCS range of 0 - 100%, the impact of full fouling on the operating performances of an ASHP unit may be evaluated as if it was operated with a clean outdoor coil but at an equivalent ambient air temperature of T a + ETR. [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 • Analysis of the average temperature dependency of thermal conductivity in VIPs. • Analysis of the heat transfer contributions that affect thermal conductivity in VIPs. • Evaluation of the combined effect of ageing and temperature on thermal conductivity. • Impact of thermal conductivity variation on thermal behaviour of a VIP-based roof. • Measures to mitigate severe conditions for VIP-based components were introduced. Abstract Over the last few years, the adoption of Vacuum Insulation Panels (VIPs) in building envelopes has increased. However, in order to obtain a correct implementation of VIPs in buildings, it is crucial to conduct a proper analysis of the thermal bridging, the service life and the ageing effects at both the design stage and during building operation. A further factor that should be considered is the dependency of thermal conductivity on temperature. In this paper, an experimental campaign has been carried out to evaluate the variation in the thermal conductivity of VIPs with the average temperature and to qualitatively assess the heat transfer contributions that affect this variation. The study has also been devoted to evaluating the effect of a variation in the thermal conductivity considering various VIP ageing stages. Moreover, dynamic heat transfer simulations have been performed, using a validated model, to investigate the impact of considering a temperature dependent thermal conductivity on the overall thermal behaviour of a building roof with VIP-based insulation. [ABSTRACT FROM AUTHOR]

Highlights • Effect of nonlinear dynamics of a hydronic heat emitter on the DR potential. • The nonlinear thermal effects had insignificant effects on the DR performance. • Shifting potential depends on the energy efficiency of the building envelope. • A reliable radiator model suitable for any simulation-based research is proposed. Abstract Existing simulation-based studies on applying model predictive control (MPC) schemes for space heating operation to enable demand response (DR) make use of linear models for the heating system, usually by assuming convective electrical baseboard heaters. However, buildings connected to district heating networks are typically equipped with hydronic heat emitters, such as radiators, that behave nonlinear. This paper therefore investigates the effect of including the nonlinear dynamics of a hydronic heat emitter on the DR potential of MPC for space heating. Furthermore, the performance of a practical two-level control approach suitable for real application, in which a heating setpoint was determined by a linear MPC and communicated to a conventional proportional integral controller, was investigated. The simulation framework for the investigation was based on the application of an experimentally obtained hydronic radiator model applied in different co-simulation setups, featuring a model of a poorly and a highly insulated apartment, respectively. The results indicated that inclusion of the nonlinear thermal effects of hydronic radiators did not significantly affect the DR performance when compared to the results of an MPC scheme controlling convective electrical baseboard heaters. In general, both setup achieved operational cost savings of approx. 5% and 18% in an existing and retrofitted building, respectively, while restricting the amount of thermal comfort violations to a limited extent. This suggests that results obtained in previous studies featuring electrical baseboard heaters also apply to buildings equipped with hydronic heating systems, and that future simulation-based studies and practical implementation of MPC for space heating can continue to rely on the use of far less computationally demanding linear control-models. Furthermore, the results suggest that the two-level control scheme seems like an appropriate control setup suitable for real applications. [ABSTRACT FROM AUTHOR]

Abstract This article introduces a parameter estimation and state prediction technique called constrained dual Extended Kalman Filter (EKF) that can be used in model prediction controls (MPC) and fault detection and diagnostics (FDD) in building systems. The proposed method is an improvement over the existing nonlinear filter-based methods such as the joint EKF or Unscented Kalman Filter, which is widely adopted in previous building controls research. Case studies using both simulation and real measurements are conducted to demonstrate the proposed algorithm when used for a building thermal zone. Data from parametric simulations are used to test the thermal model's ability to capture parameter variations. Measured data from five identical offices is collected to test the performance of parameter estimates and state predictions under real-life operation. Overall, the proposed algorithm is 25% faster than a conventional EKF with improved numerical stability. It can also help mitigate numerical instabilities seen in previous EKF research. The reduced thermal model used in this paper is also capable of detecting most of the parametric changes to the thermal zone and providing reliable temperature predictions. [ABSTRACT FROM AUTHOR]

Abstract Sustainable energy technologies are frequently considered for use with buildings in order to reduce their environmental impact. However, each technology will come with its own associated embodied carbon, which might potentially represent a significant proportion of a building's total embodied carbon impact. There is a need for further studies on the embodied carbon or CO 2 equivalent (CO 2 e) impact of sustainable energy technologies and it is important to understand how they contribute to the total CO 2 e budget of a building. Life Cycle Assessment (LCA) is used for the CO 2 e calculations and this paper has reviewed a significant number of existing studies. The results show that LCA methodologies can and do present information which has a significant degree of inaccuracy. Furthermore, the impact of some technologies can significantly increase the embodied CO 2 e impact of modern low to zero energy buildings. Considering the whole life CO 2 e impact of each aspect of a building is crucial for the successful creation of a truly low to zero carbon building. Many current studies omit the CO 2 e impact from sustainable energy technologies. This leads to results which are under representative and misleading. [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]

Highlights • A novel framework for the assessment of adaptive facade systems is developed. • Our analysis characterized adaptive facades from the market perspective. • Process mapping of three case studies identified facades' process delivery hurdles. • Currently most adaptive facades are nor designed with a user-centered approach. • Façade sub-contractor & building operator is crucial for long-term performance. Abstract During the last decades, a great number of innovative building envelope materials and façade components have been developed. The majority of these technologies promise significant improvements in energy efficiency and occupant's comfort, with products that are easily available in the market. However, it remains a challenge to assess the performance of such facades, leading to difficulties for efficient design, operation, and maintenance. As a consequence, the market adoption of adaptive facades is not realizing its full potential, resulting in missed opportunities for energy savings and improved occupant satisfaction. In this study, the current trends of adaptive facades are investigated, with particular emphasis on their performance assessment. Based on extensive literature review, the gaps in assessment of adaptive facades are determined and a novel object-based façade characterization and classification framework is proposed. Furthermore, a generic stakeholder map and process map are presented to explain current adaptive façade delivery practices. In addition, the findings of interviews and two focus group discussions with experts and specialists are presented to elucidate their expert opinions, leading to a validated framework of key performance indicators. As results of this paper, the gaps related to adaptive façade systems' assessment are identified with respect to the different actors and stakeholders, and insights and perspectives on current trends and future challenges of adaptive façade system assessment are provided. [ABSTRACT FROM AUTHOR]

Abstract In the construction sector, strong efforts are being made to reduce energy consumption in buildings, particularly regarding thermal insulation in northern countries. However, the objectives set for the thermal insulation performance of the building envelopes are rarely achieved in practice. For this reason, there is increasing interest in taking onsite measurements. This paper presents the new achievements obtained by the ISABELE (In Situ Assessment of the Building EnveLope pErformances) method for data treatment to evaluate the global transmission heat transfer coefficient of a building with a consolidated uncertainty and within a short unoccupied period. Most of the work relates to the quantification and propagation of systematic errors and to the adaptation of the thermal model used for the inverse method. Practical applications on a test cell and a demonstration on a low-energy house in real outdoor conditions are presented, as are comparisons with other measurement methods (coheating, Quick U-Value of Buildings (QUB)) and the resulting calculated parameters, which show coherent outcomes. The test cell results reveal that a stabilized, repeatable measure with an acceptable uncertainty range (± 10 % in average) can be obtained within 2 days. The house results are slightly less precise (± 15-20 %) but can be obtained just as quickly, assuming that both configurations are insulated from the inside. [ABSTRACT FROM AUTHOR]

Abstract The reduction of energy consumption in the existing building stock is a crucial element of the Swiss Energy Strategy 2050 in view of the fact that the built environment accounts for more than 44% of the final energy use in Switzerland. It is therefore necessary to characterise the Swiss building stock and in particular the residential sector at an appropriate degree of detail, distinguishing between various types of buildings (archetypes) and building elements in order to identify the untapped potential for energy retrofit. In this paper, the current thermal performance and retrofit state of the Swiss residential building stock is examined based on approximately 10,400 Cantonal Building Energy Certificates issued for individual buildings across the country. The statistical analysis of the certificates allows to estimate a thermal performance level of archetype buildings and their respective building elements as well as of the heating systems. For this purpose, we develop a method allowing to obtain typical U-Values for original and retrofitted buildings from the total U-Value distributions. Our results indicate that approximately 75% of all building elements do not yet reach the thermal performance of buildings constructed in the last 15 years. In order to reach current low-energy building standards (MINERGIE P), the U-Values of building elements constructed prior to 1990 would have to be reduced by a factor of three to more than six, from 0.5–1 W/(m²K) to 0.15 W/(m²K); windows would require an improvement by at least a factor of two, from 2.5–2 to 0.9 W/(m²K). With regard to heat supply, 50% of the surface area is still heated by inefficient and CO 2 -intensive oil-fired boilers. The results of this study hence confirm the high potential for thermal retrofit in the Swiss residential building stock. Graphical abstract Image, graphical abstract [ABSTRACT FROM AUTHOR]

Abstract Building structures, subject to dynamic loadings or external disturbances, may undergo destructive vibrations and encounter different degrees of deformation. Modeling and control techniques can be applied to effectively damp out these vibrations and maintain structural health with a low energy cost. Smart structures embedded with semi-active control devices, offer a promising solution to the problem. The smart damping concept has been proven to be an effective approach for input energy shaping and suppressing unwanted vibrations in structural control for buildings embedded with magnetorheological fluid dampers (MRDs). In this paper, the dissipation energy in MRD is studied by using results from induced hysteretic effect of structural vibrations while the fluid is placed under a controlled magnetic field. Then, a frequency-shaped second-order sliding mode controller (FS2SMC) is designed along with a low-pass filter to implement the desired dynamic sliding surface, wherein the frequency responses of the hysteretic MRD is represented by its magnitude and phase describing functions. The proposed controller can thus shape the frequency characteristics of the equivalent dynamics for the MRD-embedded structure against induced vibrations, and hence, dissipate the energy flow within the smart devices to prevent structural damage. Simulation results for a 10-floor building model equipped with current-controlled MRDs, subject to horizontal seismic excitations validate the proposed technique for low-energy structures with smart devices. The closed-loop performance and comparison in terms of energy signals indicate that the proposed method allows not only to reduce induced vibrations and input energy, but also its spectrum can be adjusted to prevent natural modes of the structure under external excitations. [ABSTRACT FROM AUTHOR]

Abstract Traditional Chinese Kang is frequently used for space heating in rural areas of northern China, since it is easy to construct and offers various benefits for a rural building, including cooking, heating, providing a place for sleeping and so on. However, various problems, such as smoke leakage, non-uniformity of the kang surface temperature and so on, exist in a rural building heated by Chinese kang. Here, a novel kang system called energy-saving elevated kang (ESEK) is proposed based on the ordinary elevated kang (OEK) model. Experimental results showed that the comprehensive efficiency can be improved by 6.06%. Under the same operation condition, the indoor temperature of ESEK is 2.2°C–5.3°C higher than that of OEK, creating a more comfortable indoor thermal environment. In addition, the temperature field of the upper surface and the velocity field of flue gas of ESEK under different boundary conditions were studied in detail using the Fluent software. Simulation results indicated that the temperature of ESEK has better uniformity. Furthermore, the optimal inlet velocity of flue gas should be between 0.5 m/s and 0.7 m/s. The ESEK proposed in this paper is suitable for application in rural buildings to improve the indoor thermal environment. [ABSTRACT FROM AUTHOR]

Abstract Among different structural elements, floor elements account for the largest portion of the mass and thus the embodied energy of the structures. Therefore, a viable approach to reduce the embodied energy of buildings may involve replacing the conventional floor systems with alternative low embodied energy floor systems. This paper investigates the potential reductions in the life cycle energy of the steel structures achievable through the adoption of steel-timber composite (STC) elements as floor and shear wall systems. Evaluating the life cycle energy implications of adopting STC elements is especially important due to the trade-off between their positive and negative effects on embodied energy and operating energy, respectively, when compared to alternative conventional elements with a higher thermal mass including concrete and steel elements. The life-cycle energy of four different structures designed for a building is evaluated by accounting for energy use in material extraction and processing, component manufacturing, transportation, construction, operation and end of life phases. Two steel structures with STC and steel-concrete composite floors and concrete shear walls are considered to evaluate the effects of STC floors on the energy-usage footprint. The third structure is designed with STC floor system and CLT shear walls; and the fourth structure is designed as a concrete structure to provide a basis for comparison between energy footprint of steel structures with STC and reinforced concrete structures. The results indicate that when designing the building with a steel structure, adoption of STC floor and shear wall systems resulted in 107.5% decrease in the embodied energy at the expense of only a slight increase in the operating energy. Furthermore, adopting a steel structure with STC floors was found to result in considerable life cycle energy savings, viz. 895 MJ/m2, when compared with the same building designed with a concrete structure. [ABSTRACT FROM AUTHOR]

Highlights • This study presents a detailed review on IRT for the investigation of building envelope defects. • The literature survey is conducted regarding existing IRT methodologies for building envelopes. • The previous studies with measurement methods, analysis schemes and analysis types are categorized in the literature matrix. • Recent advances and future trends on IRT methods are presented. Abstract Thermal radiation generated by limited resources is emitted from the surfaces and interpreted as temperature. On the other hand, the limited resources necessitate prevention of energy leakages causing noticeable temperature differences on surfaces. Providing sensitive information on temperature contrast, infrared thermography (IRT) is a prominent tool for detecting infrared energy on the surfaces of the objects. IRT is also very promising method for detecting thermal irregularities, air leakages and even moisture abnormalities on building envelopes. Since the concept of nearly zero energy buildings is to be the main target of energy policies in European Union published by European Commission, improving thermal performance of buildings becomes crucial in the last decade. Therefore, implementation of IRT for visualizing and analyzing concealed defects on building envelopes is very promising for improving the energy efficiency of buildings. Given recent regulations and benefits of emerging thermogram technologies mentioned above, a detailed review of the previous studies investigating the abnormalities of building envelopes by IRT is presented in this paper. Furthermore, the applications with measurement methods, analysis schemes and analysis types are classified to highlight the potential of IRT in inspection of building envelopes for providing energy efficient solutions. Finally, recent advances and practical future opportunities are presented for additional contribution of the IRT methods previously employed. [ABSTRACT FROM AUTHOR]

Abstract The actual thermal behaviour of façades is important to identify suitable energy-saving measures and increase the energy performance of existing buildings. However, the accuracy of in situ measurements of façades’ U-values varies widely, mostly due to inadequate test durations. The aim of this paper was to evaluate the minimum duration of in situ experimental campaigns to measure the thermal transmittance of existing buildings’ façades using the heat flow meter method, and to analyse the thermal performance of the façade during the test. Minimum test duration was determined according to data quality criteria, variability of results criteria, and standardized criteria for different ranges of theoretical thermal transmittance and for the same range of average temperature difference. Then, the minimum test duration results were compared. The findings show that ISO criteria are more sensitive and provide more accurate results, requiring a longer test duration. However, when certification is not required, the duration of the test could be reduced by applying data quality and variability of results criteria. The minimum duration of experimental campaigns depends on the theoretical thermal transmittance and the stability of climatic conditions. Moreover, results are more accurate when the dynamic method is used. [ABSTRACT FROM AUTHOR]

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

Highlights • A highly interactive web tool for the exploration of NILM results is presented. • Data cube allows insightful integration of NILM components with raw consumption data. • Hospital total demand, 7 cooling machines and temperature each minute for a year. • Fluid feedback by live coordinated views allows to interpret the NILM decomposition. • NMF exploits positivity of energy consumptions for an interpretable decomposition. Abstract Non-intrusive load monitoring (NILM) techniques have recently attracted much interest, since they allow to obtain latent patterns from power demand data in buildings, revealing useful information to the expert user. Unsupervised methods are specially attractive, since they do not require labeled datasets. Particularly, non-negative matrix factorization (NMF) methods decompose a single power demand measurement over a certain time period into a set of components or “parts” that are sparse, non-negative and sum up the original measured quantity. Such components reveal hidden temporal patterns which may be difficult to interpret in complex systems such as large buildings. We suggest to integrate the knowledge of the user into the analysis in order to recognize the real events inside the electric network behind the learnt patterns. In this paper, we integrate the available domain knowledge of the user by means of a visual analytics web application in which an expert user can interact in a fluid way with the NMF outcome through visual approaches such as barcharts, heatmaps or calendars. Our approach is tested with real electric power demand data from a hospital complex, showing how the interpretation of the decomposition is improved by means of interactive data cube visualizations, in which the user can insightfully relate the NMF components to characteristic demand patterns of the hospital such as those derived from human activity, as well as to inefficient behaviors of the largest systems in the hospital. [ABSTRACT FROM AUTHOR]

Abstract Asset Score is a standardized rating system and tool for assessing a building's energy-related systems in the United States. The web-based tool models building energy use under standard operating conditions to rate the energy efficiency of the as-built building systems and enable level comparisons of building assets. With basic characteristics entered by users, the tool creates simplified EnergyPlus building models to support the rating analysis. However, even with a reduced set of model inputs, data collection remains a challenge and the commercial building market demands a more simplified entry point to the rating system. This paper discusses a hybrid method that combines regression models with real-time simulations to allow users to enter as few as seven building parameters to quickly assess the building energy performance prior to a full-scale analysis. Built upon large-scale building stock simulations, a random forest approach was used to develop a set of regression models for various building use types. The majority of the Asset Score tool inputs were sampled extensively and fed into the regression models. These were combined with inferred inputs and user-defined uncertainty levels to create a distribution of possible energy use intensities for the building and its Preview score. With additional user inputs, the regression model can be transferred to an energy model for a full-scale energy simulation. The streamlined Asset Score Preview assessment provides an easy entry point to a full Asset Score assessment. It also enables users who manage a large number of buildings to screen and prioritize buildings that can benefit most from a more detailed evaluation and possible energy efficiency upgrades without intensive data collection. [ABSTRACT FROM AUTHOR]

Two major trends are changing the face of the construction industry. Sustainability concerns are driving innovations to improve building's energy efficiency while advances in prefabrication are improving buildings’ speed, cost, and quality. As new materials and techniques emerge, their overall environmental impact must be evaluated using techniques such as life cycle assessment (LCA). This paper reports a life cycle assessment (LCA) of an innovative magnesium oxide structural insulated panel (MgO SIP) used for a high-performance smart home in Vancouver. The LCA compares the environmental impacts across six indicators for the MgO SIPs, traditional SIPs, and traditional stick-frame construction across the life cycle phases of raw material extraction, manufacturing, transportation, construction, and operation. The results show that the MgO SIPs do not outperform conventional alternatives notably due to the long-distance transportation of materials. However, further LCA of hypothetical scenarios demonstrates that MgO SIPs have a great potential to become more environmentally friendly than the conventional alternatives by sourcing MgO domestically, implementing local or onsite manufacturing, and designing the MgO SIPs without oriented strand board. Although the results are context-dependent, the investigation of hypothetical scenarios offers insight to improve the environmental performance of this innovative product. [ABSTRACT FROM AUTHOR]

Cooling demands of commercial buildings present a relevant challenge for a sustainable future. They account for over half of the overall energy needs for the operation of an average office building in warm climates, and this situation is expected to become more pressing due to increasing temperatures in cities worldwide. To tackle this issue, it is widely agreed that the application of passive strategies should be the first step in the design of energy efficient buildings, only using active equipment if it is truly necessary. Nonetheless, there is still further need for information regarding the potential limits derived from their application. This paper explores the effectiveness of selected passive cooling strategies in commercial buildings from warm climates, defining performance ranges based on the assessment of multiple scenarios and climate contexts. This task was conducted through the statistical analysis of results from documented research experiences, to define overall ranges and boundary conditions; and through software simulation of selected parameters to isolate their impact under a controlled experimental setup. General findings showed that the mere application of passive strategies is not enough to guarantee relevant savings. Their effectiveness was conditioned to both the harshness of a given climate and different building parameters. Specific recommendations were also discussed for the selected passive strategies considered in the evaluation. [ABSTRACT FROM AUTHOR]

Centralized air distribution systems in non-residential buildings are characterized by an extensive air distribution network, that has to be built in a building environment with finite degrees of freedom. The ductwork layout, i.e., the network structure of the ducts, as well as the number and location of the fans, has a large impact on the total cost and performance of the air distribution system. Nevertheless, existing air distribution system design methods are limited to the sizing of each duct (and fan) in the network. The layout itself is considered predetermined, and thus not explicitly taken into account for optimization. In this paper, we meet this shortcoming by presenting the air distribution network design optimization method, that is able to calculate the optimal air distribution system configuration, i.e., the optimal layout and duct and fan sizes, while minimizing the total cost of the air distribution system. A multi-start local search algorithm is developed, consisting of a constructive and a local search phase. In the first phase, multiple air distribution system configurations are generated, and evaluated for feasibility. In the local search phase, all feasible solutions are further optimized in terms of material costs by decreasing and increasing the duct diameters following the steepest descent/mildest ascent approach. An application of the algorithm on a realistic test case demonstrates its usefulness in practice. [ABSTRACT FROM AUTHOR]

Generic model-assisted control algorithms for building energy systems achieve an energy-efficient building operation while the implementation effort is lower than in the case of a taylor-made automation system. In this paper, a generic distributed simulation-model-assisted and exergy-based control algorithm is presented, which is applicable to typical building energy systems (BES). It exploits dynamic nonlinear simulation models from an open-source Modelica library and makes use of sequential neighbor communication. In the supply chains of a BES, the algorithm performs multiple optimizations of small subsystems by considering pre-defined values of pre-defined coupling variables. The objective function is the sum of the exergy destruction and loss, which is based only on measurements without additional information such as monetary costs. In a simulation case study, an open-loop and a closed-loop version of the algorithm are compared to a control system based on rules and feedback controllers that was optimized manually for this particular scenario to provide a benchmark. The tracking error of the closed-loop algorithm is close to the benchmark. The open-loop algorithm achieves an energy consumption close to the benchmark. These results show that the algorithm finds suitable solutions automatically whereas the rule-based control system cannot be expected to perform equally well if boundary conditions were changed. [ABSTRACT FROM AUTHOR]

The application of building archetypes is a widespread approach used in urban building energy modeling. Working with archetypes has a range of benefits, but it is important that modelers avoid using oversimplified approaches when establishing the archetype as they lead to loss of uncertainty and, consequently, to models with inferior predictive capabilities. In this paper, we propose a multilevel take on the challenge of establishing archetypes. A simultaneous modeling and calibration framework is formulated using Bayesian inference techniques – a technique that allows for the propagation of uncertainty throughout the calibration process. By means of hierarchical modeling, information from training buildings is partially pooled together to form an optimal solution between separate building energy models and a completely pooled model. This enables the inference of uncertain archetype parameters that are less prone to building outliers than what is achieved using ordinary aggregation of individual building estimates. The proposed framework incorporates dynamic building energy modeling of arbitrary temporal resolution where uncertain parameters are fitted for individual building models and the archetype model simultaneously. The application of the framework is demonstrated using case-study data from the Danish residential building stock, containing 3-hourly measurements of energy use for 50 training buildings. The model is tested for the prediction of 100 out-of-sample test buildings’ aggregated energy use time series on a holdout validation period. With a prediction error of only NMBE = 2.9% and CVRMSE = 7.8%, the archetype framework promises well for urban modeling applications. [ABSTRACT FROM AUTHOR]

In most countries, electricity is charged depending on the time of use, which usually includes two tariffs: the low tariff, during night time, and the high tariff, during daytime. On top of their energy payment, large electricity consumers pay a monthly fee per kW of peak demand. Therefore, installation of stationary battery storage can reduce electricity payments for large consumers in two ways: by reducing the peak demand and by shifting consumption from the high tariff to the low tariff. The aim of this paper is to formulate a model to determine optimal energy and power capacity of a stationary battery storage in order to minimize electricity payments. Since the future electricity consumption is uncertain, after formulating the deterministic model, two additional models that consider uncertainty are introduced. The first one is the stochastic model, which considers uncertain scenarios, and the second one is the robust model, where uncertainty is represented by only an uncertainty set, without an assumption on the distribution of uncertainty within this set. The proposed models are tested and compared on a real-world load data of a hotel in Croatia. The case study indicates that deterministic and stochastic formulations result in slightly better investment decisions than the robust formulation. [ABSTRACT FROM AUTHOR]

Majority of building energy consumption is used to heat and cool enclosed spaces. An innovative ultra-high-performance fiber-reinforced concrete (UHP-FRC) façade system could potentially reduce this energy consumption by utilizing UHP-FRC's high structural strength and ductility hence more space for insulation. The energy performance assessment of innovative façade systems such as UHP-FRC panels could be misleading if the effect of building types and climate contexts on building energy consumption is not considered. Moreover, thermal bridging and hygrothermal analyses of UHP-FRC panels are needed to investigate the heat and moisture transfer within the panels in details. The objective of this paper is to investigate the combined effect of different building types and climate conditions on these panels’ energy performance and analyze the heat and moisture behavior within the panels in a detailed assembly scale. Numerical heat and moisture transfer simulations were conducted to evaluate the amount of risk of thermal bridging and risk of mold growth within innovative UHP-FRC façade systems. A probabilistic simulation-based building energy performance analysis was conducted to investigate the combined effect of different building types and climate conditions on the energy performance of UHP-FRC panel systems. The analysis was conducted for fourteen U.S. Department of Energy prototype buildings in fifteen climate zones (210 scenarios). The results of thermal bridging analysis showed that the UHP-FRC panel assembly provides unique thermal properties with higher thermal resistance compared with the conventional panel assembly. The UHP-FRC panel assembly minimizes the thermal bridging by eliminating the structural rebars. However, the energy savings of using UHP-FRC panels depend on the building type and climate condition. On average, energy savings are higher in colder climates (e.g., Fairbanks) than those in temperate climates (e.g., San Francisco). Also, buildings dominated by internal loads seem to benefit the least from UHP-FRC. The hygrothermal analysis also showed that the UHP-FRC panel assembly's performance is superior than the conventional panel in terms of moisture transfer and the risk of mold growth. [ABSTRACT FROM AUTHOR]

Bio-based insulation materials (such as wood or hemp) are emerging as a promising alternative in building envelope applications, aiming at improving in-use energy efficiency. When compared to common insulation materials (rock and glass wool or petrol-based foams) bio-based materials present the advantage of being renewable, with a low embodied energy and CO 2 neutral or negative. Moreover, these materials have a distinct hygrothermal performance, as the sorption/desorption of water vapour in their porous structure, in dynamic equilibrium with their surrounding environment, constantly modifies their hygric and thermal properties while causing energy transfers itself. In this paper, the hygrothermal performance of two different bio-based materials in outdoor conditions is evaluated. The first is an innovative light-weight composite made from corn pith and alginate. The second a commercially available wood insulator. The materials are tested alone and as components of external thermal insulation systems (ETICS) and compared to a conventional polystyrene foam. The results show how the sorption process influence the hygrothermal performance of the materials when the surrounding conditions are modified. When subjected to cyclic changes in temperature and relative humidity, the bio-based materials tested show a lower temperature variation than polystyrene. This is in part due to their lower thermal diffusivity, but also to the water absorption and desorption mechanisms occurring within the materials, which were measured by the change in mass of the materials during the tests. The differences in the thermal performance were more noticeable when the insulation materials were tested alone than when these were tested as a part of an ETIC System. [ABSTRACT FROM AUTHOR]

Due to the energy crisis and the awareness of sustainable development, the research on energy-efficient buildings has increasingly attracted attention. To achieve this objective, one important factor is to capture occupancy properties for building control systems, which refers to occupancy modeling in buildings. Due to the complexity of building occupancy, previous works try to simplify the modeling with some specific assumptions which may not always hold. In this paper, we propose a Generative Adversarial Network (GAN) framework for building occupancy modeling without any prior assumptions. The GAN approach contains two key components, i.e. a generative network and a discriminative network, which are designed as two powerful neural networks. Owing to the strong generalization capacity of neural networks and the adversarial mechanism in the GAN approach, it is able to accurately model building occupancy. We perform real experiments to verify the effectiveness of the proposed GAN approach and compare it with two state-of-the-art approaches for building occupancy modeling. To quantify the performance of all the models, we define five variables with two evaluation criteria. Results show that our proposed GAN approach can achieve a superior performance. [ABSTRACT FROM AUTHOR]

Numerous data-driven models have been successfully adopted for electrical energy consumption forecasting at building and larger scales. When the data set for forecasting is multi-sourced, heterogeneous or inadequate, single data-driven model may lead to convergence problem or poor model accuracy. The combination of advanced evolutionary algorithms (EAs) and data-driven models is proved effective in terms of prediction accuracy and robustness improvements. However, some of them are very time consuming to converge. In this paper, a novel EA, i.e. teaching learning based optimization (TLBO), is proposed for short-term building energy usage prediction. To enhance its convergence speed and optimization accuracy, the basic TLBO algorithm is further modified in three aspects. The improved algorithm is combined with artificial neural networks (ANNs) and applied to hourly electrical energy prediction of two educational buildings located in USA and China respectively. Performance comparisons show that the proposed model has superior performances than previously reported GA-ANN and PSO-ANN methods in terms of convergence speed and predictive accuracy, and is suitable for online energy prediction in the future. [ABSTRACT FROM AUTHOR]

Over the last few years, studies have predicted an increase in the overall air temperature due to climate change. Today's society is already sensing this change, which could have a negative impact on the environment and efforts are being made to seek all possible measures to curb it. One of the consequences of this temperature rise would be its effect on indoor comfort within buildings, which may cause higher energy consumption and operational costs, while reducing the useful lifetime of air-conditioning equipment. In this paper, an existing zero energy building (ZEB) is being studied to understand the possible effects of climate change on its zero energy status. The building is also a zero carbon building because all of its generated energies come from renewable sources (biomass, geothermal and solar photovoltaic systems). The building LUCIA has the highest innovative technologies in energy systems, design and construction elements and is currently considered as one of the top three buildings with the highest LEED certification in the world. According to current European regulations, buildings will tend to become self-sufficient in terms of energy after 2020, and therefore this study will help us to understand the changes in energy consumption within a long-term timeframe, for such zero-energy buildings. With the aid of the Design Builder version 5 software and its EnergyPlus building energy engine, a building model is simulated and energy consumption is analyzed for the years 2020, 2050 and 2080 timeframe. The climatic conditions pertain to the city of Valladolid, Spain, which has a continental climate, while the expected changes in climatic conditions have been produced through the methodology developed by the University of Southampton, called CCworldweathergen. Results have shown that the cooling demand would significantly increase for the years 2050 and 2080, while space heating would drop. This will increase the overall demand for burning more biofuels to cover the added demand in absorption cooling systems. Moreover, the previously excess generated electricity of the building by photovoltaics would then be totally consumed within the building due to increased demand. This implies that the installed systems will operate for longer hours, which will increase maintenance and replacement costs. As a result of this study, it becomes possible to quantify the expected changes in energy consumption and prepare preventive actions to anticipate this change, while improving the management and control of both the energy systems and the building. [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]

A pronounced gap often exists between expected and actual building performance. The multi-faceted and cross lifecycle causes of this performance gap are found in design assumptions, construction issues and commissioning and operational compromises. Some important factors are firmly rooted in the lack of interoperability around building information. New solutions to the interoperability challenge offer the potential to leverage and reuse available heterogeneous data in a manner that can significantly assist building performance assessment. Linked data provides an open, modular and extensible solution for the challenge. However, in the buildings domain, the integration of rule-based performance metrics and contextual information has yet to be formally established. This paper describes an approach to the provision of in-depth building performance assessment through the integration of OpenMath and linked data. An ontology describing performance metrics in RDF is presented, together with an automated metric evaluation solution using multi-silo queries and computer algebra systems, providing a flexible, automated and extensible mechanism for the assessment of building performance. Building managers and engineers can simultaneously analyse time-series building performance at a range of levels, without burdensome manual intervention such as is the case with traditional solutions. A test implementation on a large university building highlights the potential of this solution. [ABSTRACT FROM AUTHOR]

The cost-optimal analysis represents a useful tool to stimulate the refurbishment of existing buildings, highlighting the minimal global cost that private or public users have to sustain in order to attain appreciable energy savings in the building life span. The identification of precise interventions on the building-plant system could steer legislators to the emanation of appropriate financial incentives in order to make the refurbishment of existing edifices more attractive. However, the cost-optimal solutions cannot be generalized as they are strongly influenced by the initial conditions and by the climatic context. In this paper, a traditional social housing unit, realized in Italy during the 1970s, largely widespread and strongly energy-consuming, was analysed in two different climatic zones belonging to the Italian territory. Suitable interventions were identified for the reduction of energy requirements for heating, cooling and domestic hot water production. These analyses were carried out by using the same simulation tool for energy and economic performances, highlighting the deviances among the cost-optimal solutions, the n-ZEB target and the minimal interventions for the containment of energy consumptions imposed by the current Italian legislation for buildings subjected to refurbishment. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the influence of building fabric, services and occupant related factors on actual energy use of six case study dwellings, located in three new low energy social housing developments in UK, covering a variety of built forms and construction systems (timber frame, hempcrete, steel-frame). Physical monitoring of indoor environment and window-opening is cross-related with building fabric and systems’ performance, and qualitative data gathered through occupant surveys, review of control interfaces and handover guidance, to understand the causes of the gap between modelled and measured energy use. Actual energy use is found to exceed design expectations by a factor of three, questioning the need for whole-house mechanical ventilation heat recovery (MVHR) systems at measured air permeability rates of 6 m³/(h.m²) against the design target of 3 m³/(h.m²). Lack of proper commissioning of MVHR and heating systems, combined with inadequate user comprehension about their operation and control leads to occupant ‘misuse’ wherein systems are de-activated, thereby negatively affecting indoor air quality. This is confounded by occupant factors related to higher demand temperatures, unexpected opening of windows during winters due to under-performance of MVHR combined with habitual behaviours, and over-use of heating systems to compensate for higher than expected air permeability. [ABSTRACT FROM AUTHOR]

This study investigates an energy-inefficient council housing tower block in London, due for retrofit, by exploring the correlations between occupancy and energy consumption patterns, thermal comfort and building energy performance in the winter. The aim of this study is to evaluate the building performance and develop a reliable building simulation model to be employed in the second phase of the study for developing an energy-efficient and cost-effective retrofit strategy to support the council's plans. The research seeks to demonstrate the significance of using dominant occupancy and energy use profiles as opposed to relying on standardised profiles when calculating building energy consumption using building simulation software. The paper reports on the results from the first phase of the study where a quantitative methodology; including a questionnaire, structured interviews, indoor monitoring, and building simulation modelling was adopted. The results provide evidence that occupants’ socio-demographic characteristics have a considerable impact on household energy consumption and fuel bills. The results also show that indoor environmental issues experienced in many flats are partly attributed to the thermally inefficient building envelope and partly due to occupants’ patterns of operating their homes with evidence of excessive heating energy use in attempts to alleviate the indoor issues experienced. [ABSTRACT FROM AUTHOR]

Demand-controlled-ventilation (DCV) refers to a ventilation system with controlled air flow rate based on indoor air quality. DCV operates at reduced air flow rates during most of the operation time. Therefore, less energy is required for fan operation, compared to a constant-air-volume (CAV) ventilation system. Typically, DCV has a two-layer control with variable-air-volume (VAV) valves, and a fan speed control to maintain a constant-static-pressure in the duct system based on a pressure set point. However, this nominal design based fan pressure setpoint is higher than required when all VAV-valves are closed to a certain extent. Therefore, advanced pressure-reset (PR) control - resetting the pressure set point - potentially reduces fan energy use even further. This paper assesses the impact of fan control on both fan energy use and ventilation performance in DCV system of a densely occupied office. Results of a simulation model and realistic measurement setup are compared. The PR control, using air flow rate and VAV-valve position measurements as feedback, causes significantly reduction on fan energy use. These reductions compared to conventional DCV and CAV respectively, are approximately 10% and 72% in case of high occupancy and 50% and 93% in case of low occupancy. Largely, DCV with PR control is strongly considered, especially when occupancy is often expected to deviate significantly from the nominal conditions. Moreover, both simulations and measurements show that there is a clear trade-off between air flow rate deficit and fan energy use, when the fan energy use is lower, the air flow rate deficit is higher and vice versa. Furthermore, the results show that VAV-valve accuracy, characteristics and its lower operational limit hamper the ventilation system in achieving the predicted performance as in the simulation. [ABSTRACT FROM AUTHOR]

Coupling auxiliary cooling devices with ground source heat pump (GSHP) systems in cooling dominated areas can effectively solve the ground thermal imbalance problem. However, the input capacity of the auxiliary heat rejecter directly affects the performance of such hybrid ground source heat pump (HGSHP) systems. This paper presents an investigation on the optimal cooling tower input capacity of a cooling tower assisted GSHP system through both experiments and simulations. The experiments were carried out based on a HGSHP system implemented in an office building and the experimental results were used to validate a numerical model. A simulation system of the cooling tower assisted GSHP system was then developed using TRNSYS and validated against the experimental data collected. The impacts of the cooling tower input capacity on the soil temperature and the system performance were simulated. The results showed that the soil heat accumulation could be effectively alleviated when the cooling tower input capacity ratio (CTICR) was greater than 50%. The optimal cooling tower input capacity was highly dependent on the operation scenario used. The optimal CTICR under two operation scenarios considered was around 54%, while that under the other operation scenarios was around 63%. The control strategy based on the fixed temperature difference between the cooling water leaving the heat pump and the ambient air dry-bulb temperature was found to be the optimal control strategy for the system studied. [ABSTRACT FROM AUTHOR]

The extensive use of thermal insulation in low-energy dwellings makes them susceptible to heat trapping in warmer periods. Construction elements with dynamically adjustable thermal transmittance properties, so-called dynamic insulation systems, can be a promising solution for reducing this overheating problem, while simultaneously lowering the energy consumption for heating. In this paper, the performance of a novel type of closed-loop forced convective dynamic insulation system is investigated. A simulation model to predict the performance of the dynamic insulation is developed in EnergyPlus. First results show that a ninefold higher U-value can be achieved in comparison with the insulating state of the system. Multiple case studies have been analysed to study the behaviour and performance of the system. It was found that the dynamic insulation system can reduce the energy consumption and increase the indoor thermal comfort of a typical residential building, while using less auxiliary energy than comparable passive cooling systems, such as night ventilation. Applying dynamic insulation to a façade construction with a heavyweight interior partition and lightweight exterior partition resulted in the best performance. If a small period of thermal discomfort is allowed, the closed-loop dynamic insulation system can obviate the need for an active cooling system in the climates of Helsinki, Amsterdam and Stuttgart. [ABSTRACT FROM AUTHOR]

This paper presents a two year long empirical study on the effects of fabric retrofit insulation on a high rise social housing building (a 23-storey block with 157 flats) in Newcastle upon Tyne (UK). The study has followed a quasi-experimental approach coupled with qualitative methods and examines whether temperature take-back is taking place; whether it operates independently of socio economic characteristics due to saturation effects; and the relationship between temperature take-back, physical factors and occupant’s behavioural change. The presented empirical evidence suggests that, first, temperature take-back as extra warmth (or energy consumption savings) is not occurring. Second, the saturation effect has taken place. This supports the assumption that temperature take-back decreases owing to saturation effects when pre-intervention internal temperatures saturate (approaching 21 °C) in lieu of the hypothesis that low-income householders take the benefits of an energy efficiency intervention as extra warmth rather than energy savings. Third, an upper level or maximum take-back temperature was achieved for the dwellings ranging from 20.85 °C to 24.81 °C. Fourth, behavioural factors such as turning on the heating appear to be less relevant than physical factors such as energy-efficiency improvements to explain the increased of standardised mean internal air temperature. The study also suggests that local building characteristics (e.g. heating pipes routing) play an influential role and that to evaluate appropriateness of retrofitted energy-efficiency insulation measures pre-intervention variables such as internal temperatures, heating system and building fabric performance should be taken into account. [ABSTRACT FROM AUTHOR]

Achieving low operational energy (OE) consumption in high heating and cooling situations typically leads to well-insulated buildings. In those cases, embodied energy (EE) can exceed the operational share. Specific literature refers mostly to heating-dominated residential buildings, with a clear focus on European, Asian, and North American countries. Information on embodied impacts of buildings other regions is virtually inexistent. This paper aims at estimating lifecycle energy and greenhouse gases (GHG) emissions of selected design versions of a photovoltaic-powered Living Lab in Campinas, Brazil; and at finding the embodied-to-operational impact ratios as well as the main contributors to those overall impacts. Homer Energy software supported sizing of photovoltaic (PV) arrays for ten energy compensation scenarios to, based on simulated OE, determine the feasibility threshold for onsite generation admitted by the building design. We then modelled lifecycle energy and GHG emissions for the net zero (NZE) and threshold energy positive (E + ) versions of the case study design. The Cumulative Energy Demand (CED) and the CML 2001 v.2.05 methods supported embodied energy and global warming potential (GWP) calculations in SimaPro 7.3. The E + building compensates its OE plus non-renewable energy embodied in building products. Steel frame and partitions were the largest contributors to EEG in building products, whilst the insulated façade panels and PV array performed key energy performance roles at comparatively lower embodied impacts. Shifting from NZE towards E + status discretely increased the embodied-to-operational energy ratio (EE:OE), at similar embodied-to-operational GHG emissions (EG:OG) ratios. Pre-use share of lifecycle CED was slightly surpassed by the operational one, whilst responding for 60% of lifecycle GWP. Material replacement over the reference service life contributed significantly to operational impacts. EOL treatment had negligible effect on lifecycle impacts. EE more than tripled OE and embodied emissions exceeded OG by a factor of seven. EEG prominence confirms the crucial need for a harmonized calculation approach, as experienced for operational stage accountancy over the recent years. We acknowledge the high uncertainties involved in using simulated over measured OE consumption and in using foreign LCI databases. The former limitation can be solved by monitoring operational performance upon projects completion. This study offers practical and detailed reference for LCA practitioners in all countries facing the latter challenge, which will persist until integrated national LCI databases finally become available. [ABSTRACT FROM AUTHOR]

To reduce global greenhouse gas emissions associated with building energy use, owners of large building portfolios such as university campuses frequently rely on building energy models (BEM) to better understand potential costs and benefits of retrofits. Model development workflows that are designed for individual buildings require a level of effort that would be time and cost prohibitive to apply to such campuses which often include hundreds of diverse-use buildings. While smaller campuses can effectively utilize the traditional BEM approach to study retrofit scenarios, this option is therefore not feasible for larger campuses. Large universities have instead utilized a combination of statistical and spreadsheet models which may not fully capture the unique architectural features, programmatic requirements, and systems configurations of individual campus buildings. With the goal of overcoming these limitations, two separate urban energy models, that employed considerably different methodologies, were developed for the campus of the Massachusetts Institute of Technology to evaluate future energy scenarios with an appreciably smaller effort vis-à-vis developing building-by-building energy models. This study reviews these two models with regards to their setup and calibration effort, ability to model individual building energy use, and the accuracy in predicted savings from implementing a variety of retrofitting measures. The paper identifies both models’ strengths and limitations and suggests best practice procedures for administrators of other campuses interested in undergoing a similar exercise. [ABSTRACT FROM AUTHOR]

In cold climates, the electrical power demand for space conditioning during certain periods of the day becomes a critical issue for utility companies from an environmental and financial point of view. Shifting a portion or all the demand to off-peak periods can help in reducing the peak demand and stress on the electrical grid. To predict the required energy that needs to be stored, predictive supervisory control strategies such as Model Predictive Control (MPC) have been developed, by which the future operating modes of storage systems can be preplanned. However, control strategies like MPC requires a building model and an optimization algorithm. Their development is time-consuming and also requires high implementation cost. This paper is aimed at developing a new simplified predictive controller to manage an electrically heated floor for shifting and/or shaving the building peak energy demand. The function of the developed controller is to increase the rate of energy storage during off-peak hours and to decrease it during peak periods, while maintaining occupants’ thermal comfort. To achieve this goal without using a detailed building model, a simplified solar predictive model, using available online weather data has been proposed. The controller approach is based on a learning process; it takes building responses of previous days into consideration. The developed algorithm was applied on two models of a single-storey building, with and without basement. Results show a significant decrease in thermal discomfort, average applied powers during peak periods and mid-peak periods. The approach has also proven to be financially attractive to both supplier and consumer. [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]