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Highlights • A unified method is raised to analyze the practical performance of 32 heat pump systems for space heating with different heat sources. • Over-sized capacity design, over centralized system design, unreasonable control strategy and lack of maintaining are found universally existed in the investigated systems. • Decentralized and reasonable system design, accurate and efficient control strategies are suggested. Abstract This paper introduces continuously field test results on operational energy performance of 32 heat pump systems for space heating with various heat sources in cold region of China. Therefore, normalized energy performance index for the holistic heat pump based space heating system including compressor electricity use, circulating pumps energy use for both heat source and heat sink, were introduced to evaluate and compare between different systems or different control strategies. Results showed that over-sized heat pump capacity design and install declined heat pumps efficiency during whole heating season especially in partial load regime, and solo heat pump station with large heating distribution networks led to dramatic heat loss and hydraulic unbalance problems. In addition, complicated control strategy for both heat pumps and circulating pumps did not performed properly according to building heat demand fluctuating and heat source temperature variation during whole winter. The paper disclosed clearly that optimized design and operation of the holistic heat pump based space heating systems during the heating season are essential to ensure the actual energy performance for any kinds of heat pumps rather than believing in theoretical assumption. [ABSTRACT FROM AUTHOR]

• Modelling energy savings of renovations in the Dutch non-profit housing stock. • Assessment of 1.6 million dwellings, 21 building features and 3 empirical models. • Empirical models outperform the theoretical building energy model. • Shortcomings exist when predicting effects of specific energy-saving interventions. In Europe, the energy performance of dwellings is measured using theoretical building energy models based on the Energy Performance of Buildings Directive (EPBD), which estimates the energy consumption of dwellings. However, literature shows large performance gaps between the theoretically predicted energy consumption and the actual energy consumption of dwellings. The goal of this paper is to investigate the extent to which empirical models provide more accurate estimations of actual energy consumption when compared to a theoretical building energy model, in order to estimate average actual energy savings of renovations. We used the Dutch non-profit housing stock to demonstrate the results. We examined three empirical models to predict the actual energy consumption of dwellings: a linear regression model, a non-linear regression model, and a machine learning model (GBM). This paper shows that these three models alleviate the performance gap by giving a good prediction of actual energy consumption on sectoral cross-sections. However, these models still have shortcomings when predicting the effects of specific renovation interventions, for example newly introduced heat pumps. The non-linear and machine learning model (GBM) outperform the theoretical model in terms of estimating energy savings through renovation interventions. [ABSTRACT FROM AUTHOR]

Abstract Convenience stores are known to have higher Energy Use Intensities (EUIs) than most other commercial building types. However, convenience store energy performance analyses have not been systematically investigated. Moreover, current national convenience store benchmarks are inconsistent from one data base to another due to lack of relevant energy data. This paper assesses the energy performance of more than five hundred convenience stores in the same fleet in Eastern United States. The investigation aims to establish benchmarks for convenience stores with and without gasoline pumping stations. The main factors influencing the actual convenience store building energy use were determined. Multiple regression models were developed to find relationships between annual energy consumption per unit area and gross floor area, customer transaction count, building operating year, etc. The statistically characterized results are meant to serve as a reference data set in comparing the whole-building energy performance index for buildings of similar functionality. The statistical correlation analyses can strengthen the robust prediction of energy performance in convenience stores, enabling proper assessment of energy conservation measurements (ECMs) for convenience store operations, as well as guiding additional such energy performance studies. [ABSTRACT FROM AUTHOR]

Abstract: This paper aims to study the various parameters that affect the energy performance of commercial buildings in Singapore. The parameters are diverse, ranging from characteristics of construction of the walls and windows, to the various system settings and types within the building. Building energy performance is measured via two key indexes, namely, the Envelope Thermal Transfer Value (ETTV) and the annual cooling energy requirement (E c). Parameters related to these two indexes are identified. An additional parameter, the solar absorptance of the wall, is further incorporated to calibrate the ETTV equation. A relative ranking on the functional parameters of ETTV has been performed to evaluate their effectiveness in lowering the ETTV of buildings. In addition, the impact of using cladding on ETTV is also studied. A correlation for E c, expressed in the form of a simple linear equation, has been developed. This correlation accounts for the internal building loads, envelope loads, operating schedules and efficiency of the cooling equipment. Finally, ETTV and E c have been employed to study the effects of chiller over-sizing and ventilation rates on building cooling energy. In the pursuit for better energy-efficient buildings, the approach presented in this paper contributes to the construct of sustainable energy-efficient built-environment. [Copyright &y& Elsevier]

With the world rapidly urbanizing, addressing the energy intensive urban built environment is becoming increasingly important. Cities across the United States and the world are turning to energy benchmarking as a means of understanding the relative energy efficiency of their building stock and identifying potential opportunities to reduce energy usage. Benchmarking utilizes building characteristics and energy use data to measure a building’s energy consumption against a performance baseline and derive a level of energy efficiency. Over twenty cities in the United States and many others across the world have passed laws mandating the collection and disclosure of energy use data to enable benchmarking and pinpoint potential energy saving opportunities. However, municipalities are struggling to convert this data into actionable insights and identify which buildings are prime candidates for energy efficiency interventions. Although an extensive body of work exists on benchmarking building energy performance, previous works are limited in their ability to leverage such emerging data streams and conduct analysis at the city scale. Moreover, previous methods are largely based on black-box models that limit the interpretability of results and in turn hinder the ability of policy-makers to employ such models in their policy design and decision-making processes. In this paper, we propose DUE-B, a new Data-driven Urban Energy Benchmarking methodology based on recursive partitioning and stochastic frontier analysis. To test DUE-B, we evaluate its performance using real energy and building data from over 10,000 buildings in New York City, and we compare the results to other common benchmarking models using the Kendall tau-b correlation coefficient. Results indicate that DUE-B is more robust than conventional benchmarking methods in respect to identifying subsets of efficient and inefficient buildings. Furthermore, we highlight how results from DUE-B can be utilized by municipal officials and other policy-makers to target inefficient buildings for energy efficiency interventions, incentives, and programs. Specifically, we indicate how DUE-B can be utilized by municipalities to target the most inefficient buildings for subsidized onsite energy audits and less inefficient buildings for less capital-intensive energy efficiency strategies such as incentives and educational programs. In the end, more robust benchmarking methods like DUE-B have the potential to enhance the efficacy of municipal energy efficiency programs and help transition cities to a more sustainable energy future. [ABSTRACT FROM AUTHOR]

This paper presents the results of the validation of an experimental method for studying the thermal benefits of green façades. The main aim is to evaluate the impact of plants occultation on energy performance of a vertical wall in the temperate climate of the city of Lille in northern France. An experimental platform consisting of three identical prototypes (three boxes as thermal labs) has been designed and instrumented. Each prototype has been highly insulated from each face except from the vertical southern wall which was realized with a poor thermal conductivity material. The following measurements were taken: ambient temperature (outside and inside thermal labs), external and internal surface temperatures of southern walls, heat fluxes transferred through south verticals walls (reference and vegetalized walls), solar incident radiation and wind velocity variation under instantaneous real climatic conditions. This enabled the analysis of the variation of energy balance according to the presence or not of a shading effect on the south vertical walls as well as their coverage rate. Several tests were performed on the three experimental thermal labs by imposing a leaf coverage rate which differs during each measurement. The results have shown that masking reduces the outside temperature and enhances the interior thermal comfort especially during summer. [ABSTRACT FROM AUTHOR]

With the increased complexity of air conditioning systems, the computational load and complexity of real-time optimization appear to be challenging for applications. To overcome the challenge, multiplexed optimization has been proposed in which multiple set-points are sequentially optimized and updated one by one. In such a way, it can achieve equivalently-good energy performance but with exponentially reduced computational load if compared with those traditional methods that optimize all set-points simultaneously. In fact, the time instant for each set-point optimization and the set-point optimization sequence have impacts on the overall performance of the multiplexed optimization. Considering such impacts, this paper proposes a new multiplexed optimization method for enhanced performance. In the proposed method, optimization is activated as the system energy efficiency is low. The set-point optimization sequence is selected according to their impacts on the system energy performance. The one with the most energy saving potential will be firstly optimized. The case study results demonstrate the improved performance of the proposed method in terms of energy, computation load and system stability when compared with the conventional multiplexed optimization. The proposed method can be applied in complex air conditioning systems for energy saving, computation load reduction and system stability improvement. [ABSTRACT FROM AUTHOR]

The reduction of energy consumption and CO 2 emissions in buildings has become an essential field of study in the recent years. Simplified design tools, used in the first design stages, can be of great help in adopting concrete decisions that will, at the end, allow these to be reduced. This paper presents a new predictive model for office buildings in Chile. Starting from the 1,386,000 study cases pursuant the ISO 13790:2008 standard, 18 multivariable regression models have been generated, 9 for energy consumption and 9 for CO 2 emissions., They have been adapted to each climatic zone in Chile. In these case studies, 8 fundamental variables have been considered to cover the design parameters. This research considers number of stories (NS), floor area (FA), form ratio (FR), window-to-wall ratio (WWR), coefficient of performance (COP), Energy efficiency ratio (EER), heating emission factors (HEF) and cooling emission factors (CEF). The models generate an R 2 between 91.81% and 98.05% for energy consumption and between 96.83% and 99.56% for CO 2 emissions, with the results of this research being incorporated into future regulations and into the first stages of design for office buildings in Chile. As an expected outcome, the model will contribute to reduce, or at least contain, energy consumption and CO 2 emissions associated with office buildings in the future. [ABSTRACT FROM AUTHOR]

These days, many studies are about the performance of some shading devices. Many engineers think the performance of internal shading systems is inferior to external systems. Because when using internal shades, the solar heat has already entered the internal spaces and has become trapped. However, in real applications, external shading is difficult to use, easily damaged and prone to dirt buildup. Internal shading is more flexible, cheaper and easier to repair. Some engineers doubt the validity of this traditional thinking and believe internal shading may be effective and useful to some extent because many occupants use internal blinds to minimize air conditioning costs. In this paper, the possibility of substituting the external shades with an internal ones using high reflectivity materials was studied through experimental tests and simulation validations. The results indicate that an internal shading system may be as effective as an external system if proper materials are used. Such substitution can reduce the overall cost of a shading system and can provide flexibility to the design of building facades. A grey relational analysis of the internal shade optimization is further presented so that the significant factors influencing the internal shading device performance are better understood. These factors should be taken into consideration during the design. [ABSTRACT FROM AUTHOR]

Summary The article deals with the main problems arising during the sustainable renovation process and energy refurbishment of historical architecture. In particular, it focuses on the feasibility study for a huge historical listed building, aiming at its progressive and complete re-utilization as university campus, respectful of the many cultural values of which it is the depository. The complex of the ‘Albergo dei Poveri’ was built in Genoa between the late seventeenth century and the middle of the nineteenth century, as a monumental structure for charitable purposes. Given its size and location in the heart of the city, it still represents an important urban structure and a great opportunity for urban renewal, even though it is actually almost completely abandoned. Main aim of the research is the definition, from a methodological and technical point of view, of feasibility studies in order to submit the historical monumental heritage to a process of ‘energy efficiency’ and ‘energy production’, even recurring to the most suitable technologies supplied by renewable energies. In this paper, a preliminiary approach and general criteria for the building refurbishment, in relation to the architectural and historical commitments, are presented. [ABSTRACT FROM AUTHOR]

A great number of low carbon technologies have been developed in the last decades. The use of such technologies promises good indoor environment for the building's occupants, lower energy consumption and carbon emissions. However, there are uncertainties related to payback periods and usability constraints of low carbon technologies. In addition, past and current research has shown differences between the expected and the actual performance of buildings, both in terms of energy consumption and indoor comfort. For a better understanding of differences between expected and actual performance of buildings, it is necessary to investigate the energy consumption, the behaviour of the occupants and their interaction with new technologies, and the resulting indoor comfort. Monitoring building performance can help to reduce the uncertainties related to the building performance of buildings. This paper presents an overview and classification of data collection methods to monitor the energy consumption, thermal comfort of occupants and the operation of buildings in use. Data collection methods and techniques are categorised and linked to specific methods to evaluate building performance and recommendations are made to set up building monitoring research. By identifying the most effective methods to monitor buildings, this research aims at embedding performance monitoring in standard practice. [ABSTRACT FROM AUTHOR]

The European Union stresses the accent on the need of energy consumption and expenditure data related to housing stock (EP, 2010). Most of housing and living conditions databases of Member States investigate the housing status of a concerned region through a survey to be submitted to the sampled households. The assessment of energy performance then requires a simplified energy performance certification method, based on qualitative variables. In this paper the French Enquête Nationale Logements (ENL) is considered. A conversion algorithm is elaborated to refer each of the ENL housing units to a reference building and a reference HVAC system of the European Typology Approach for Building Stock Energy Assessment database (TABULA–EPISCOPE, 2013) for France. The ENL housing stock is better specified in its technical and energetic features through a typological data crossing. As a result, an energy label and an energy performance index expressed in [(kWh, ep)/(m 2 year)] are issued for every single ENL row. The calculation outcomes are assessed through a sensitivity analysis and compared to other national statistics; finally the distribution of energy labels is discussed. Many purposes of results exploitations are cited, concerning in particular the fuel poverty evaluation and the energy expenditure per household estimation. [ABSTRACT FROM AUTHOR]

Abstract: The paper presents an incremental development of the methodology for chilled water system design optimization. Initially, the system configuration parameters are varied with fixed design conditions to confirm the established best practice design criteria, followed by a comprehensive system design optimization. The implemented simulation-based optimization approach couples the Dymola/Modelica dynamic modeling and simulation program with GenOpt generic optimization program to find optimal system configuration. A dynamic system model is developed to vary and simulate different chilled water system configurations. Optimization of the chilled water system is achieved at both design and configuration level using five design variables. Two discrete variables are related to system configuration: number of chillers and number of cooling towers and three continuous variables are related to system design: building load demand, temperature difference across condenser, and cooling tower fan speed. The strategy of varying system design and configuration variables together for overall system optimization proved to be the most energy efficient. For a fixed building load demand, power consumption of the considered system can be reduced 17–43% by selecting an optimal system configuration. [Copyright &y& Elsevier]

Abstract: This is the first research paper on data center from Finland. The objectives of this study are to evaluate air management and energy performance of cooling system and investigate the possibilities of energy saving and reuse in the data center. Field measurements, particularly for long term''s IT and facility powers, were conducted. Different performance metrics for the cooling system and power consumption were examined and analysed. Key problem areas and energy saving opportunities were identified. The electrical end use breakdown was estimated. Results show that IT equipment intake conditions were within the recommended or allowable ranges from ASHRAE. The Power Usage Effectiveness (PUE) value for a typical year was about 1.33. Noticeable recirculation of hot air was not observed, but extreme bypass air was found. The air change rate was set much bigger than the recommended ASHRAE''s value. There was no heat recovery system. The air management and heat recovery issues therefore need to be addressed. Fan speeds (Computer Room Air-Conditioning Unit) should be reduced and the ventilation rate should be minimized. Further, a simulated heat recovery system was presented demonstrating that the data center could potentially provide yearly space and hot water heating for 30,916m2 non-domestic building. [Copyright &y& Elsevier]

Abstract: Energy use in the built environment represents a large part of total energy use in Sweden and is one important sector where energy conservation needs to be significantly improved in order to meet the national implementation of the European goals. One key question that needs to be investigated in relation to these goals is the performance and implementation of passive or low-energy houses. This paper presents results and an evaluation of a newly built house in an area with passive houses in Linköping, Sweden. Nine passive houses were built with the aim to be energy efficient, with an annual space heating demand of 21kWh/m2, and at the same time to have the same visual appearance as any other building in the surrounding area. This study evaluates the energy performance of a residential area with low-energy buildings based on Building Energy Simulation (BES) (IDA ICE 4), and measurements from the real object. Both annual and hourly validation is performed using room by room modeling and internal heat gains. A novel approach to internal heat gain modeling is presented using time-use data (TUD). The results show possible improvements in the design, the building envelope and in the heating control. [Copyright &y& Elsevier]

Abstract: This paper presents the results of a recent research effort to collect and analyze data pertaining to traditional bath buildings (“hammams”) in Egypt, Turkey, Morocco, Syria, and Algeria. Thereby, the energy performance of and the thermal comfort conditions in five such buildings were studied. Moreover, empirically calibrated building performance simulation models of a number of objects were generated in order to predict the consequences of alternative thermal retrofit measures. The results provide the opportunity for an objective assessment of the actual energy and indoor environmental performance of these buildings. [Copyright &y& Elsevier]

Abstract: According to the Energy Performance of Buildings Directive (EPBD) all new European buildings (residential, commercial, industrial, etc.) must since 2006 have an energy declaration based on the calculated energy performance of the building, including heating, ventilating, cooling and lighting systems. This energy declaration must refer to the primary energy or CO2 emissions. The European Organization for Standardization (CEN) has prepared a series of standards for energy performance calculations for buildings and systems. This paper presents related standards for heating systems. The relevant CEN-standards are presented and a sample calculation of energy performance is made for a small single family house, an office building and an industrial building in three different geographical locations: Stockholm, Brussels, and Venice. The additional heat losses from heating systems can be 10–20% of the building energy demand. The additional loss depends on the type of heat emitter, type of control, pump and boiler. [Copyright &y& Elsevier]

Abstract: The energy performance of buildings has become increasingly important in the general strive to reduce the overall energy use, which is manifested in the Energy Performance of Buildings Directive launched by the European Union. An important first step is of course to identify and address buildings that have an energy saving potential. In order to achieve this, robust methods for evaluation as well as reliable energy key figures are needed. For a large majority of multifamily buildings in Sweden the available data of the energy use originates from the property holder. Unfortunately, the data is often limited to the energy that the property holder is responsible for. Thus, information from the tenants about their household electricity use, indoor temperatures, number of residents, etc., is missing. In this paper an evaluation was conducted on monthly consumption data registered by the property holders for over 100 multifamily buildings/real estates in Sweden. The used approach, based on the energy signature method, was developed for evaluating the energy performance of multifamily buildings in terms of the overall heat loss coefficient, K tot. To compensate for the missing data, different assumed consumption profiles have been used. The results shows that although the obtained value of K tot for an individual building is rather sensitive to the assumed consumption profiles of household electricity, the sensitivity is reduced if the evaluation is made in relative and not absolute terms. Thus, the use of consumption profiles could be a successful way to circumvent the present lack of a detailed knowledge of a buildings total energy use. In addition, an evaluation in relative terms instead of absolute values is also more correct, since available data in almost all cases does not support the determination of the true value of K tot. The use of an average consumption profile instead of a detailed knowledge is of course not desirable, but for fairly large buildings such an approach could be successful. [Copyright &y& Elsevier]

Abstract: The methods used to assess the energy performance of buildings are static or dynamic. A paradigm shift is to estimate the energy consumption by using a probabilistic approach and a single concept for the whole range of operation of the building (heating, ventilation and cooling) and to decouple the thermal behavior of the building, the thermal comfort range and the climate data. These requirements can be achieved by using the free-running temperature to characterize the building behavior and the frequency distribution of the outdoor temperature to describe the climate. This paper demonstrates that the dynamic values can be used to estimate the energy load curve, that this curve may be applied to calculate the energy consumption and that the free-running temperature is an equivalent form of the heating/cooling curve. The main advantages of using the concept of free-running temperature are that: (1) the dynamic behavior may be described by steady-state concepts, (2) the whole range of building operation (heating, ventilation and cooling) is described by a single concept and (3) the thermal behavior of the building, the comfort and the climate are decoupled. The mathematical formalism uses matrix notation. [Copyright &y& Elsevier]

Abstract: This paper addresses the issue of energy performance of data centers by closely examining energy use of two data centers in commercial office buildings. The primary objective of the study is to examine an empirical energy use pattern of data centers under tropical climatic conditions, and give guidance for data centers’ design, operation and maintenance and retrofitting to achieve better energy performance. Actual energy use characteristics, design criteria, and energy and cost saving potentials were analyzed and compared between two data centers. Methodology of energy performance evaluation of data centers was discussed. The study concludes that data centers were high energy consuming areas in commercial office buildings—energy consumptions of approximately 3000kWh/(m2 year) and 2000kWh/(m2 year), respectively, were observed in the case studies. Power demands were often grossly over-provided in these facilities. This leaded to substantial increase in capital and running cost, which can be wasteful. Disparity in energy performance between case studies demonstrated the need for design guidelines and practical benchmarking. In one case study, approximately 56% (1.2GWh/year) of energy consumption could be conserved through efficient designs of base infrastructure and energy consuming systems, as compared to better practice. The predicted cost saving is more than US$ 80,000 per year. [Copyright &y& Elsevier]

• We selected three benchmarking methods to establish building energy benchmarking models based on a sample of 45 hotel buildings in China. • We compared the three benchmarking methods in terms of consistency, robustness and explanatory ability. • The energy efficiency performance obtained from the three methods were found to be inconsistent. • We came up with suggestions based on comparative analysis for policy-makers to develop building energy benchmarking programs. A reasonable building energy efficiency benchmarking program plays an important role in energy consumption control and supervision. Previous studies have focused on the process of establishing a single benchmarking method, but few have compared the performances and outcomes of different methods. To fill this gap, this paper selects three benchmarking methods—multiple linear regression (MLR) based on Energy Star, stochastic frontier analysis (SFA) and the descriptive statistics method (DSM) based on the national energy consumption standard in China—to develop benchmarking models. We demonstrate each method using data on the energy and building characteristics of 45 four- and five-star hotel buildings located in Chongqing, China. To compare the consistency, robustness and explanatory ability of the three methods, we first utilize the Spearman rank correlation analysis to test whether these methods have consistent energy efficiency ranks and then present Sankey diagrams to further reveal the interactions of the estimated energy efficiency grades obtained from the three methods. It is found that the results of DSM and SFA are most consistent, while MLR vs. SFA and MLR vs. DSM present significant differences in evaluating building energy performance. In addition, DSM is more robust for evaluating the ranks of sampled buildings, while SFA is more robust for evaluating energy efficiency grades. Furthermore, we discuss the explanatory ability of each method. In addition to the building characteristics, the design and operational characteristics of the HVAC system have great effects on building energy consumption. Finally, we present suggestions for policy-makers regarding the development and implementation of the building energy benchmarking program in Chongqing and for the management of buildings with different energy performances to further improve the energy efficiency. [ABSTRACT FROM AUTHOR]