Search

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

A significant focus of research and new technologies for reducing energy use in buildings is on operating the systems more efficiently during the times when the systems are active. However, there is a large potential for energy savings in determining the periods when the systems should or should not be active. This scheduling aspect of operation is often overlooked even though relatively simple solutions can unlock substantial energy savings. This paper describes a smart building start (SBS) algorithm that considers multiple zones in a building to determine individual schedules for room controllers as well as the central systems based on solving a simple optimization problem. Application of the SBS algorithm to multiple interconnected systems enables a staggered start-up that minimizes peak loads and also ensures comfort is within a target range with minimal system run time. The SBS algorithm extends the capability of traditional optimal start and is designed to be simple to deploy and robust. Simulation results as well as results from tests in a real building with a VAV system are presented. The presented algorithm is applicable to any type of building with a zonal or multi-zone HVAC system. To function, it needs to be able to change setpoints in rooms and monitor room temperatures, as well as, if desired, turn the central system on or off. [ABSTRACT FROM AUTHOR]

[Display omitted] • Two modules were analyzed during Antarctic summer at Spanish research station. • Measured transmittances and infiltrations were excessively high, resulting in high energy consumption for heating. • Indoor air conditions were poor in both modules, particularly the CO 2 concentration. • Extreme weather conditions accelerated the degradation of insulating materials and sealants. • Energy efficiency standards are urgently needed to improve the carbon footprint of Antarctic bases. In this paper, we present the energy characterization of two habitable modules at the Spanish station "Gabriel de Castilla", located on Deception Island, Antarctica. The analysis includes profiles of energy consumption for space heating and domestic hot water, as well as indoor air conditions, which were all recorded during one month of Antarctic summer. Additionally, the measurement of walls' transmittance and air infiltrations, together with thermography analysis, enabled evaluating the conservation state of the buildings' envelope. Upon analyzing all this data, it is evident that there is potential to enhance the design of future modules, improving the thermal comfort while significantly reducing the energy consumption. This will contribute to decrease the logistics and environmental impacts of these research stations, crucial considerations in human activity on the Antarctic continent. [ABSTRACT FROM AUTHOR]

• Automatic MiC envelopes and layout generation by a novel SSG-MOO method. • Multi-objective optimization formulation for passive MiC design. • A pilot MiC study in Hong Kong produced 5 selected Pareto optima out of 625. • Up to 0.42% energy savings and 9.71% spatial daylight autonomy improvement against the baseline. • A multi-level analysis of results and design strategies for practitioners. Modular-integrated Construction (MiC) is an emerging construction technique promoted in the building sector for high productivity and low waste emission in the construction phase; yet, the standardized modules also bring new challenges, such as balancing passive energy efficiency and spatial daylight autonomy, to the operational phase. This paper proposes a Symmetric Skeleton Grammar-based Multi-Objective Optimization (SSG-MOO) method to formulate parametric MiC envelopes and detailed layout, with the two objective functions being energy efficiency and interior daylight performance in the operational phase. Pareto optima of the SSG-MOO, computed by the Non-dominated Sorting Genetic Algorithm II, are generally verified and analyzed in three levels, i.e., MOO's solution space, SSG layout, and MiC design parameters. A case study of MiC residential building in Hong Kong demonstrated the SSG-MOO method through five new passive MiC designs (i.e., spatial reorganization of three architectural modules, and parameter tuning of the envelops and corridors), achieving up to 0.42% energy savings and 9.71% spatial daylight autonomy improvement compared to the baseline design. The contribution of this paper is two-fold, including a novel and sound SSG-MOO formulation for parametric MiC designs, and offering time-efficient and evidence-based design tactics for MiC designers and industrial practitioners to push boundaries of MiC. [ABSTRACT FROM AUTHOR]

[Display omitted] • The LCA methods and findings of 41 papers on air-conditioning systems are examined. • Retrieved studies presented discrepancies in the LCA goals and scope definition. • The global warming potential (GWP) was the most evaluated indicator across papers. • Grid-connected electrical heat pumps generally had a higher life cycle GWP. • Improvements related to AC energy sources and other life cycle aspects are proposed. Air conditioning (AC) has become the fastest-growing energy end-use in buildings worldwide, and its adoption is expected to increase further due to various socioeconomic factors and climate change. Despite this, the decarbonization of space cooling is progressing slowly; hence, the emissions burden at each stage should be examined in detail. Given this context, it is crucial to assess the environmental performance of AC systems by considering a comprehensive approach like the Life Cycle Assessment (LCA). While several studies have already targeted the LCA of AC systems, a clear overview of those studies' methodologies, assumptions, and results is still lacking. Therefore, this systematic review examined the methods and key findings of 41 peer-reviewed articles. Although the results revealed discrepancies among the goals and scope, impact assessment methods, and indicators, most articles predominantly focused on the global warming potential (GWP) impact, and its reported quantification was further analyzed. It was observed that grid-connected vapor-compression heat pumps/chillers (conventional systems) presented higher GWP impacts than other AC systems powered by renewables, which in contrast, exhibited higher impacts in some toxicity and resource depletion-related indicators. However, the share of GWP showed different distributions, as the pre-operation emissions of solar-powered AC systems (either PV or thermal) were higher than those of conventional systems, mainly driven by reduced energy consumption usage. This review concludes with some recommendations for each stage of the life cycle. Since the operation phase generally showed the highest impact, more efforts should be devoted to accelerating the transition to a 100% clean electricity power system at a national scale. In contrast, the need to power AC systems with on-site renewables should be carefully assessed based on the context. [ABSTRACT FROM AUTHOR]

K-12 schools are the largest energy consumers in the public sector, with their HVAC energy consumption representing the largest portion of their total energy use. While transitioning these schools to grid-interactive HVAC system operation through advanced controls offers significant financial and environmental benefits, and model predictive control (MPC) has been identified as a promising solution to achieve that, very few MPCs are affordable and have been deployed in K-12 schools. This situation raises concerns about the unclear real-world benefits of MPC technology among facility managers and industries. To address this gap, this paper presents a low-cost MPC solution that requires minimal control infrastructure costs and a unique field demonstration at a K-12 school, conducted for both cooling and heating seasons. This work adopted a previously developed MPC and extended it for use in the school application. The MPC aims to coordinate multiple packaged units to eliminate unnecessary peaks and shift cooling or heating loads in response to grid signals based on load conditions, while maintaining thermostat temperatures within school-defined bounds. Throughout the field tests, the MPC achieved a 24% reduction in peak demand during the cooling season and shifted cooling or heating loads by up to 16% in response to the school's utility tariff, considering load conditions, while also allowing end-users to override thermostat setpoints. The paper also discusses the limitations of this study and future research directions for better performance of the MPC at K-12 schools. • First MPC demonstration in K-12 school buildings for peak demand reduction and load shifting. • Experimentally demonstrated a scalable MPC for multiple RTUs without hardware retrofit. • Hierarchical MPC is improved in consideration of practical challenges such as user's override and poor data resolutions. • Achieved 24% peak demand reduction and showed 16% of load shifting potential. • Share lessons learned during the demonstration of practical challenges. [ABSTRACT FROM AUTHOR]

• HVAC system stock is heterogeneous and changes over time. • A HVAC stock modeling and an archetype building energy modeling were integrated. • Disregard of the heterogeneity and its change can cause error in energy modeling. • Energy reduction by technological innovation relies on the share of the HVAC stock. Urban building energy model (UBEM) is an important tool in coping with energy issues of building sector. This paper focuses on an issue that the stock of heating, ventilation, and air-conditioning (HVAC) systems has been oversimplified in UBEM without considering its heterogeneity. It has been observed that this oversimplification may incur a significant error in the result. To address this issue, this paper proposes a framework that integrates a logistic regression based HVAC system stock modeling method and the bottom-up type engineering modeling method using building archetypes considering HVAC system configurations. A case study with Japanese office building stock revealed that (1) the disregard of the heterogeneity resulted in an error of 15% in the annual primary energy consumption, (2) the historical change in the HVAC system stock could decrease the consumption up to 5%, and (3) its composition has a significant influence on the energy saving due to energy efficiency increase in heat source machines used in HVAC systems. The presented method would contribute not only to improving the reliability of UBEM but also to providing an analytical capability of considering energy efficiency technologies related to HVAC systems along with the alternation of technology selection in the building stock. [ABSTRACT FROM AUTHOR]

• Affordable and adaptable VIP based internal and external retrofitting solutions. • Implementation of VIP based integral retrofitting solutions in two tertiary buildings. • Space heating energy saving analysis before and after VIP based retrofit. • Envelope heat loss coefficient reduction analysis before and after retrofitting. Vacuum insulation panels (VIPs) represent a huge opportunity to achieve nearly zero energy buildings, especially in the retrofitting of existing buildings. VIPs can be applied in conjunction with façade cladding elements, considerably reducing the heat losses or gains from the building by means of very slim wall construction systems or retrofit solutions. However, the fact that VIPs cannot be cut on-site, can be easily damaged during their handling, installation and use and have an envelope that can cause thermal bridging in the junction between panels or when combined with other materials, has hindered their penetration in the construction market. This paper presents two innovative façade retrofitting solutions, a rear ventilated façade and a stud mounted internal solution, that have tackled all these issues and provide thermal transmittances of 0.28 and 0.14 W/m2 K in relatively slim insulation systems of 10 cm widths. Solutions have been installed on the entire façade of two existing buildings located in Bilbao (Spain) and Malmö (Sweden) subjected to an integral rehabilitation process, covering 2100 m2. Buildings energy use have been monitored before and after the renovation, showing energy cuts of around 35% from pre-intervention status. This paper presents the lessons learnt during the design and installation process of the vacuum insulation integrating solutions in the façade of two existing buildings and the thermal performance results achieved after their retrofitting. [ABSTRACT FROM AUTHOR]

• The paper has a focus on energy consumption habits and trends using statistical methods. • Occupants' behavior is monitored using smart metering system and awareness surveys. • The impact of a serious game on occupant's behavior is evaluated. The paper has a focus on energy consumption habits, trends and intervention strategies in residential buildings, mainly through the serious game approach with a combination of direct consumer feedback through smart metering. More than 150 homes in France and Spain have been involved in the research experiment and the consumption habits of approximately 50 homes were deeply analyzed. The applied methods, processes, results and findings of the monitoring data analysis are presented in the paper with two aims. First, consumption profiles and trends were determined for apartment homes with regard to heating, domestic hot water and electric consumption. Second, the impact of a serious game experiment was assessed comparing energy consumption, indoor air temperature and users' habits (based on questionnaires) before and after launching the experiment. [ABSTRACT FROM AUTHOR]

• Renewable energy assessment methods used in 12 GBRSs are analysed and compared. • Methods used in green neighbourhood rating system are also introduced. • Evaluation way, renewable energy types, building characteristics, etc. are analyzed. • The effects by using different methods in one building are analysed. • Suggestions are provided to improve the renewable energy assessment. Green buildings and neighborhoods can help mitigate impacts of buildings on the environment, society and economy. Many rating systems or tools have been developed worldwide to assess and certificate green buildings or green neighborhoods. Renewable energy plays an important role in achieving green buildings/neighborhoods or zero energy buildings/neighborhoods by reducing fuel consumption and pollution emissions. However, substantial differences exist in assessing or quantifying the renewable energy in green building/neighborhood rating systems. This paper therefore provides a comprehensive review on renewable energy assessment methods adopted in green building/neighborhood rating systems, which would be very helpful to understand and then improve the rating systems. These methods are analyzed and discussed regarding to the calculation way, involved renewable energy types, building characteristics and energy conversion. Then a case study is conducted to quantitatively illustrate the difference of typical renewable energy assessment. Suggestions are summarized to improve the assessment methods. This paper will help investors, users and policy makers understand the rating systems more thoroughly and promote the development of green buildings and green neighborhoods. [ABSTRACT FROM AUTHOR]

[Display omitted] • Identifying recent developments in thermal-driven dehumidification technologies. • Evaluating critical characteristics including dehumidification efficiency, energy consumption and cost. • Assessing the desiccant properties for thermal driven dehumidification technologies. • Directing future research to address environmental concerns via innovative sustainable humidity control mechanisms. As we navigate an era marked by significant environmental concerns and technological advancements, the search for energy-efficient and ecological friendly solutions is more critical than ever. One area of growing significance is the control of indoor humidity levels, which not only impacts human comfort and health but also the structural integrity and air quality within buildings. The challenge is to control these levels while lessening energy consumption and environmental impact. A feasible solution lies in the use of thermal-driven dehumidifiers, a promising technology that offers a sustainable approach to humidity control. Thermal-driven dehumidifiers have emerged as promising solutions for humidity control in various applications, owing to their energy-saving and eco-friendly features. Thus, the focus of this review paper is to explore the most recent advancements and enhancements in thermal-driven dehumidification technologies. This includes systems based on solid desiccant, liquid desiccant, and thermoelectricity. The study aims to fill the existing literature gaps, providing a thorough analysis of the current state of these technologies, their performance indicators, and their potential for future development. The study also explores the suitability of these technologies for different ambient conditions and humidity loads. It addresses critical characteristics such as dehumidification efficiency, cooling capacity, regeneration heat, and energy consumption. Each technology is thoroughly examined, including its suitability for various ambient conditions and humidity load scenarios. Specific real-world examples are examined to highlight these technologies' practical importance and possible influence in tackling humidity management concerns. [ABSTRACT FROM AUTHOR]

[Display omitted] • Frosting & defrosting characteristics of appliances are reviewed from 2000 to 2023. • Parameters affecting frost formation in 'no-frost' evaporators are surveyed. • Methods for improving frosting and defrosting performance are summarized. • Correlations of j and f factors for 'no-frost' evaporators are summarized. • Major findings and recommendations for future research are presented. Refrigerators and freezers are now common household devices, and they consume a considerable amount of energy each year. The deposition and accumulation of frost on the surface of the refrigerator evaporator is inevitable and always has a significant negative impact. The periodic defrosting is necessary for household refrigerators, which increases the energy consumption and the compartment temperature. This paper presents the key findings concerning the frosting and defrosting characteristics of refrigerators and freezers based on the existing literature in 2000 ∼ 2023. In the first part, the frosting research is summarized. Firstly, the parameters affecting the frost formation of the refrigerator evaporator are analyzed. Then, the structure of the 'no-frost' evaporator is introduced. Meanwhile, the heat transfer and pressure drop characteristics of the 'no-frost' evaporator are discussed. Two methods for improving 'no-frost' evaporator performance are also presented. The second part focuses on the defrosting research, including an analysis of defrosting energy consumption. Four methods to improve refrigerator defrosting performance are also summarized. Suggestions are made for future research initiatives and essential improvement measures. This review strives to serve as a valuable reference for the study of frosting and defrosting characteristics in household refrigerators and freezers. [ABSTRACT FROM AUTHOR]

• Climate change's impact on retrofitting was tested on Le Corbusier's apartment. • Climate change scenarios project up to 70% increase in summer overheating. • Adaptive natural ventilation can reduce warm discomfort of 50–60%. • Adaptive setpoints can reduce total energy consumption of 20–30%. • Adaptive strategies are particularly favourable in historic buildings. Historic buildings, often exempt from retrofits to preserve originality, require retrofitting due to potential future climate-related indoor issues. For Modern Architecture constructions, there is a need to find solutions that help address the discomfort and heat losses caused by the extensive use of glazing. By analysing Le Corbusier's studio-apartment this paper aims to inspect: (i) Solutions for energy, Indoor Environmental Quality, and preservation; (ii) Climate change impact on them; (iii) Possible adaptation strategies to cope with climate change. Spectrally selective glazing reduced summer overheating by 15%; high-performance glazing lowers cold discomfort (24%) and heating (22%) but increased warm discomfort; shadings maintained energy use and reduced summer discomfort by up to 44%; thermal insulation can reduce winter discomfort and halves energy use but raised summer discomfort by up to 41%. Tests on 2050–2100 climate change scenarios reveal up to 70% more warm discomfort hours. Adaptive strategies can help, with natural ventilation cutting warm discomfort by 50–60%, and adaptive setpoints reducing cooling demand by about 35%. Adaptive strategies can complement traditional retrofitting in addressing current and future climate conditions, especially in historic buildings that require minimal interventions to preserve their historical characteristics and enhance resilience. [ABSTRACT FROM AUTHOR]

This paper analyzes electricity use in buildings and explores key research questions related to assessing, rating, labeling, and benchmarking building energy use. The analysis reviews annual Energy Use Intensity (EUI) data from 3060 fully electric-powered buildings across six categories: residential, educational, offices, hospitals, hotels and restaurants, and wholesale and retail trade services. One-fifth of the analyzed buildings is derived from an energy dataset that offers a higher time-scale resolution, providing more detailed insights into energy usage patterns. The analysis employs various factors, including the seasonal variation factor (SVF), daily variation factor (DVF), monthly factor (M f), and hourly factor (H f), to gain a detailed understanding of actual energy usage at different time scales. The findings indicate that electricity use is less sensitive to seasonal variations than other energy carriers that provide heating and cooling. The paper provides hourly and monthly peak load percentages (PPL), which can indirectly assist in assessing hourly schedules for building energy performance simulations. The monthly energy use pattern varies between building categories, with high-energy months alternating between winter and summer. For non-residential buildings, high-energy hours correspond directly to the daytime, while for residential buildings, there is a shift towards the evening, and the daily amplitude is lower. Furthermore, the analysis of daily and monthly variability of heating energy carriers, even if non-electric, sheds light on the implications of electrification for these loads. • The study evaluates annual electricity data from 3060 fully electric-powered buildings. • Median EUIs are meaningful energy performance benchmarks by building category. • Residential and educational buildings exhibit EUIs of 90-120 kW h/m2. • Offices and hospitals demonstrate EUIs of 160-170 kW h/m2. • Monthly and hourly factors establish energy benchmarks for finer time resolution. [ABSTRACT FROM AUTHOR]

In a context of massive renovation of residential housing, stakeholders need decision-support tools based on knowledge of the current building stock and an accurate simulation of energy demand. For this purpose, we developed a val- idation/calibration method on a territorial/national scale in order to represent the real consumption of housing. This methodological approach provides (1) more reliable identification of energy-saving measures (changes in technology or behaviour) and (2) improved knowledge of the energy simulation tool and its post-calibration performance for optimisation issues. The main contribution of the calibration method described in this paper is the geographical scale concerned: all French residential housing has been modelled, simulated and calibrated with national data (geometries and attributes) on buildings. Furthermore, some occupants' socio-professional characteristics have been taken into account to reflect their actual energy behaviours. This is different from traditional approaches that focus only on a few buildings or archetypes. This paper also describes the application of this methodology on an Open Source simulation software in order to be easily verifiable and usable. This linear model will also be used to optimise renovation solutions at territorial scale in future work. All data used in this paper are Open Data and thus available to the scientific community. This method enabled more than 18 million buildings to be calibrated while reducing the Normalized Root Mean Square Error, between simulated and real energy annual consumption, from 52% to 24% for gas and from 24% to 15% for electricity. In addition, the user of the method is free to prioritise either the maximum error reduction or the number of calibration coefficients if a simpler model is desired. This paper also discusses the results obtained from this method for future improvement. [ABSTRACT FROM AUTHOR]

Building performance simulation is a powerful tool applied both in research and for building design including heating, ventilation, and air-conditioning systems. Several research studies have used this tool to investigate the potential of energy savings measures for swimming facilities. However, in these facilities the technical complexity is a considerable challenge in modelling since many complex phenomena occur in the various sub-systems. The building industry traditionally plans and design these complex buildings by heuristic rules of thumb, and these empirical design rules may lead to significant differences between real and predicted performance. Therefore, it's important to develop simplified models with acceptable accuracy for simulation-based design of swimming facilities. The scientific literature introduces different simplifications for the air handling unit modelling, but the impact of these simplifications is hardly analyzed. Therefore, the paper investigates the model complexity of the air handling unit in a Norwegian swimming facility by comparing a novel simplified model and a detailed model which serves as a digital replica of a real unit. The simplified decoupled model is found to have an acceptable accuracy for early-stage design, bearing in mind the overall uncertainty at this design stage. However, when carrying out a detailed investigation of a swimming facility, the detailed model should be applied, since this complex heuristic rule-based model, is taking into account phenomena like thermal-coupling effects between the swimming pool and the air handling unit and the control errors of the real internal controller. In conclusion, the paper derives useful guidelines for building performance simulation design of air handling unit, which is the main energy-intensive component in indoor swimming pool facilities. [ABSTRACT FROM AUTHOR]

• Overheating regulations and calculation methods in 26 European countries were compared. • Most of the existing calculation methods are outdated and do not fit climate-proof buildings. • France requires a mixed-mode operation of naturally ventilated households. • The UK developed a heatwave-based calculation approach. • Comfort-based, multi-zonal, and time-integrated calculation approaches are needed. With the ongoing significance of overheating calculations in the residential building sector, building codes such as the European Energy Performance of Building Directive (EPBD) are essential for harmonizing the indicators and performance thresholds. This paper investigates Europe's overheating calculation methods, indicators, and thresholds and evaluates their ability to address climate change and heat events. e study aims to identify the suitability of existing overheating calculation methods and propose recommendations for the EPBD. The study results provide a cross-sectional overview of twenty-six European countries. The most influential overheating calculation criteria are listed the best approaches are ranked. The paper provides a thorough comparative assessment and recommendations to align current calculations with climate-sensitive metrics. The results suggest a framework and key performance indicators that are comfort-based, multi-zonal, and time-integrated to calculate overheating and modify the EU's next building energy efficiency regulations. The results can help policymakers and building professionals to develop the next overheating calculation framework and approach for the future development of climate-proof and resilient residential buildings. [ABSTRACT FROM AUTHOR]

• The paper reviews 33 on-field residential feedback studies. Only occupied homes where feedback was provided and energy consumption was monitored were considered for the review. • Our study proposes a taxonomy for energy feedback based on different characteristics of feedback such as frequency, type, presentation style and mode of access. • Understand the different ways in which field studies were conducted and assess a few parameters to establish their relationship with energy savings achieved. Residential energy feedback is about providing personalized information on household energy use to consumers to encourage energy savings. This paper conducts a review of field-based studies that have evaluated the impact of energy feedback on residential energy consumption. The review includes studies in real occupied homes that have deployed feedback intervention(s) and measured energy savings. Our study builds a taxonomy for energy feedback based on different characteristics of feedback such as frequency, type, presentation style, and methods of access. Energy savings from similar feedback types were found to differ depending on how the study was conducted. The reviewed studies deployed a range of feedback information including energy units, energy cost and tailored information conducted across diverse audiences (ethnicity, geographical positioning), varying experimental types (longitudinal, Randomized Control Trial) and, size and duration of the studies. The duration of studies varied widely, ranging from one month to three years and demonstrated energy savings between 5% and 20%. While most studies achieved energy savings due to energy feedback, a few of them reported an increase in energy consumption which could be due to rebound effect. Most of the studies in literature adopted a longitudinal design where the current household energy consumption was compared with the past consumption to arrive at the savings. Others used Randomized Control Trial (RCT) design where energy consumption of intervention group was compared with control group. Most of the studies were conducted in developed countries with cold climates.. There are fewer studies done on large-scale residential energy feedback especially in emerging economies where there is a rise in air conditioning use. We propose future studies to also consider the human behavior and cultural influences while evaluating impact of energy feedback. Our recommendation is that the academic and policy community address this gap since energy feedback is likely to stimulate positive behavior change amongst householders leading to energy savings. [ABSTRACT FROM AUTHOR]

Highlights • Review the existing data sources of US commercial building energy usage. • Compare energy results from survey and simulation data for US commercial buildings. • Discuss the different applications of existing data sources for US commercial building energy. • Provide the cases of applications to guide the users to use the data sources. Abstract U.S. commercial buildings consumed around 18% of total primary energy in 2017 and a 2.23 EJ increase is expected by 2050. Energy-related data for commercial buildings can be used for various applications, including benchmarking, building component analysis, market potential analysis, and policy making. Although there are plenty of data sources for energy usage in commercial buildings, they have not been thoroughly reviewed and summarized. As a result, users do not have comprehensive guidelines about selections of right data sources for specific application needs. To fill this gap, this paper conducts a comprehensive review to summarize data sources for energy usage in U.S. commercial buildings and discuss their usages for different applications. First, the paper summarizes the survey and simulation data sources for energy usage. The data sources are compared in terms of their data collection methods, released information, and relevant features. Second, this paper analyzes the applications for different survey and simulation data sources. This review categorizes the applications of data sources into five categories, including energy performance benchmarks, energy use forecasts and predictions, energy use contributions of building components, supports of building energy policies, and urban-scale energy use analysis. Moreover, the paper introduces several cases to demonstrate the usages of these data sources. [ABSTRACT FROM AUTHOR]

Highlights • Development of a heat exchanger semi-empirical model accounting for frost formation. • Experimental validation of the HX model in partially frost regime. • Frost control strategies numerically implemented and compared. • Strategies lead to trade-offs between ventilation quality and energy consumption. Abstract This paper tackles the issue of frost formation in air-to-air heat recovery devices dedicated to single room ventilation by means of both numerical simulations and experimental approaches. In such heat exchangers, it is commonly known that the formation of a frost layer on the surface generates an additional thermal resistance and a flow section reduction, which leads to an overall degradation of the overall unit performance. This paper proposes a three-zone model, considering a dry, a wet and a frost zone, by determining the location of moving boundaries. Each zone is handled independently and the relative proportion of each zone is determined by means of the exchanger wall temperature. Besides this frost model, a defrost model is also envisaged. Once validated with experimental data collected on a U-flow-type heat exchanger, the developed model is used to implement different strategies to reduce or prevent frost formation in the exchanger. Based on three different criteria, these strategies are compared with each other to evaluate their benefits and drawbacks. The criteria give information on the energy efficiency of the ventilation, on the air renewal quality and on the pressure balance between the inside and the outside of the building. [ABSTRACT FROM AUTHOR]

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

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

Highlights • A pre and post renovation energy use analysis of almost 90,000 renovated dwellings. • The (p)rebound effects explain only partly disappointing energy renovation results. • Effectiveness of renovations are dependent on state of building prior to renovation. • Effectiveness of renovations are dependent on type of occupant. • Deep renovations often save less energy than expected but are the most effective. Abstract Energy renovations often result in lower energy savings than expected. Therefore, in this study we investigate nearly 90,000 renovated dwellings in the Netherlands with pre and post renovation data of actual and calculated energy consumption. One of the main additions of this paper, compared to previous studies on thermal renovation, is that it only takes dwellings into account with the same occupants before and after renovation, using a large longitudinal dataset. Overall this paper shows new insights towards the influence of the energy efficiency state of a building prior to energy renovation, the type of building, the number of occupants, the income level of the occupants and the occupancy time on the actual energy savings, the energy saving gap and on the probability of lower energy savings than expected. We also investigate if the influence is different per type of thermal renovation measure. Some of the findings are: it is impossible to conclude which single thermal renovation measure is the most effective because this is dependent on the energy efficiency of the building prior to the energy renovation, type of building, income level and occupancy; occupants with a high income save more energy than occupants with low income; dwellings with employed occupants benefit more from improved building installations than dwellings occupied by unemployed occupants; The prebound and rebound effects are only part of the explanations for lower than expected energy savings; Deep renovations result more often in lower than expected energy savings than single renovation measures but nevertheless they result in the highest average energy saving compared to other thermal renovation measures. The results could be used for more realistic expectations of the energy reduction achieved by thermal renovations, which is important for (amongst others) policy makers, clients and contractors who make use of energy performance contracting, home owners, landlords and (social) housing associations and as a starting point to improve the energy calculation method. [ABSTRACT FROM AUTHOR]

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]

Occupancy is one of the main factors affecting building energy consumption. The occupancy data, which refer to the occupancy number in this paper, has been widely used in the building simulation field. However, due to the stochastic nature of occupant behavior, it is hard to predict and measure how many people stay in a given building. The rapid development of mobile Internet technology provides an efficient and convenient option for occupancy detection. This paper proposes a concept of typical occupancy data (TOD), which are extracted from real-time occupancy data collected by mobile devices. K -means algorithm is employed to generate the TOD data through cluster analysis. An energy performance model of an office building is used as a case study to demonstrate the effectiveness of the TOD data. [ABSTRACT FROM AUTHOR]

Highlights • Proposed approach combines environmental and energy LCA. • The efficiency of external insulation analysed in terms of 2E efficiency criteria. • Methodological approach applied for building energy renovation project. • Several energy class renovation scenarios are examined. • Specific life cycle indicators and paybacks are calculated for all scenarios. Abstract The authors of the paper present a methodological approach for combining environmental and energy life cycle assessments of building energy refurbishments towards a nearly zero-energy building. The authors applied the proposed approach to a case study and examined several energy class renovation scenarios. Specific life cycle indicators and paybacks were calculated for all scenarios. The paper analyses the efficiency of insulation of the external envelope of a building (the external wall, floor on the ground and the roof) in terms of 2E efficiency criteria (energy – non-renewable primary energy consumption and ecology – CO 2 gas emissions), focusing on different thermal insulation materials. The life cycle assessment method was applied to analyse the environmental performance of building envelope insulation. Primary energy consumption and CO 2 gas emissions when insulating the envelopes to change their energy efficiency class from F to B and from B to A++ were determined. The paper also presents a graphical interpretation of primary energy savings and CO 2 gas emissions over a period of 60 years as well as identifies thermal insulation materials that are the most reasonable for building insulation in terms of energy and ecology. [ABSTRACT FROM AUTHOR]

Highlights • To design building's controls and setup strategies for personal behaviours, factors related to behaviours are studied. • Adaptive behaviours can create balance between indoor quality, comfort and energy use (ICE factors). • A design framework is proposed to facilitate environmental and personal adaptive behaviours. Abstract Adaptive behaviour has a significant impact on the quality of indoor environment, comfort, and energy consumption. Therefore, facilitating positive occupant behaviours will improve these three factors. The aim of this paper is to develop a design framework that can be used as part of the design process to facilitate adaptive behaviours. This paper reviews studies that focus on reasons behind adaptive behaviours, and implication of these adaptive behaviours on the built environment. This paper highlights that 'Context', 'Occupant', and 'Building' (COB) have the most influence on adaptive behaviours. However, in most cases their influence is not considered holistically. This study also illustrates that adaptive behaviour has implications for the quality of Indoor environment, level of Comfort, and Energy consumption (ICE). This paper introduces a framework consisting of three stages: (1) Evaluate the relation between COB and ICE factors with adaptive behaviours holistically; (2) Design building's controls for 'environmental behaviours', set-up strategies for 'personal behaviours', and find a balance between these two; 3) Monitor the performance of adaptive behaviours through Post Occupancy Evaluation (POE). [ABSTRACT FROM AUTHOR]

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

This paper provides a review of the literature concerning the impact of temporarily increased cooling setpoint temperature on occupant thermal comfort during demand response (DR) events in commercial, air-conditioned buildings. We address concerns regarding thermal comfort as it relates to zone temperature modifications that may be implemented as a part of DR measures. Increased zone setpoint temperatures during the cooling season can adversely affect building occupants physically and psychologically, and impair their perceived indoor air quality and self-estimated performance. In some cases, however, improved occupant thermal comfort due to warmer zone setpoint temperatures during DR events has also been reported. In order to reduce the negative impacts on building occupants, DR must be implemented with careful control and monitoring. There are significant differences in assumptions made about the way people would respond to a thermal environment between the static heat balance model and the adaptive approach, with the adaptive approach offering a wider range of acceptable indoor temperatures. Therefore, application of the adaptive approach could be one option to improve building energy performance by taking advantage of occupant adaptive behaviors during DR events. Depending on the building services and systems available, expectations of the occupants, and the control options they are given to adjust to their thermal environment, occupants could potentially adapt to temperatures higher than what are currently being practiced in buildings. However, an upper limit threshold for temperature modifications, even if temporary ones, must be recognized to minimize adverse impacts on building occupants prior to DR implementation. Therefore, the ideal goal would be to develop menthods that would identify an optimum balance between energy consumption and the building occupant thermal comfort before applying DR strategies. Prior review papers relevant to DR have generally concentrated on the energy saving potential alone, or where energy savings have been prioritized over occupant thermal comfort. This paper reviews implementation of DR from the perspective of occupant thermal comfort and presents a summary of the most relevant experimental and field studies regarding occupant thermal comfort during DR events in commercial, air-conditioned buildings. [ABSTRACT FROM AUTHOR]

This paper examines the extent to which different household socio-demographic and building characteristics contribute to high energy use in Social Housing. Using data from the sample created in the framework of the EU funded ICE-WISH project (social housing pilots in ten European countries, of around 25 dwellings each), an odds ratio analysis was performed to examine the effect of socio-demographic and building's structural determinants on high residential energy consumption. The analysis is performed separately for electricity use for lighting and appliances and for energy consumption for space and water heating. Results indicate that high electricity consumption in social housing is related to both socio-demographic characteristics of the occupants and characteristics of the buildings in which they live (OR = 5.6 for households with three occupants compared to single households and OR = 3 for households living in houses greater than 80 m 2 ), whereas high energy consumption for space and water heating is only related to building characteristics (OR = 1.15 for households with three occupants compared to single households and OR = 4.77 for households living in houses greater than 80 m 2 ). The outcomes of this paper call for future energy policy to intelligently incorporate traditional and behavior-based energy efficiency interventions for reducing residential energy consumption and CO2 emissions. [ABSTRACT FROM AUTHOR]

The growing awareness of climate change is constantly moving the attention of designers and policymakers from typical and current scenarios to future layouts. This new approach introduces a degree of uncertainty that should be accounted in the building design process. The multitude of possible scenarios suggests considering dynamic system that can adapt themselves to unpredicted operating conditions. The aim of this study is to test a new approach and a new flexibility metric analysing the behaviour of a high-performance dynamic internal curtain in current and future scenarios. The first part of the paper focuses on the optimization of the dynamic system in the current scenario; this preliminary analysis represents the traditional design approach and is considered the baseline for all the comparisons. Hence, defining a matrix of likely scenarios, this paper explores the behaviour of three different selected control strategies – always off (i.e., no curtain), fixed control, optimized control – in the different scenarios considering possible variations of i) climate, ii) urban context, iii) internal loads, and iv) building use. The main outcomes of the research are, on the one hand, the comparisons of the control strategies and the benefits of the dynamic system and, on the other hand, the definition of a new metric that can properly describe the flexibility of the building systems with reference to the future scenarios analysed. This metric is based on six classes – which describe the statistical distribution of the energy consumptions of all the scenarios simulated in the matrix – and an index called Energy Flexibility Index (EFI) that quantifies the flexibility of the technology considered. The case study analysed highlights how implementing a dynamic shading system, considering the same building use, can increase the EFI of nearly 21% for non-optimized control strategy and up to 23% when optimized. While changing the building use in residential reduces these values respectively, to 6% and 7%. [ABSTRACT FROM AUTHOR]

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

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

Traditional air-conditioning systems are energy intensive and contribute to higher operational costs especially in summer. This paper examines and compares the performance of two cooling systems in a room: one with a cooling tower connected thermally activated building system (TABS) combined with a fan coil unit (FCU), and the other with a conventional inverter split air-conditioner (AC). Natural ventilation adversely affected indoor air temperatures in TABS room while integrating FCU operation reduced the temperature by 5 °C and AC provided the most comfortable temperature. Thermal comfort survey of three occupants showed significant inconsistencies with Fanger model particularly for TABS with FCU and TABS without ventilation cases, as occupants felt comfortable indicating the positive effect of only sensible cooling. Energy consumption studies show that TABS in closed condition and with natural ventilation as the most energy efficient with AC being least efficient of the four systems. In terms of overall comfort and energy consumption for continuous operation throughout the day, TABS integrated with FCU was deemed the best option. [ABSTRACT FROM AUTHOR]

• The energy consumption can be effectively predicted by the prediction model. • Spearman correlation coefficient is used to screen input parameters of predicted model. • The prediction model with optimal performance requires only three input variables. • The prediction model has better results by using learning rate of 0.02 in training. • The energy consumption at a certain indoor temperature setpoint can be predicted. With increasing energy consumption, how to achieve the energy-saving operation of air-conditioning systems is crucial for improving the energy efficiency of buildings. The accurate and reliable energy consumption prediction of air-conditioning systems can be useful for optimizing the energy supply and equipment operation strategies. However, most existing studies focus on the prediction of the long-term energy consumption of air-conditioning systems, which usually exceeds the individual control time steps of the air-conditioning system. If the energy consumption of air-conditioning systems in the next control step can be predicted, then the least energy-consuming operating strategy can be selected at the beginning of each control step by relying on the predicted energy consumption, thereby achieving greater energy conservation. This paper proposes a real-time energy consumption prediction model for air-conditioning systems based on a long short-term memory neural network. The correlation between the energy consumption of air-conditioning system and input variables can be obtained by calculating the Spearman correlation coefficient. The predicted model results show that the normalized root mean square error of the prediction model is 0.0429 when the indoor air temperature, condenser inlet temperature, and historical energy consumption are set as inputs to predict the energy consumption of the air-conditioning system for the next 15 min. Meanwhile, the energy consumption at a certain indoor temperature setpoint can be predicted by the prediction model to aid in selecting a more appropriate indoor temperature setpoint, which can reduce energy consumption by optimizing the operation strategy of the air-conditioning system at each control step. [ABSTRACT FROM AUTHOR]

• An optimization algorithm is developed for determining optimal flexible workplaces. • The thermal comfort models in the objective function are learned from personal data. • The optimization allows a customized trade-off between thermal comfort and energy consumption. • The algorithm is verified using both collected data and the ASHRAE database. Due to distinct preferences across individuals, a large proportion of people are not satisfied with the thermal environments of their workplaces. Although recent studies have investigated flexible workplaces to meet the different preferences of individuals, the feasibility of adopting them to real-world environments is limited by the room capacity and potential for extra energy consumption. To address the knowledge gaps, this paper proposes a framework to jointly optimize thermal comfort and energy consumption of buildings through flexible workplaces by considering personal thermal preferences. A joint optimization algorithm that integrates building energy and personal thermal comfort models is developed based on the concept of the Large Neighborhood Search (LNS) algorithm. Analytical energy prediction models are obtained through Nonlinear Polynomial Regression (NPR) and personal thermal comfort models are established using Support Vector Machine Models (SVM). To verify the algorithm, a case study considering two scenarios (with and without existing personal thermal comfort data) is presented. The results indicate the proposed optimization algorithm can significantly improve the thermal comfort of the occupants while saving 22% and 14 % of energy consumption in the two scenarios, respectively. The proposed optimization method is valuable for building managers while adopting the concept of flexible workplaces. [ABSTRACT FROM AUTHOR]

With rising energy prices, it is becoming increasingly attractive for households to form an energy community (EC) and become an active member of the energy system. Therefore, the choice of the right sharing coefficient, which defines how the produced energy is shared, is important for the expected profits. The aim of this paper is to analyse and compare two existing sharing coefficients with two new sharing coefficients. Therefore, we define two EC setups, one with only residential members and one with residential and commercial members, and investigate the impact of the sharing coefficients by using a data driven simulation model. For the analysis, we use a Monte Carlo approach in combination with load profiles of EC members simulated via time series models to account for random variation in electricity demand. The applied methodology gives additional insights on the profitability and the distribution of savings. The analysis shows that sharing coefficients that benefit small consumers are essential to incentivise private members to form an EC with commercial members. It is shown that when such an EC is formed, higher savings, a higher degree of self-sufficiency and a more efficient use of the produced electricity can be achieved. [ABSTRACT FROM AUTHOR]

• Energy Communities analysis and review in Europe and, more specifically, in Spain. • Promoting energy poverty reduction and cooperation through Energy Communities. • Real case study focused on reducing energy poverty in the city of Getafe (Spain). • Selection of public buildings to implement energy community in two neighborhoods. • Significant electricity bill reductions for energy poverty households. Advancements in renewable energy technologies, a growing awareness of the need for sustainable energy solutions, and the emergence of new business models in the energy sector, have contributed to the growth of Energy Communities. Public entities can find in energy communities today an opportunity to tackle energy poverty, to increase the cooperation among citizens and to empower them to be a more active player within the energy sector. This paper analyzes energy communities in Europe and focuses specifically on Spain; considering the three beneficial aspects previously mentioned. It aims to obtain ground truth about the applications of these new citizens' arrangements. A citizen-led initiative at the city of Getafe (Madrid, Spain) is included and discussed in detail. This case study focused on reducing energy poverty of its participants. An energy community was designed and implemented as a collective PV solar self-consumption infrastructure. The roofs of various public buildings in the two case study neighborhoods were selected for locating the PV installations. Real metered data were used to evaluate the solution. A public building was selected for the energy community, considering generation on roof and dwellings proximity. The results provided that out of the 77% PV generations could be used to contribute to the demand of 100 residences; while the resulting 23% would provide approximately 60% of the energy demand of the public building. The setting up of the Energy Community not only had the technical part but also included workshops seminars and information sessions, to ensure that people prone to benefit and maximize its impact. [ABSTRACT FROM AUTHOR]

• A new spray cooling system is proposed based on PV/T and heat recovery in sow houses. • A simulation model is developed to dimension the new system. • The maximum error is less than 7.2% for the key equipment models in the new system. • The optimal operating ranges of new system are determined in five climate regions. • The operating control suggestions of new system are obtained in five climate regions. In this paper, a new spray cooling system (NSCS) is proposed based on PV/T and heat recovery in sow houses. It contributes to improving system applicability in high-humidity areas and reducing system energy consumption due to solar dehumidification and heat recovery. Meanwhile, the simulation model of NSCS is established and the reliability is verified for the models of its key equipment. The results show that the maximum error is less than 7.2% for the models. The optimal control parameter ranges are further determined for NSCS in five climate regions in China through simulation. The results show that in hot-summer and warm-winter (HSWW) region or hot-summer and cold-winter (HSCW) region, the optimal operating ranges are 40–45 kW and 7245–9245 kg/h for spray power and mass flow rate of circulating water, respectively. However, they are 25–30 kW and 13245–15245 kg/h in other three climate regions, respectively. Finally, the annual performance parameters are compared for NSCS in five typical cities. The regional applicability and operating control suggestions are further obtained for NSCS in five climate regions. The results show that the heat recovery coefficient and energy efficiency ratio are the maximum when NSCS is operated in HSWW and HSCW regions. In high-temperature and arid regions, removing desiccant wheel from NSCS may be a good method to reduce system investment and energy consumption. Meanwhile, the surplus electric and thermal energy can be used for regional energy utilization in NSCS. The above conclusions can determine the regional applicability of NSCS and guide its operating control in different climate regions. [ABSTRACT FROM AUTHOR]

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

[Display omitted] • An architect-friendly rapid evaluation for the adaptive facades (AFs) is presented. • The method eliminates uncertainty in AFs selection during the early design stage. • Optimal hourly values are obtained via co-simulation with EnergyPlus and Python. • AFs strategy is characterized by climate and optimal values using a white-box model. • U-value strategy reduces consumption by up to 6.6%, SHGC&τ v strategy by 17.0%. Adaptive façades (AFs) are technologies with great potential to reduce energy consumption by changing their properties to adapt to variable climatic conditions. This paper proposes an architect-friendly computational approach for the exploration of strategies for the selection of the thermal parameters of AFs based on co-simulation and white-box models in the early design stage. In the case study, the proposed approach is applied to obtain strategies with variable U -values and variable SHGC& τ v values for high-rise office buildings in seven cities. The energy consumption analysis of five scenarios is carried out to investigate the energy-saving potential of the AFs and to propose design strategies for transparent façades, and the accuracy of the approach is verified. It is concluded that the highest match of the variable U- value strategy with the optimal hourly U- values is 85.3%, while that between the variable SHGC& τ v strategy and the optimal hourly SHGC& τ v values is only 71.0%. Regarding the energy-saving potential, the highest energy-saving rate is 6.6% for the variable U- value strategy. However, for the variable SHGC& τ v strategy, the highest energy-saving rate is greater than 10.8% in seven cities. The difference between the energy-saving rates of the proposed strategy and the optimal hourly strategy is less than 0.4%, and it is 0.8% for the AFs with variable U- values and variable SHGC& τ v values, respectively. This architect-friendly approach represents a widely used design strategy for AFs that can directly provide recommended thermal parameters based on climatic conditions, and is an effective way to demonstrate the potential application of AFs in the early design stage. [ABSTRACT FROM AUTHOR]

The objective of this paper is to optimize the passive design of newly-built residential buildings in hot summer and cold winter region of China for improving indoor thermal comfort while reducing building energy demand. In this respect, this paper investigates the performance of a representative apartment building in the city of Shanghai and evaluates the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multi-objective optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time Ratio (CTR) is defined based on the modification of Szokolay’s theory in terms of bioclimatic analysis, and the impacts of passive design variables on the indoor thermal comfort and building energy demand in terms of different directions are comprehensively investigated. Results of the multi-objective optimization indicate that the residential buildings of Shanghai have a great potential in comfort-improvement and energy-saving. A series of novel optimal passive design tactics for residential buildings in Shanghai are derived accordingly which could be easily understood and conveniently carried out by the architects in practice. [ABSTRACT FROM AUTHOR]

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

Buildings are responsible for about 92% of the total energy end-use in Hong Kong, of which above 70% is from the commercial sector. Most of the buildings in Hong Kong are high-rise, and approximately 15% of the total building stock is commercial buildings. Despite the considerable improvement in the understanding of the life cycle energy use of office buildings, there is still a lack of research into the life cycle energy demand of high-rise office buildings. Such knowledge is however essential for facilitating building energy conservation in the high-rise urban environment. The aim of this paper is to investigate the life cycle energy use of high-rise office buildings. The research was carried out through a critical literature review and case studies of ten real-life high-rise office buildings in Hong Kong. Results show that the life cycle energy consumption is 51.78–73.64 GJ/m 2 over the 50-year study period. Building operation consumes 78–89% and the rest (i.e. 11–22%) is taken by the embodied energy. Despite the distinction in terms of the amount of embodied energy between high-rise buildings and low-rise counterparts, no clear correlation is found between building height and embodied energy intensity. Moreover, energy use for material manufacturing and transport should be prioritised in reducing the embodied energy, of which the transport energy needs to be taken into extra consideration for the case of Hong Kong. The findings should inform construction industry participants of the significant potential in reducing the embodied energy of high-rise office buildings. The paper profiles the life cycle energy use of high-rise office buildings and should be important for the policy formulation towards the holistic energy conservation in high-rise buildings over their lifespans. [ABSTRACT FROM AUTHOR]

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

This paper describes a method for residential water use modeling predicated on metered energy data. Actual measured hot water volumes for major indoor consumption are used to verify and adjust the outputs in gallons of hot water consumption based on climate variables, water heater technical features, and set-point and intake temperatures. Three independent datasets for residential energy (RECS 2009), water heater efficiency (Air-conditioning, Heating and Refrigeration Institute-AHRI), and end-use domestic water (Residential End Uses of Water, Version 2-REU II) are applied to identify specific demographic, built environment and geographic factors that relate patterns of energy demand to water consumption. The proposed model acts within the broader Integrated Urban Metabolism Analysis Tool (IUMAT), a system-based analytical framework for evaluating the environmental performance of the built environment. The method described in this paper offers an alternative approach to residential water consumption modeling by implementing volume of hot water consumption as a proxy for indoor water use. It provides utilities with the potential to parse and prioritize energy and water conservation measures. [ABSTRACT FROM AUTHOR]

In order to improve the energy efficiency of buildings, thermal insulation plays a pivotal role, however increasing external wall thermal insulation without also addressing construction details can lead to increased thermal bridging and mould growth. Detailed knowledge of a buildings thermal envelope is paramount to correctly analysing existing problems that promote cold bridging and low surface temperatures. No detailed database exists for housing in Ireland which describes the geometrical configuration of the existing stock. This paper presents findings from an investigation into the prediction of heating energy consumption performance for external envelope retrofit measures when adopting default standardised coefficients for thermal bridging as opposed to simulated values based on accurate geometrical information. Using a remote extraction methodology to obtain geometrical information on house typologies, this paper presents a study that produced a detailed building component database premised on stock aggregation theory using Cork City’s local authority housing as a case study. Three construction types; block on flat, cavity and composite cavity are identified with representative construction details for housing typologies modelled in Psi-Therm 2d enterprise. Linear thermal transmittance and minimum surface temperatures are evaluated and an energy efficient external retrofit for each construction detail is proposed. Thermal characteristics for each house archetype are developed using information extracted from 1551 asset rating surveys. Three case study terraced house typologies are then modelled using Ireland’s national asset rating software to demonstrate the importance of obtaining more accurate information regarding the building stock. The results highlighted up to 21.5% variation in energy performance when replacing a default thermal bridging coefficient for calculated values. [ABSTRACT FROM AUTHOR]

Simulation-based building retrofit analysis tools and electricity grid expansion planning tools are not readily compatible. Their integration is required for the combined study of building retrofit measures and electrified heating technologies using low-carbon electricity generation. The direct coupling of these modelling frameworks requires the explicit mathematical representation of Energy Conservation Measures (ECMs) in building-to-grid energy system models. The current paper introduces an automated calibration methodology which describes retrofitted buildings as parametric functions of ECMs. The buildings are represented using a lumped parameter modelling framework. A baseline model, representative of the building prior to retrofit, and the retrofit functions are calibrated using Particle Swarm Optimization. Synthetic temperature and heating load time-series data were generated using an EnergyPlus semi-detached house archetype model. The model is representative of this residential building category in Ireland. It is shown that the proposed methodology calibrates retrofitted building models to an acceptable level of accuracy ( MAE below 0.5 °C). The methodologies introduced in the current paper are capable of generating lumped parameter building models with similar dynamics for different ECMs for any archetype building energy model. The identified building retrofit models have the potential to be integrated with electricity grid models in a computationally-efficient manner. [ABSTRACT FROM AUTHOR]

Improved ventilation in an urban residential neighborhood is a determinant for better energy efficiency and air quality of the neighborhood. This is particularly important for the real estimates recently developed in many cities in China, as these neighborhoods are built with high density. In this paper, we consider in an idealized neighborhood with two categories of packaging building densities ( λ p ) of 0.25 and 0.44, which respectively represent medium and compact urban development. For each packaging density, the frontal area density of arrays is varied from 0.125 to 0.5 through adding building blocks and reducing building size simultaneously. Computational fluid dynamics simulations are carried out to predict the wind flow through the building arrays by the use of renormalization group (RNG) k - ε turbulence model. Our predictions are validated by comparing with experimental data. Numerical results reveal that ventilation rate could be greatly enhanced when a low level of packaging building density is maintained. The momentum exchange rate at the canopy roof level is effectively strengthened when the frontal area density decreases, together with a reduction of ventilation in the urban canopy layer (UCL). Additionally, a linear relationship is found between the UCL ventilation rate and the momentum exchange rate at the urban canopy roof level. For a constant packaging density, reducing frontal area density improves the city block ventilation by enhancing the air exchange rate at the roof level rather than increasing horizontal drag. This paper also illustrates a practical strategy in optimum neighborhood building layout design to minimize the pollutant level. [ABSTRACT FROM AUTHOR]

In times of great transition of the European construction sector to energy efficient and nearly zero energy buildings (nZEB), a market observation containing qualitative and quantitative indications should help to fill out some of the current gaps concerning the EU 2020 carbon targets. Next to the economic challenges, there are equally important factors that hinder renovating the existing residential building stock and adding newly constructed high performance buildings. Under these circumstances this paper summarises the findings of a cross-comparative study of the societal and technical barriers of nZEB implementation in 7 Southern European countries. The study analyses the present situation and provides an overview on future prospects for nZEB in Southern Europe. The result presents an overview of challenges and provides recommendations based on available empirical evidence to further lower those barriers in the European construction sector. The paper finds that the most Southern European countries are poorly prepared for nZEB implementation and especially to the challenge/opportunity of retrofitting existing buildings. Creating a common approach to further develop nZEB targets, concepts and definitions in synergy with the climatic, societal and technical state of progress in Southern Europe is essential. The paper provides recommendations for actions to shift the identified gaps into opportunities for future development of climate adaptive high performance buildings. [ABSTRACT FROM AUTHOR]