Green roofs and cool roofs are commonly used to improve indoor thermal environment, reduce air-conditioning load and mitigate the Urban Heat Island (UHI) effect. This study aimed to quantify the ...differences in thermal and energy performance between the two different roof types under the climate of Shanghai. Firstly, field experiment was conducted in the Shanghai area. Thermal performance of green roof, cool roof and common roof in summer and winter were measured. Results showed that, compared to common roof, the cool roof had an average cooling effect of 3.3 °C on the outer roof deck surface in summer, while the green roof only had a cooling effect of 2.9 °C. In winter, the green roof provided good insulation, and could improve outer surface temperature of the roof deck by an average of 3.3 °C compared to the cool roof. A hygrothermal transfer model for green roof was coupled with a dynamic building thermal performance simulation software (THERB) and validated using measured data. The coupled model was used to predict the effect of both roof types on energy performance of a public building. Simulation results showed that green roof could reduce the cooling and heating loads of the top floor by 3.6% and 6.2%, respectively. The cool roof could reduce cooling load by 3.6% and increase heating load by 10.4%. Finally, a parametric analysis was implemented. The functional mechanism of the main parameters of green and cool roof as well as their impacts on thermal and energy performance of public buildings were analyzed in detail. Conclusions drawn from this paper could provide guidance for the design optimization and application of green roof and cool roof in Shanghai area.
•Thermal performance of green roof and cool roof was monitored in Shanghai area.•A green roof heat transfer model was coupled with BES model (THERB) and validated.•Thermal and Energy effect of green and cool roof on public building was predicted.•Parametric analysis on thermal and energy performance of green roof was conducted.•Parametric analysis on thermal and energy performance of cool roof was conducted.
•A multi-objective search to minimise the building total energy need was performed.•Number, position, shape and type of windows and the thickness of walls were varied.•The analyses were performed for ...different climates and urban contexts.•A post-Pareto analysis was performed through a box plot elaboration.•A small area was found for non-south facing windows in all locations.
The majority of decisions in the building design process are taken in the early design stage. This delicate phase presents the greatest opportunity to obtain high performance buildings, but pertinent performance information is needed for designers to be able to deal with multidisciplinary and contrasting objectives. In the present work, an integrative approach for the early stages of building design is proposed to obtain detailed information on energy efficient envelope configurations. By means of genetic algorithms, a multi-objective search was performed with the aim of minimising the energy need for heating, cooling and lighting of a case study. The investigation was carried out for an open space office building by varying number, position, shape and type of windows and the thickness of the masonry walls. The search was performed through an implementation of the NSGA-II algorithm, which was made capable of exchanging information with the EnergyPlus building energy simulation tool. The analyses were conducted both in absence and in presence of an urban context in the climates of Palermo, Torino, Frankfurt and Oslo. In addition, a preliminary analysis on the Pareto front solutions was performed to investigate the statistical variation of the values assumed by the input variables in all the non-dominated solutions. For the analysed case study, results highlighted a small overall Window-to-Wall Ratio (WWR) of the building in all locations. Pareto front solutions were characterised by low WWR values especially in east, west and north exposed façades. The area of the south facing windows was higher compared to the other orientations and characterised by a higher variability.
•A BIM-supported energy performance analysis for green building design is proposed.•This systematic analytical framework integrates explainable machine learning and multi-objective optimization.•It ...can serve as a data-driven decision tool to guide green building development even under uncertainty.•The top important features that greatly affect the building energy performance can be quantitatively identified.•Building energy performance can be improved by 13.43% using the obtained optimal strategy.
Supported by the combination of the advanced BIM technique with intelligent algorithms, this paper develops a systematic framework using explainable machine learning and multi-objective optimization to realize the automatic prediction and optimization of building energy performance towards the sustainable development goal. There are three critical parts incorporated, including the DesignBuilder simulation, BO-LGBM (Bayesian optimization-LightGBM) and an explainable method SHAP (SHapley Additive explanation)-based prediction and explanation of building energy performance, and AGE-MOEA algorithm-based multi-objective optimization (MOO) under sources of uncertainty. It has been verified in a case study for green building design. Results show that: (1) The predictive BO-LGBM model can make a highly precise prediction in agreement with the simulation data, reaching up the R2 larger than 93.4% and MAPE smaller than 2.13%. From the SHAP calculation, features related to the HAVC (Heating Ventilation and Air Conditioning) system tend to contribute more to affecting the prediction results. (2) The AGE-MOEA-based optimization can identify a set of Pareto optimal solutions in simultaneously minimizing the building energy consumption, CO2 emission, and indoor thermal discomfort degree, arriving at the highest optimization rate of 13.43% under proper adjustment of certain features. (3) In the MOO task, the consideration of model and data uncertainty by prediction intervals and Monte-Carlo simulation can further increase the optimization rate by around 4.0% than the deterministic scenario, resulting in more desired strategies in optimizing the green building performance. In short, this paper enriches the area of green building development. For one thing, it raises the transparency and interpretability of machine learning to make the prediction more convincing. For another, it efficiently determines the passive and active design solutions along with the detailed profile of influential factors for green building design.
Since the Energy Policy Act of 1992, federal facilities have increasingly used performance contracting to finance energy and water efficiency measures. Utility Energy Performance Contracts (UESCs) ...have received less attention despite having similar goals and processes as Energy Savings Performance Contracts (ESPCs). This paper provides a comparison between the two performance contracting models and highlights the tradeoffs that should be considered. Higher costs observed in ESPCs are driven by higher overhead and the costs of savings guarantees. These cost drivers cascade into longer financing terms and higher interest rates. These results suggest that federal agencies should explore UESCs as a potentially more cost-effective way to achieve energy savings improvements.
•A daylighting model and an energy simulation model of the vacuum PV glazing were developed.•The applicability and limitation of the vacuum PV glazing in different climates were investigated.•The ...vacuum PV glazing improves the energy performance of typical PV glazing.•The vacuum PV glazing can balance the daylighting availability and visual comfort.•The reversed and the reversible vacuum PV glazing can enhance the potential of the application.
Amorphous silicon-based semi-transparent photovoltaic windows can produce renewable electricity and offer a certain amount of natural daylight for occupants. However, it has a deficiency as the absorbed solar energy would be partially transferred into additional cooling demand in summer. In this respect, a novel semi-transparent photovoltaic vacuum glazing is proposed to improve energy performance. The selection of appropriate glazing of an energy-efficient building should take into consideration the specific climate conditions. The daylighting behaviour of the glazing will also affect the daylighting performance as well as the lighting consumption. In this paper, the thermal performance, daylighting performance and overall energy performance of the proposed vacuum PV glazing in different climate regions have been investigated. A daylighting model was conducted by DAYSIM to evaluate the annual daylighting performance. It was found that the vacuum PV glazing can balance daylighting availability and visual comfort by providing sufficient daylight in the anterior half of the room and reducing daylight glare to the minimum level. The energy simulation by EnergyPlus demonstrated that the vacuum PV glazing has the energy-saving potential up to 43.4%, 66.0%, 48.8%, and 35.0% in Harbin, Beijing, Wuhan and Hong Kong, respectively. However, the applications of the vacuum glazing lead to additional cooling consumption in the moderate climate zone, such as Kunming. The results advanced the understanding on the applicability and limitation of the vacuum PV glazing in different climate backgrounds. Furthermore, the reversed and the reversible vacuum PV glazing were proposed to enhance the adaptability. The results suggest that the reversible vacuum PV glazing can act energy response in a more efficient way and fully utilize the energy-saving potential of the integration of the PV glazing and the vacuum glazing.
The most ambitious challenge for designers is an effective shading system that is able to keep the balance between the daylight harvesting and view out maximization while minimizing discomfort risks ...and building's energy load. In the literature, several definitions exist for an adaptive façade and many terminologies were introduced and used interchangeably. Therefore, this paper aims to distinguish the existing adaptive system typologies based on their key characteristics. In addition, a review based on a systematic search is conducted to outline possible design approaches towards non-conventional adaptive facades (AFs) through simulations at early stage of design. As the main research outcome, most of the studies evaluated indoor daylighting level and discomfort glare through parametric tools, while none of them proposed a specific control strategy to predict non-conventional adaptive facades' performance. These observations emphasize existing research gaps in this field that can affect the applicability of such facades in real practices.
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•Ten adaptive typologies with their specific characteristics were identified from the literature.•Three design approaches towards non-conventional adaptive facades were explored through a critical analysis.•None of the studies investigated view to outdoor or thermal comfort in details.•None of the studies proposed a control strategy to verify the performance of non-conventional adaptive façades.•Algorithmic and parametric tools such as Grasshopper was the most used simulation interface to develop such facades.
Increasing the energy efficiency of the built environment has become a priority worldwide and especially in Europe. Because of the relatively low turnover rate of the existing built environment, ...energy efficiency retrofitting appears to be a fundamental step in reducing its energy consumption. Last experiences have shown that there is a vast energy efficiency potential lying in the building stock, and it is mainly untapped. One of the reasons is a lack of robust methodologies able to evaluate the effect of applied energy efficiency measures and inform about the expected impact of potential retrofitting strategies. Nowadays, dynamic measured data coming from automated metering infrastructure provides valuable information to evaluate the effect of energy conservation strategies. For this reason, energy performance modeling and assessment methods based on this data are starting to play a major role. In this paper, several methodologies for the measurement and verification of energy savings, and for the prediction and recommendation of energy retrofitting strategies, are analysed in detail. Practitioners looking at different options for these two processes, will find in this review a thorough and detailed overview of the different methods that can be used. Guidance is also provided to determine which method could work best depending on the specific case under analysis. The reviewed approaches include statistical learning models, machine learning models, Bayesian methods, deterministic approaches, and hybrid techniques that combine deterministic and data-driven modeling. Existing research gaps are identified and prospects for future investigation are presented within the main conclusions of this research work.
•Novel techniques to estimate energy efficiency savings in buildings were reviewed.•Techniques to plan energy retrofitting strategies in buildings were reviewed.•The focus is on data-driven methods (statistical, machine learning, Bayesian).•Strengths and weaknesses of every method are analysed.•Research gaps and prospects for future investigation are presented.
•This study reviews the state-of-the-art in “energy” as well as “building”.•Building’s dynamic energy performance should be managed in the built environments.•This study summarizes recent progress in ...the building’s dynamic energy performance.•The major phases can be categorized into monitoring, diagnosing, and retrofitting.•This study proposes the specific future development directions and challenges by phase.
According to a press release, the building sector accounts for about 40% of the global primary energy consumption. Energy savings can be achieved in the building sector by improving the building’s dynamic energy performance in terms of sustainable construction management in the urban-based built environments (referred to as an “Urban Organism”). This study implements the concept of “dynamic approach” to reflect the unexpected changes in the climate and energy environments as well as in the energy policies and technologies. Research in this area is very significant for the future of the building, energy, and environmental industries around the world. However, there is a lack of studies from the perspective of the dynamic approach and the system integration, and thus, this study is designed to fill the research gap. This study highlights the state-of-the-art in the major phases for a building’s dynamic energy performance (i.e., monitoring, diagnosing, and retrofitting phases), focusing on the operation and maintenance phase. This study covers a wide range of research works and provides various illustrative examples of the monitoring, diagnosing, and retrofitting of a building’s dynamic energy performance. Finally, this study proposes the specific future developments and challenges by phase and suggests the future direction of system integration for the development of a carbon-integrated management system as a large complex system. It is expected that researchers and practitioners can understand and adopt the holistic approach in the monitoring, diagnosing, and retrofitting of a building’s dynamic energy performance under the new paradigm of an “Urban Organism”.
•An energy atlas of the multifamily building stock in Sweden is presented.•Its development is automated using Extract, Transform and Load technology.•It can be used to support energy retrofitting on ...various spatial scales.•The demand for renovation and energy retrofitting will peak in the coming decade.•The use of energy in the existing building stock can be reduced up to 50% by 2050.
Many studies have highlighted the importance of retrofitting to mitigate the energy use of building stocks. An important step in the development of renovation strategy and energy conservation advising is to gather information of the energy performance of the existing buildings. However, renovation strategies must also consider the socio-economic challenges associated with the cost of energy retrofitting. This paper describes the development of an energy atlas of the multifamily building stock in Sweden for visualizing and analyzing energy use and renovation needs. The atlas has been developed using Extract Transform and Load technology (ETL) to aggregate information on the energy performance, building ownership, renovation status, and socio-economic status of inhabitants from various data sources. The atlas can visualize the energy use and renovation status of multifamily buildings in 2D maps and 3D models, displaying data for either individual buildings or aggregated data on spatial scales ranging from 250×250m squares through district and municipality to county areas. A demonstration of its use on national and city scales indicates that energy retrofits of multifamily buildings reaching a service life of 50years can reduce the energy use of the existing building stock by up to 50% relative to 1990. However, costs associated with renovation and energy retrofits of multifamily buildings can be problematic, especially in economically weak suburbs. A good understanding of past and future renovation needs and socio-economic consequences is important in the development of a sustainable national renovation strategy.
The building sector accounts for 40% of the total energy consumption in the EU. It faces great challenges to meet the goal of transforming the existing building stocks into near zero-energy buildings ...by 2050. The development of Energy Performance Certificate (EPC) schemes in the EU provides a powerful and comprehensive information tool to quantitatively predict annual energy demand from the building stock, creating a demand-driven market for energy-effective buildings. Properties with improved energy rating have had a positive impact on property investments and rental return because of the reduced energy bills. In addition, the EPC databases have been applied to energy planning and building renovations. However, it should be mentioned that the current evaluation system faces problems, such as not being fully implemented, delivering low quality and insufficient information to stimulate renovation, therefore requiring improvements to be made. This paper provides a review of the current EPC situations in the EU and discusses the direction of future improvements. The next generation EPC should rely on BIM technology, benefit from big data techniques and use building smart-readiness indicators to create a more reliable, affordable, comprehensive and customer-tailored instrument, which could better represent energy efficiency, together with occupants’ perceived comfort, and air quality. Improved EPC schemes are expected to play an active role in monitoring building performance, future energy planning and quantifying building renovation rates, promoting energy conservation and sustainability.
•Presentation of a brief review of the EPC-related directives.•Review and comparison of the development of the EPC in EU member states.•Discussion on the utilization of the EPC at the urban scale.•Identification of the existing issues and shortcomings in the current EPC.•Proposal of future improvements for the EPC.
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