Building Energy Rating Research Articles

Life Cycle Assessment Meeting Energy Standard Performance: An Office Building Case Study

Transitioning from fossil to renewable energies, particularly photovoltaic (PV) energy, could influence building design in terms of environmental evaluation. The aim of this study was to rate a typical office building that complies with the Israeli Standard SI5282, Energy Rating of Buildings, and to evaluate it by life cycle assessment (LCA). An office building in Tel Aviv with four exterior wall construction technologies was modeled as follows: (1) a concrete-block-based wall with minimal windows; (2) a concrete-block-based wall with maximal windows; (3) an autoclaved aerated-block-based wall with minimal windows; and (4) an autoclaved aerated-block-based wall with maximal windows. The electricity sources used to support the building’s operational energy were: (i) 31% coal, 56% natural gas, and 13% PV (adopted in 2020); (ii) 8% coal, 57% natural gas, and 35% PV (planned for 2025); and (iii) 100% PV (planned for the future). A two-stage nested mixed analysis of variance was used to simultaneously evaluate the results of six ReCiPe2016 methodologies. The results show that as fossil fuels are replaced by PV energy production, there is a greater need to use LCA methodology in building design in conjunction with energy standards. The energy rating is recommended to be carried out with an environmental assessment of the production stage of construction. Ignoring the LCA results could lead to the misinterpretation of a building’s sustainability.

Design optimization of urban typologies: A framework for evaluating building energy performance and outdoor thermal comfort

• A computational workflow is implemented, and a multi-phase optimization framework is developed for evaluating building energy performance and outdoor thermal comfort. • The framework is tested for various low-rise, mid-rise, and high-rise theoretical urban typologies in Syracuse, New York. • Tradeoffs between energy performance and outdoor thermal comfort are studied by energy use and outdoor thermal comfort autonomy, respectively. In the physics-based simulation of urban geometries, the outdoor environment was usually simulated separately from buildings – until recently, when the holistic assessment of the urban environment began to attract more attention. Although analyzing design alternatives with multiple objectives is still a challenge, computational tools enable generating thousands of scenarios to rapidly assess performance corresponding to a specific goal. In this study, we developed a multi-phase optimization framework for conceptual urban design. We tested this framework for urban typologies in Syracuse. The energy performance of each alternative was compared with a baseline. The alternatives that generate wasteful energy performance were filtered out first, then remaining scenarios that performed better than the baseline were analyzed using outdoor thermal comfort autonomy (OTCA). Mid-rise multifamily buildings showed the best performance (55.8% energy improvement compared to the baseline). Although hot week outdoor comfort satisfaction among selected mid-rise typologies was high (92.9–98.5%), the satisfaction in cold week was very low (between 8.4–11.6%) among them. This framework contributes to identifying an acceptable range of design solutions by broadening the perspective of the field toward using a more customized optimization framework in early design that will further guarantee the requirements of energy efficient and sustainable cities.

A new method of evaluating energy efficiency of public buildings in China

Traditional building energy evaluation methods usually adopt a single energy use indicator as the benchmark. However, such single-indicator based methods often lead to a paradox that switching off building service equipment or systems is equivalent to energy saving. To avoid such paradox for a more pragmatic and comprehensive evaluation of building energy use, this paper aims to establish a robust evaluation model of the operational energy efficiency for public buildings by coupling the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE). Firstly, 23 quantitative indexes and 7 qualitative indexes are extracted from existing building energy codes/standards in the input-output perspective of energy performance evaluations for public buildings. The AHP is then used to determine the weight of each index based on a proposed index correction method, which extends the range of applicability of the index system. Finally, a three-level comprehensive evaluation model is established for the operational energy efficiency of public buildings. Furthermore, a case study is conducted on a typical office building to validate the evaluation results with the proposed model. The case building achieves an overall score of 84.9 at a “Good” level, and corresponding recommendations are made for further improving building performance indexes. The proposed method is of great significance to developing building energy efficiency assessment systems and guidelines in China and over the world.

Post occupancy evaluation of 12 retrofit nZEB dwellings: The impact of occupants and high in-use interior temperatures on the predictive accuracy of the nZEB energy standard

The Europe Union needs to reduce its carbon emissions. To achieve the proposed 55% emission reduction target by 2030 it has embarked on a Renovation Wave which aims for more, and deeper, building renovation. Considering this ambition and the scale of the challenge, there remains a surprising paucity of documented post occupancy evaluation studies of deep retrofit projects, particularly those related to the new nZEB standards and of group housing schemes. This paper reports on the post-retrofit performance of a community of 12 single story, one bedroom social houses located in the southeast of Ireland, occupied by retired and elderly tenants. The deep retrofit works included the upgrade of the building fabric, ventilation and heating, all with a view to transforming the living standards of the occupants. They in turn responded, when surveyed, with near unanimous satisfaction. The upgrade and the addition of onsite microgeneration ensured these houses were transformed from lowly F and G national building energy ratings (BER) to A rated homes as calculated by the national energy rating software, DEAP. However, a performance gap is reported between the expected A performance (<75 kWh/m2/yr) and the actual performance, with some homes consuming more than twice the predicted energy, while in one extreme case the mean winter indoor temperatures are more than 7 °C above the operating temperatures assumed by the DEAP software. The higher than expected indoor temperatures are directly correlated with the higher than expected energy consumption, consumed by a heat pump which in itself exhibited inefficiencies in operation.This post occupancy evaluation, post retrofit, provides evidence therefore of high occupant satisfaction, but a satisfaction based on significant energy ‘underperformance’. This case study provides evidence and insights that can help guide future retrofit practices as Ireland progresses towards the transformation of its building stock to near Zero Energy Buildings (nZEB).It also opens up serious questions around the aims and expectations of our national nZEB standard and generates some key insights into the energy consumption of nZEB dwellings and the assessment methods necessary to measure them accurately.

Investigating the probability of designing net-zero energy buildings with consideration of electric vehicles and renewable energy

PurposeDue to technological improvement and development of the vehicle-to-home (V2H) concept, electric vehicle (EV) can be considered as an active component of net-zero energy buildings (NZEBs). However, to achieve more dependable results, proper energy analysis is needed to take into consideration the stochastic behavior of renewable energy, energy consumption in the building and vehicle use pattern. This study aims to stochastically model a building integrating photovoltaic panels as a microgeneration technology and EVs to meet NZEB requirements.Design/methodology/approachFirst, a multiobjective nondominated sorting genetic algorithm (NSGA-II) was developed to optimize the building energy performance considering panels installed on the façade. Next, a dynamic solution is implemented in MATLAB to stochastically model electricity generation using solar panels as well as building and EV energy consumption. Besides, the Monte Carlo simulation method is used for quantifying the uncertainty of NZEB performance. To investigate the impact of weather on both energy consumption and generation, the model is tested in five different climatic zones in Iran.FindingsThe results show that the stochastic simulation provides building designers with a variety of convenient options to select the best design based on level of confidence and desired budget. Furthermore, economic evaluation signifies that investing in all studied cities is profitable.Originality/valueConsidering the uncertainty in building energy demand and PV power generation as well as EV mobility and the charging–discharging power profile for evaluating building energy performance is the main contribution of this study.

A rapid evaluation method for design strategies of high-rise office buildings achieving nearly zero energy in Guangzhou

The construction of nearly zero energy buildings (NZEB) has achieved dramatical impact on global warming and energy crises. It is still a challenge for designers to derive design strategies on how to achieve NZEB in the early design stage, because a complex modelling process with many input parameters of the current NZEB design and evaluation tool is still unavoidable. This article, therefore, aims to introduce a tool suitable for the rapid and reliable evaluation of NZEB design strategies for high rise office building in the city of Guangzhou in China. Firstly, a high-rise office building with typical geometry features is established by sensitivity analysis and survey, thereby the reference building consumption is obtained. Secondly, comprehensive simulations on cases with various envelope features, air conditioning performances and lighting control methods is carried out. Based on the sensitivity analysis on simulation results, key influencing parameters are selected out, effective strategies which fulfills “Technical standard for nearly zero energy buildings (NZEBTS)” are put forward. Finally, a parametric building energy evaluation model is built by regression analysis on simulation results. Combined with energy efficiency index from “NZEBTS”, an evaluation tool is developed to help designer determine NZEB strategies. The results revealed that the most effective strategies to achieve NZEB in Guangzhou are to apply high performance external windows, improve air conditioning systems and utilize intelligent zone-controlled lighting systems, meanwhile, the utilization ratio of renewable energy (ηs) should be more than 40% of building total annual energy consumption.

Sustainability insights on emerging solar district heating technologies to boost the nearly zero energy building concept

Arising the Nearly Zero Energy Buildings (NZEB) concept in Europe, the solar district heating systems (SDHS) present a potential solution to meet the buildings sector's European energy performance directive. Nevertheless, current practices face several technological and economical barriers to ensure service quality. In this context, our work presents a sustainability analysis (technical, economic, environmental, and social) for SDHS integration in the residential sector to meet the NZEB and positive energy building goals. This paper proposes an application of a machine learning model incorporating multi-objective optimization and multi-criteria decision making to facilitate a sustainability index for the decision-making stakeholders and policymakers. The proposed analysis application is illustrated through retrofitted residential communities with building energy rating (D) at different sizes (10, 25, 50, 100, and 500 houses) located in Emmen (Netherlands) and compared to a standard decentralized heat pump. The optimization results show the ability of SDHS to provide a solar fraction up to 95% in the community of 500 houses. Furthermore, achieving a NZEB status is only approved economically from a community size of 100 houses with a life cycle cost of 41 €/m2 and a payback period of 25 years. These results align with a substantial environmental and social improvement of 78.2% and 29.7%, respectively, compared to the decentralized heat pump. Overall, this study provides policy decision making with an evaluation for positive energy communities and suggests the SDHS integration to meet the global sustainability goals.

Building energy performance analysis at urban scale: A supporting tool for energy strategies and urban building energy rating identification

The energy consumption of the building sector has complex and interrelated characteristics. The development of modeling techniques capable of evaluating the impacts of energy-efficient technologies requires great effort owing to the variety of building sizes and geometries, wide range of thermal properties of building envelopes, variable occupant behavior, and lack of measured consumption data. However, energy policies require thorough knowledge of the energy performance of a building stock to be truly effective. In this paper, an urban-scale building energy modeling tool based on an engineering bottom-up approach is presented. The employed methodology makes it possible to assess the energy performance of a building stock, define energy efficiency measures, and evaluate their effects automatically using a geographic information system. Moreover, the modeling tool introduces an innovative urban building energy rating similar to the energy rating of individual buildings. The proposed energy modeling tool is then applied to a real case consisting of three villages in central Italy with 769 residential buildings.

Evaluation of Energy Performance and Comfort: Case-Study of University Buildings with Design Adapted to Local Climate

One of the main strategies to reduce countries’ energy bills is to invest in efficient buildings. To achieve this objective, the European Union Member States have developed different methodologies to evaluate building energy performance, which are often supported by simulation tools. These tools are based on calculation engines that use databases and simplifications to attempt to bring their results close to real building performance and are mostly designed to be used at the end of the process, neglecting their role in project decision-making processes. To compensate for this situation and to obtain the most accurate results, the methodologies recommend previous work during the building design phase to adopt passive design solutions that learn from experience and aim to adapt the building design to the local climate. However, these design solutions are difficult to adopt while working with medium to large public buildings and are often not properly understood by the simulation tools. In addition, new BIM methodologies are being implemented, starting to enable proper interaction between the designer and the results, and opening up the option of introducing other types of calculations, such as building comfort, in the calculation process. Among the group of countries with limited simulation tools that are starting to be substituted is Spain, which recently launched its first BIM-based energy simulation tool. This tool aims to compensate for the limitations of the former simulation tools and opens up the option of performing comfort calculations by sharing information with other programs. The objective of this research is to evaluate, from different perspectives, the performance of this new simulation tool on three buildings at the University of Alicante. These were chosen as university campuses are responsible for large groups of buildings and belong to the group of stakeholders interested in obtaining efficient and comfortable buildings. These case studies are defined by their extreme adaptation to design recommendations for mild-warm weather. At the end of the process, the difference is measured between simulation and real building performance. The results obtained show that simulation still differs greatly from real building performance from the energy performance point of view, while the comfort evaluation shows results that are closer to the reality of the buildings.

Buildings’ Energy Efficiency and the Probability of Mortgage Default: The Dutch Case

We investigate the relationship between building energy efficiency and the probability of mortgage default. To this end, we construct a novel panel data set by combining Dutch loan-level mortgage information with provisional building energy ratings provided by the Netherlands Enterprise Agency. Using the logit regression and the extended Cox model, we find that building energy efficiency is associated with a lower probability of mortgage default. There are three possible channels that might drive the results: (i) personal borrower characteristics captured by the choice of an energy-efficient building, (ii) improvements in building performance that could help to free-up the borrower’s disposable income, and (iii) improvements in dwelling value that lower the loan-to-value ratio. We address all three channels. In particular, we find that the default rate is lower for borrowers with less disposable income. The results hold for a battery of robustness checks. This suggests that the energy efficiency ratings complement borrowers’ credit information and that a lender using information from both sources can make superior lending decisions than a lender using only traditional credit information. These aspects are not only crucial for shaping future energy policy, but also have implications for the risk management of European financial institutions.

Hotel energy rating system using dynamic zone EUI method in Taiwan

This study seeks to develop a predictive method for hotel energy consumption and an energy rating system for existing hotels based on utility bills. It forms part of T-BERS (Taiwan’s Building Energy Rating System) currently being developed by the Architecture and Building Research Institute. T-BERS adopts the dynamic zone EUI (energy use intensity) method and a right-skewed EUI distribution and references the 7-class rating of EP Label used in the EU for public buildings. Rather than using a EUI for an entire hotel building as the rating index, the dynamic zone EUI method takes “dynamic” EUI indices calculated accumulatively from corresponding EUIs for 10 energy zones in a hotel. Thus, a customized EUI rating scale may be established to tailor to the unique scale and spatial composition of each hotel, thereby ensuring a fair assessment. The minimum, median and maximum EUI values for the 10 energy zones are set based on benchmark models simulated with eQUEST. The median EUI value is set based on the minimum criteria in the latest building code, and the maximum and minimum values based on the worst and best conditions in existing hotels in the market. The scoring model is compared and validated against the distribution of actual EUIs for 89 hotels measured by Taiwan's Bureau of Energy. It is shown to be aligned with real distributions of EUIs in the hotel building market and comply with the requirements of scale sensitivity and scale reliability. A modification for energy assessment predicating on utility bills has also been proposed herein. Using yearly occupancy rate YOR as a modifying factor, a hotel with irregular operations can now receive more customized, fair and rational assessment.

Rethinking the concept of building energy rating system in Australia: a pathway to life-cycle net-zero energy building design

Over the last decades, Australia has taken several measures to tackle the increasing trend of energy use in residential buildings. Recently, the Trajectory for Low Energy Buildings has been endorsed aiming to reduce energy usage in residential buildings. However, the primary focus of this trajectory is on decreasing operational energy without considering the embodied energy of the building and systems. This paper aims to address one primary question; ‘can the continued exclusion of embodied energy from the energy efficiency regulations effectively lead to reducing energy consumption in Australian residential buildings?’. The findings indicate that embodied energy becomes a dominating factor as buildings’ thermal performances increase according to the Australian energy efficiency regulations. In transitioning from a standard 6.0-star building to a highly energy-efficient 8.7-star building, the proportion of embodied energy significantly increases from 20–40% to 50–75%. This study recommends establishing minimum mandatory requirements for buildings’ embodied performance.

Linking data model and formula to automate KPI calculation for building performance benchmarking

Buildings consume a large proportion of global primary energy and building performance management requires massive data inputs. Key Performance Indicator (KPI) is a tool used for comparing different buildings while avoiding problems caused by heterogeneous data sources. However, silos of building and energy consumption data are separate, and the linkages between a KPI formula and different data sets are often non-existent. This paper develops an ontology-based approach for automatically calculating the KPI to support building energy evaluation. The proposed approach integrates building information from BIM and energy and environmental information collected by sensor networks. A KPI ontology is developed to establish a KPI formula, thereby linking static and dynamic data generated in the building operation phase. Each KPI can be defined by inputs, a formula and outputs, and the formula consists of parameters and operators. The parameters can be linked to building data or transformed into a SPARQL query. A case study is investigated based on the proposed approach, and the KPIs for energy and environment are calculated for a real building project. The result shows that this approach relates the KPI formula to the data generated in the building operation phase and can automatically give the result after defining the space and time of interest, thus supporting building performance benchmarking with massive data sets at different levels of details. This research proposes a novel approach to integrating the KPI formula and linked building data from a semantic perspective, and other researchers can use this approach as a foundation for linking data from different sources and computational methods such as formula created for building performance evaluation.

Urban form study for wind potential development

Wind energy development is helpful for realizing a green city. This work concentrates on the study of estimating urban wind energy with consideration of urban morphology. Fourteen typical urban forms in Beijing city were selected and analyzed with nine relevant urban morphology parameters. Computational fluid dynamics numerical simulations were used to evaluate the wind energy potential of the urban forms. This work demonstrates that urban forms with higher plot ratio and mean aspect ratio usually have higher wind potential density by site area, an important indicator for neighborhood-scale wind potential development. Urban forms with higher average building height would have higher wind potential density by roof area, an important indicator for building-scale wind potential development. To promote wind potential over roofs, a layout of 45° of building configuration with inlet wind direction and building forms with round-angle corners are suggested. Local wind distribution is important for wind energy evaluation of individual buildings and wind energy distribution over different directions; however, it has a substantially lesser effect on the general wind potential comparison among urban forms with different urban characteristics.

A Holistic Review of Building Energy Efficiency and Reduction Based on Big Data

The construction industry is recognized as a major cause of environmental pollution, and it is important to quantify and evaluate building energy. As interest in big data has increased over the past 20 years, research using big data is active. However, the links and contents of much literature have not been summarized, and systematic literature studies are insufficient. The objective of this study was a holistic review of building energy efficiency/reduction based on big data. This review study used a holistic analysis approach method framework. As a result of the analysis, China, the Republic of Korea, and the USA had the most published papers, and the simulation and optimization area occupied the highest percentage with 33.33%. Most of the researched literature was papers after 2015, and it was analyzed because many countries introduced environmental policies after the 2015 UN Conference on Climate Change. This study can be helpful in understanding the current research progress to understand the latest trends and to set the direction for further research related to big data.

Quantitative evaluation of the building energy performance based on short-term energy predictions

Building energy prediction is a potential tool for benchmarking the future energy uses of individual buildings. However, inevitable gaps between predicted and actual energy uses and discrepancies between buildings make it challenging to quantify energy consumption. Therefore, this paper proposes a systematic methodology of quantitative building energy evaluation based on short-term energy prediction. First, the 24-h ahead building energy prediction model is developed based on a recurrent neural network via the Multi-Input Multi-Output strategy. Second, the quantitative energy evaluation strategy is proposed to quantify prediction gaps based on the 1-D k-means clustering. Third, case studies are conducted on five real buildings to verify the reliability of the proposed methodology. Results show that the energy prediction models achieved outstanding accuracies. Besides, it is necessary to analyze the absolute percentage error (APE) variation of each time step to deeply understand the building energy performance rather than the overall prediction performance evaluation index, such as CV-RMSE and MAPE. Further, customized energy quantification systems are established for buildings per their specific, individual energy performance. The building energy is quantified by labeling APEs into multiple levels. Moreover, building operation characteristics can be further understood by quantifying energy uses.

Energy Rating of Buildings to Promote Energy-Conscious Design in Israel

Improving the energy efficiency of existing and new buildings is an important step towards achieving more sustainable environments. There are various methods for grading buildings that are required according to regulations in different places for green building certification. However, in new buildings, these rating systems are usually implemented at late design stages due to their complexity and lack of integration in the architectural design process, thus limiting the available options for improving their performance. In this paper, the model ENERGYui used for design and rating buildings in Israel is presented. One of its main advantages is that it can be used at any design stage, including the early ones. It requires information that is available at each stage only, as the additional necessary information is supplemented by the model. In this way, architects can design buildings in a way where they are aware of each design decision and its impact on their energy performance, while testing different design directions. ENERGYui rates the energy performance of each basic unit, as well as the entire building. The use of the model is demonstrated in two different scenarios: an office building in which basic architectural features such as form and orientation are tested from the very beginning, and a residential building in which the intervention focuses on its envelope, highlighting the possibilities of improving their design during the whole design process.

Understanding green building energy performance in the context of commercial estates: A multi-year and cross-region analysis using the Australian commercial building disclosure database

To understand the relationship between green building energy performance and regional commercial estates, this study analysed Australia’s Commercial Building Disclosure (CBD) program database. This database discloses the annual energy use intensity (EUI) and the corresponding energy rating (1–6 stars) of 2460 National Australian Built Environment Rating System (NABERS) certified office buildings. The study selected for analysis Australia’s six largest cities and then used panel data regression, where commercial estate factors (total stock of office buildings, vacancy rate, average gross face rent, and government incentives such as financial support) served as independent variables and the EUI was the dependent variable. The p-values of all the models are below 0.05, indicating that the results are statistically significant. Results showed the commercial real estate factors were significantly related to the EUI for buildings with a rating of 1 star and above. The correlation between EUI and commercial real estate factors became less strong with the rating level increasing. The effect of ‘green building’ branding makes the office buildings more attractive with regard to tenancy and their energy performance more reflective of the variation in the commercial real estate market. This study is a frontrunner in contextualising green building energy performance and ratings in the context of regional commercial estate, and the regression models employed in the study could be used to define regional baselines for energy ratings in future studies.

Parameters for Thermal Energy Systems Resilience

To provide a building design that is robust, adaptable, and affordable, one must understand the aspects of the building’s geographic location that will impact equipment selections, operating hours, and maintenance needs. One must also consider the building’s “thermal resilience,” i.e., its ability to withstand a heating plant outage. Designing for resilience is of growing importance, especially for military and government installations that must maintain critical functions even during outages. Buildings with a fast rate of temperature degradation with the loss of heating system function have low resiliency; buildings with a slower rate of temperature degradation have higher resiliency. In extreme cold climates, resiliency can play an integral role in protecting property during an outage. A drop in indoor temperature can pose a risk of freezing plumbing, which can lead to burst pipes and interior flooding that can cause enormous and costly damage, and which can effect a loss of workspace in an office building. More resilient designs must consider not only building HVAC installations, but also building envelope and the whole energy infrastructure, including thermal capacity of concrete and brick walls, internal water pipes, critical system redundancy, outside insulation without weak points, and a centrally controlled, low carbon hot water heat supply. This paper describes a quantitative approach to evaluate a system’s resiliency based on analytical and experimental studies conducted under IEA EBC Annex 73 and the Environmental Security Technology Certification Program (ESTCP) project Technologies Integration to Achieve Resilient, Low-Energy Military Installations, to evaluate building energy performance in extreme climate conditions. This work recommends that more thermally resilient designs for buildings in cold climates include consideration of increased thermal resistance of the building envelope, improved whole-building airtightness, and higher thermal mass.

Impact of Urban Morphology and Climate on Heating Energy Consumption of Buildings in Severe Cold Regions.

This study aims to acquire a better understanding of the quantitative relationship between environmental impact factors and heating energy consumption of buildings in severe cold regions. We analyze the effects of five urban morphological parameters (building density, aspect ratio, building height, floor area ratio, and shape factor) and three climatic parameters (temperature, wind speed, and relative humidity) on the heating energy use intensity (EUI) of commercial and residential buildings in a severe cold region. We develop regression models using empirical data to quantitatively evaluate the impact of each parameter. A stepwise approach is used to ensure that all the independent variables are significant and to eliminate the effects of multicollinearity. Finally, a spatial cluster analysis is performed to identify the distribution characteristics of heating EUI. The results indicate that the building height, shape factor, temperature, and wind speed have a significant impact on heating EUI, and their effects vary with the type of building. The cluster analysis indicated that the areas in the north, east, and along the river exhibited high heating EUI. The findings obtained herein can be used to evaluate building energy efficiency for urban planners and heating companies and departments based on the surrounding environmental conditions.