Steel and concrete are traditionally used as structural materials for non-residential and multi-housing buildings. However, wood can meet the same structural property requirements, and a variety of ...multi-story buildings have recently been built all over the world using this key material. In this study, the main motivations and barriers to wood adoption for structural uses in non-residential buildings are highlighted, based on an analysis of grey literature concerning some well-known buildings and on scientific literature. The motivations found were linked to sustainability, lack of expertise, costs, rapidity of erection, and aesthetic of wooden structures. In contrast, the barriers preventing its use encompass building code implementation, technology transfer, costs, material durability and other technical aspects, culture of the industry, and material availability. Furthermore, an analysis of non-residential timber building meeting minutes for nine projects is also presented to support the identification of problems and concerns related to site assembly issues, the conception of the building, the scheduling, and stakeholders’ relationships. With a better understanding of the expectations and challenges concerning wood usage in non-residential construction projects, companies will be able to adapt their business models and use the resource even more in the future to develop innovative structures.
This work presents a new operational framework to measure the smartness and smart readiness of highly electrified buildings. The framework seeks to enhance legacy systems and controls of existing ...buildings and establish minimum criteria for future constructions to ensure they interact effectively with users and the grid, aiming for a clean energy transition. To this end, we develop two modified complementary assessments, one based on the method indicated by the Smart Readiness Indicator (SRI), proposed by the European Union (EU), and the other following the Smart by Powerhouse scheme, introduced by a Norwegian consortium of stakeholders focused on developing future proof climate buildings. The proposed structure is implemented in ten non-residential buildings in Norway with different energy systems, typologies, and construction dates. The results of this study demonstrate that energy flexibility quantification plays a crucial role in correctly implementing the framework in highly electrified buildings. Therefore, the dynamic impact of having Electric Vehicle Charging (EVC) and other electrical-dependent loads must be considered in the assessment. With the proposed modifications, the EVC weight in the flexibility score now varies from 24.0 to 43.6%, up from the original 5%. Overall, the pilot buildings have a smart readiness level between 21.6% and 31.7%, with mostly automated smartness levels. Nevertheless, the study also emphasizes the need to differentiate current HVAC (Heating, Ventilation, and Air Conditioning) technologies and their efficiencies.
Green buildings have been widely adopted to achieve sustainable development in the built environment. However, the high cost is the main obstacle to develop green buildings. Whether the operational ...savings of green buildings could recover the initial construction cost is still under debate. This paper aims to empirically examine the above question by conducting a life cycle cost analysis of non-residential green buildings in the tropic climate by comparing the Life Cycle Costs (LCC), Construction Costs (CC) and Operation Costs (OC) for various types of buildings that are certified by different levels of Green Mark in Singapore. Data were collected from 44 non-residential buildings that were constructed over the period for 1978–2013 on a national scale. The findings show that the annualized average values of LCC, CC and OC of green buildings are S$ 222.03/m2, S$ 91.85/m2 and S$ 130.18/m2 respectively (S$ as Singapore Dollar, $ as United States Dollar, and S$ 1 = $ 0.73). One level increase of the Green Mark certificate standard would increase the annualized LCC and CC by S$ 47.81/m2 and S$ 25.37/m2 respectively, with no significant influence on the OC. Key influencing factors and their effects on both the annualized LCC and OC have also been identified in the discussion. The findings contribute to the literature by providing a clear framework to analyze life cycle economic assessment of green buildings and by enriching the diversity of cost comparison for green buildings across different regions.
•A framework to analyze life cycle cost of green buildings is proposed.•LCC of 44 non-residential green buildings were calculated and compared.•Annualized average LCC of green buildings in Singapore is SGD 222.03/m2.•Increase of Green Mark certified standard would increase LCC and CC, not for OC.•Annualized LCC is largely influenced by the Escalating Rate of Operation Costs.
Reducing energy consumption in buildings and increasing renewable production are key goals of European policies to achieve a sustainable and competitive low-carbon economy by 2020 and beyond. ...Non-residential buildings constitute a heterogeneity sector characterized by high energy consumption and various building types, sizes and energy characteristics over Europe. This paper presents the overall results of the data collected by the GreenBuilding Programme (GBP), launched in 2006 to promote and improve energy efficiency in new and existing European non-residential buildings. The GPB involved building owners willing to adopt energy efficiency measures to decrease energy consumption of their buildings by of at least 25%. Based on voluntary participation, hundreds of partners joined the project, which collected data from more than a thousand buildings of different age, size, use and type (such as offices, hotels, and industry). This paper provides an overview of the Programme and its main results up to its completion in 2014. The paper focuses on building characteristics, energy performance, efficiency measures and energy savings, which are globally estimated to be around 985 GWh/year. A more detailed focus is then given to office buildings, which represent the most frequent building category in the Programme. Case studies are presented to show best practices in various countries with consolidated energy efficiency policy strategies. The paper categorises the main technological measures related to envelope, appliances and systems. It shows how a wide range of technologies are becoming an integral part of buildings and how technology plays a major role in exploiting the massive potential benefits of reducing building energy consumptions. The analysis of the results generates a reliable snapshot of European non-residential building stock.
•An overview of the operation and performance of the solar chimney were introduced.•Potential design and operating parameters affecting the SC was discussed.•Natural ventilation in solar chimney was ...elaborated.
The requirement for passive cooling strategies in buildings has great attention in almost all countries, where hot temperatures are predominant throughout the year. The ventilation process is a crucial necessity for a healthy lifestyle and its significance is additionally highlighted through the contemporary universal outbreak of Covid-19. One of the promising applications for cooling residential buildings is the solar chimney (SC) that is particularly convenient for hot and humid climates. The solar chimney is a natural draught passive method that utilizes available solar energy to build up the stack pressure. The solar chimney participates in elevating the cooling and heating efficiency of residential/non-residential spaces. The present article introduces an overview of the operation and performance of the SC. Studying the potential design and operating parameters influencing the SC performance for natural ventilation (NV) compared to the electrical high-energy technologies to sustain the acceptable indoor climatic conditions is important. As well, the natural ventilation for harsh climate conditions using SC only is not applicable so the enhanced solar ventilation systems are studied. Combined enhanced cooling/heating energy systems based on the solar chimney are considered as an effective strategy towards low-energy consuming buildings.
Investments in energy efficiency are vital for reducing greenhouse gas emissions by 2030 given that changes in the structure of the main energy sources cannot be expected in the short to medium term. ...The greatest potential for energy savings and cutting emissions lies in buildings due to their significant carbon intensity and rapid growth rate. However, gaps remain in what is known about integrating decarbonisation of the built environment into the economy-wide system. The paper addresses such gaps by examining the socio-macroeconomic implications of different scenarios related to building stock investments in a small open economy. The effectiveness of the measures implemented for various building types and the possibility of a rebound effect are also considered. The study is valuable for the peculiarities of the recursive dynamic computable general equilibrium model, GreenMod Slovenia, which was established to analyse the effects of decarbonisation. Two major contributions emerge: (1) projected energy efficiency in buildings is presented separately for commercial services, public services and households in two investment scenarios, namely, the business-as-usual scenario and the energy efficiency scenario with additional investments; and (2) the disaggregation of households into income quintiles to project their consumption of energy inputs. The study reveals vital macroeconomic benefits flowing from the energy efficiency scenario, including higher GDP and employment. Second, energy efficiency improvements in commercial services might encourage higher energy consumption. Finally, low-income households reduced the consumption of energy products the least. In this quintile group, energy efficiency improvement can lead to greater energy consumption, denoting policy failure.
•Energy-efficient buildings are a small yet key step towards decarbonisation.•Energy efficiency improvements might see poor households use even more energy.•Regarding energy use, commercial services are less responsive to investments.
Display omitted
•Unique preconditions, specific characteristics for use can be boundary conditions.•Energy use, users’ behavior, lighting are correlated conditions within buildings.•Boundary ...conditions can help explain the occupants’ behaviour and the use of spaces.•Knowledge of boundary conditions helps to understand how to design buildings.•Boundary conditions can be building/ user/ input-values and method-specific.
This paper aims to review the boundary conditions (B/C) in specific categories (energy, building use, and lighting) within non-residential buildings to pave the way to a better understanding of users’ requirements and needs of the built environment. For this paper, B/C are understood as unique preconditions, specific characteristics for use, determining specific features of buildings, enabling an accurate understanding of non-residential spaces concerning energy use, user behaviour, and lighting.
This paper describes the results of an overall quantitative (1st method) review and a systematic review (2nd method) of boundary conditions and their factors within different types of non-residential buildings from the users’ perception. Followed by a qualitative experts’ literature review (3rd method) on B/C within offices, schools, and hospitals chosen by a team of international experts working together on Subtask A: User perspective and requirements, Task 61 IEA (International Energy Agency): Solutions for daylighting and electric lighting.
The first review method led to the selection of 21 papers. The second method resulted in the selection of 7 papers out of 93,143 found in Scopus; during the 3rd review, experts collectively chose 74 additional papers focussing on the users' factors contributing to specific B/C. The scope of this paper is limited only to offices, schools, and hospitals. Based on the findings, the authors recognise a broad definition of boundary conditions from specific values, and conditions to interconnected factors, user profiles, functions of the building types, and operating hours.
This paper is an overview of B/C factors found in the literature that can help explain the occupants’ behaviour and the use of spaces. B/C are often type of building/user/location/situation/simulation input-values and method-specific. Therefore, they cannot be widely applicable but offer patterns and help to understand the correlations between various factors shaping the built environment. A better comprehension of the reasons for identifying B/C and their factors can help in developing a deeper knowledge of how we use buildings to find optimal ways to design them.
•Integrated thermal and electrical demand simulations for non-residential buildings.•Design optimization considering short-term and long-term storage cycles.•DoE for uncertain boundary conditions in ...non-residential building planning.•Regression analysis of parameters influencing building energy system sizes.•Necessity for considering uncertainty and control strategy within sizing methods.
In non-residential buildings, many factors affect thermal and electrical loads. Some of these factors are not known during the planning process but are essential for a proper energy system design.
Conducting a simulation- and optimization-based sensitivity analysis, this study investigates the effects of usage intensity and weather uncertainties on building energy system sizing. We developed a toolchain that comprehensively covers the stages, from determining user-related electricity demand to thermal demand calculation and energy conversion system design, up to deterministic design optimization of storage systems. By means of design of experiments, we systematically applied the toolchain to an all-electric non-residential building as a use case.
We find that weather has the strongest correlation with optimal storage sizes and the size of energy conversion systems. They are also affected by the usage intensity of certain building zones. In addition, the storage sizes influence each other in the complex building energy system of our use case. Depending on the scenario and objective, annuities deviate 6%, annual emissions deviate up to 10% from the base scenario.
We conclude that normative design methods do not suffice for optimal building energy system design and offer a viable method that can be incorporated into existing planning processes.
•Daily load profiles of fourteen academic buildings are classified using k-means.•Three methods are compared using different data collection time-steps and timeframes.•Two distinct groups of ...buildings are identified regarding power demand patterns.•A seasonal effect is observed using six-month and one-year timeframes.•A two-cluster classification is confirmed for building stock aggregated profiles.
We investigated clustering techniques on time series of daily electric load profiles of fourteen higher education buildings on the same campus. A k-means algorithm is implemented, and three different methods are compared: time-series features extraction with Manhattan distance and raw time series with Euclidian distance and Dynamic Time Warping. The impact of data characteristics with data collection time-steps and timeframes is studied using a database of more than 6,500 daily electric load profiles. We show that Euclidian distance applied to electric demand time series with three-month timeframes and ten-minute time-step provides the most consistent clustering results. In addition, useful insights are highlighted for non-residential buildings electric demand modeling and forecasting. Two groups of buildings can be distinguished regarding electric load profile patterns. On one hand, teaching, research, libraries, and gymnasium buildings show similar patterns distributed in two clusters corresponding to business days and closing days load profiles. On the other hand, campus office buildings present a larger number of clusters inconsistent with day-type dependent load profiles. A seasonal effect is also observed using six-month and one-year timeframes. Finally, a two-cluster distribution is obtained when aggregating all buildings load profiles.
•Buildings with similar water-energy usage and intensity were identified and clustered.•Analysis revealed heterogeneity in water and energy consumption patterns of buildings.•Benchmarking ...buildings provided a measure of comparison for multi-utility management.•Data-driven modeling revealed meaningful insights into urban water-energy nexus.
As the threat of climate change grows alongside a continual increase in urban population, the need to ensure access to water and energy resources becomes more crucial. In the context of the water-energy nexus in urban environments, this work addresses current gaps in understanding of coupled water and energy demand patterns and reveals apparent dissimilarities between utilization of water and energy resources for heterogeneous buildings. This study proposes a data-driven approach to identify fundamental water and energy demand profiles, cluster buildings into groups exhibiting similar water and energy use, and predict their demand. The clustering problem was cast as a two-stage cluster ensemble problem, in which several clustering methods with different settings were employed, and then the results obtained from partial view of the data were combined to achieve consensus among the partitionings. The influential drivers for water and energy consumption were identified, parametric and non-parametric prediction models were developed and compared, utilizing high and low temporal data resolution. The clustering analysis performed in this work revealed that water and energy consumption patterns of heterogeneous buildings are not exclusively characterized by general building characteristics. Analysis of the predictive models showed that an overall non-parametric model provides better predictions for water and energy compared with parametric models and that models with high and low data resolution provide comparable demand predictions. The results of this study highlight the value of data-driven modeling for revealing meaningful insights into usage patterns and benchmarking buildings’ performance to provide a meaningful measure of comparison to facilitate multi-utility management. Overall, the methods outlined in this study provide another step towards building greater resiliency within urban areas in preparation for future changes in population and climate.
PDF
