Energy Performance Of Office Buildings Research Articles

The impact of microclimate on energy performance of office buildings within urban contexts located in a composite climate, the city of Indore

The energy consumption and thermal performance of a building depend not only on the internal factors, geometry and orientation but also on the external microclimatic factors such as vegetation, solar radiation, air temperature, wind speed and wind direction. Further, it is also influenced by the surrounding built environment characteristics such as street geometry, buildings and surface characteristics. The main objective of the current research paper is to record the energy performance of office buildings within urban contexts, located in a composite climate, for instance, the city of Indore and to determine the influence of the external parameters on energy consumption of the built space so as to optimize the built environment factors and achieve low energy consumption. The current study involves the identification of two office buildings in Indore with different built environmental characteristics. Field measurements were carried out on street canyons along the south and west façades of the buildings and the impact of external microclimatic parameters and the surrounding built environment characteristics on energy consumption of the building was quantified in this study. It was found that the street geometry, H/W ratio, street orientation, building material, urban density and vegetation has significant effects on microclimate and energy consumption of the buildings.

Relationship Analysis and Optimisation of Space Layout to Improve the Energy Performance of Office Buildings

Architectural space layout has proven to be influential on building energy performance. However, the relationship between different space layouts and their consequent energy demands has not yet been systematically studied. This study thoroughly investigates such a relationship. In order to do so, a computational method was developed, which includes a method to generate space layouts featuring energy-related variables and an assessment method for energy demand. Additionally, a design of experiments was performed, and its results were used to analyse the relationship between space layouts and energy demands. In order to identify their relationship, four types of design indicators of space layout were proposed, both for the overall layout and for each function. Finally, several optimisations were performed to minimise heating, cooling and lighting demands. The optimisation results showed that the maximum reduction between different layouts was up to 54% for lighting demand, 51% for heating demand and 38% for cooling demand. The relationship analysis shows that when comparing the four types of design indicators, the façade area-to-floor area ratio showed a stronger correlation with energy demands than the façade area ratio, floor area ratio and height-to-depth ratio. Overall, this study shows that designing a space layout helps to reduce energy demands for heating, cooling and lighting, and also provides a reference for other researchers and designers to optimise space layout with improved energy performance.

Impacts of Courtyard Envelope Design on Energy Performance in the Hot Summer–Cold Winter Region of China

This paper aims to investigate the effects of courtyard envelope design on the energy performance of office buildings in the hot summer–cold winter region of China. Two types of courtyard buildings were simulated with 200 energy models by changing the following variables: window–wall ratio (south, north, east, and west walls), window U-value, wall U-value, solar heat gain coefficient, and orientation. The treed Gaussian process (TGP) sensitivity analysis method was employed to quantify the contributions of parameters related to courtyard design that result in the changes of annual cooling, heating, lighting, and total energy consumption. The results show that the courtyard envelope design has a significant effect on the energy consumption in this case study. The most influential factor affecting annual cooling energy consumption and the annual total energy consumption is the orientation, which is responsible for 37% and 81%, respectively, in two layouts to annual cooling energy use. The corresponding proportion increased to 45% and 86% in terms of the total energy consumption. The most influential factor influencing annual heating energy use is the window U-value, which explained nearly 60% of the changes to the heating energy use. The effect of the solar heat gain coefficient in two kinds of layouts is as high as 82% and 79% for lighting energy use in this case study. Due to the different courtyard forms, the magnitude of the effect of the parameters on energy consumption and the main trend of the effect is slightly different.

Space layout and energy performance: Parametric optimisation of space layout for the energy performance of office buildings

Studies have shown that space layout design can impact the building energy performance (BEP). However, its isolated effect on the BEP has not been identified yet. Performative computational architecture has proven to be effective to improve the BEP. However, only a few studies have tried to apply the performative computational architecture to space layout design. This research aims to investigate how space layout affects BEP, and to develop a computational optimisation method for space layout to improve the BEP of office buildings. Firstly, the mechanism on how space layout affects the BEP and how much energy is affected by space layout were identified through literature review and simulation. 11 layouts with different function allocations were simulated and compared. The outcome showed that layout variance affected lighting the most, and the maximum difference happened in Harbin, being 46% without shading and 35% with shading. As a follow-up, another literature review was conducted, which identified the functional requirements of space layout design, methods for automatic generation of space layout, and requirements for energy performance optimisation. In addition, a computational method was developed to optimise space layout design for energy performance improvement, regardless of functional requirements. As a result, the relationship between space layout and energy demands were recognised. In conclusion, space layout has proven to be a significant influence on the BEP, and conscientious design can improve it. For optimal energy performance, manual design of space layout is not feasible; in order to do that, a computational approach is needed.

The effects of shading devices on office building energy performance in Mediterranean climate regions

Fixed shading devices (SDs) are still used as an essential and useful element in architectural design. Even with minor changes to be made when designing these devices, the energy performance of a building, especially in hot climate regions, can be significantly increased. In contrast to studies using one or a few parameters, this study aimed to make a comprehensive evaluation by considering more parameters simultaneously to determine energy-efficient fixed external SD scenarios that can be used in office buildings. This approach increases the accuracy of the results in terms of providing trade-offs. This study also aims to fill the gap of the research on SD strategies in Turkey. A total of 1485 scenarios were created with fixed external SDs (overhangs, horizontal and vertical louvers, and egg-crate variations) using the parameters of direction, glazing type, window-to-wall ratio (WWR), SD depth, and slope. Primary energy consumption values of all scenarios were calculated with the DesignBuilder software. Results were discussed according to the impact of each parameter on energy consumption and evaluated through descriptive statistical analysis. As a result, energy-efficient scenarios were determined. The best scenarios obtained for each SD type reduced the cooling energy consumption by between 37% and 49% compared to the no shading scenario using high-performance glazing type and by between 73% and 78% compared to the no shading scenario using low-performance glazing type. The total annual energy consumption was reduced by approximately 33% and 70%, respectively.

Improved energy performance evaluating and ranking approach for office buildings using Simple-normalization, Entropy-based TOPSIS and K-means method

Reasonable evaluation of building energy performance can provide great benefit for government (policy makers) to put forward effective energy conservation policies, and building regulators to make suitable energy-saving strategies. Traditional approaches employ the annual total energy consumption (or the annual total energy use intensity) to evaluate and rank the energy performance of buildings. However, these approaches ignore the energy consumption fluctuation of buildings in different seasons. As a consequence, this paper proposes an improved data-driven-based building energy performance evaluating and ranking approach for office building in city scale using the Simple-normalization, Entropy-based TOPSIS and K-means method. The proposed approach chooses the monthly energy use intensity in single year of office buildings as evaluation indicators, and consists of three steps: (1) The building energy use intensity are calculated by Simple-normalization method. (2) The Entropy-based TOPSIS method is applied to score and evaluate the building energy performance. (3) Finally, the K-means method is employed to rank the evaluated buildings. To validate the proposed approach, 24 office buildings in Tongling city of China are served as case study to present the evaluating and ranking procedure. Simultaneously, the comparison analysis between the proposed approach and two traditional approaches are conducted considering consistency and rationality synchronously. The comparison results demonstrate the proposed approach can more effectively score the energy performance of office buildings, and achieve the reasonable order and grade. In addition, to demonstrate the application, the proposed approach is also applied on Urban-area Building Energy Consumption Monitoring System of Tongling city in China. As a result, this study provides convenient and effective tool to present the energy efficiency gap and energy-saving potential between different buildings in city scale.

Application of operational-based strategic intervention model for evaluating office buildings energy efficiency performance

The operational management and strategic interventions for energy efficiency (EE) of facilities could be optimised if interventions and decision-making processes are well integrated. Hence, this study developed a conceptual dual model for building energy performance (BEP) as a composite model based on prior theories. The theoretical study variables were interventions (technical and operational) and decision-making (management) factors (manifest variables) derived from an extensive literature review. Likewise, the constructs (latent variables) were the aggregated data of the intervention/decision-making evident factors used in the composite scale model. These constructs define the identifiable EE (management) manifest factors and classify them for standardised EE management practices. This paper describes the effects and the causal relationship between constructs derived from these factors that impact BEP via the composite scale model. An online self-administered questionnaire was used in gathering information from the occupants of selected office buildings in two countries (Nigeria and the UK). Structural equation modelling was engaged in evaluating the structure of the composite scale model that serves as a merger of isolated critical factors that affect BEP improvement. The model has four parts: the strategic driver, management policy, operational and building energy performance constructs as distinct sub-models. The results of the model evaluation reveal that the collected data fit the hypothesised dual model and have good fits. The models are not significantly different; they help investigate the fundamental relationship between the constructs. The result also reveals a strong positive correlation of management policy with strategic drivers for EE; strategic drivers with the use of building energy performance model; and management policy with operational EE practices. Path evaluation shown on the dual model specified the hypothesised causal relationship amongst constructs and strategic driver as the only significant positive mediator. Furthermore, the study integrates interventions and decision-making in a new dual model for improving BEP for diagnostic and solution purposes. Facility managers and owners could use the dual model as a strategic and tactical decision-making implement in managing low-carbon office BEP.

Effect of space layouts on the energy performance of office buildings in three climates

Numerous studies have shown that architectural design affects energy performance significantly. However, the effect of space layouts on building energy performance has not been fully analysed. In this paper, we aim to study the effect of space layouts on energy performance. An office building was used as the reference, and 11 layout variants were proposed and compared for energy performance. Three climates (temperate, cold and tropical) were inspected, with three typical cities (Amsterdam, Harbin and Singapore). Dynamic simulation was conducted for the energy performance assessment integrating daylighting simulation with energy simulation. For each layout, two situations were simulated: one has no shading system, and the other one has an exterior screen for shading. Based on the simulation results, it is found that lighting demand is affected the most by the layout variance, and the resulting maximum difference (difference divided by the highest demand) happens in Harbin, being 46% without shading and 35% with shading. Regarding the sum of the final energy for heating, cooling and lighting, using a heat pump system, the maximum difference is 8% for the layouts both without and with shading system occurring in Amsterdam.

Generalized additive models: An efficient method for short-term energy prediction in office buildings

In 2018, commercial buildings accounted for nearly 18.2% of the total energy consumption in the USA, making it a significant contributor to the greenhouse gases emissions (see, e.g. [1]). Specifically, office buildings accounted for 14% of the energy usage by the commercial sector. Hence, their energy performance has to be closely monitored and evaluated to address the critical issues of greenhouse gases emissions. Several data-driven statistical and machine learning models have been developed to assess the energy performance of office buildings based on historical data. While these methods often provide reliable prediction accuracy, they typically offer little interpretation of the relationships between variables and their impacts on energy consumption. Moreover, model interpretability is essential to understand, control and manage the variables affecting the energy consumption and therefore, such a feature is crucial and should be emphasized in the modeling procedure in order to obtain reliable and actionable results. For this reason, we use generalized additive models as a flexible, efficient and interpretable alternative to existing approaches in modeling and predicting the energy consumption in office buildings. To demonstrate the advantages of this approach, we consider an application to energy consumption data of HVAC systems in a mixed-use multi-tenant office building in Chicago, Illinois, USA. We present the building characteristics and various influential variables, based on which we construct a generalized additive model. We compare the prediction performance using various commonly used calibration metrics between the proposed model and existing methods, including support vector machine as well as classification and regression tree. We find that the proposed method outperforms the existing approaches, especially in terms of short term prediction.

Urban governance dispositifs: cohering diverse ecologies of urban energy governance

As cities confront increasingly complex governance problems, conceptions of urban governance are becoming progressively more receptive to grasping its dynamic and multiplex nature, its connection to multiple lines of authority and forms of power, and the socio-material assemblages through which it works. Yet, despite conceptual advances around the dynamism and heterogeneity of urban governing assemblages and their durability, much remains to be understood about the processes and devices that compose and cohere their constituent elements to generate governance capacity. We explore this limitation by deploying Foucault’s concept of ‘dispositif’ to analytically characterize how urban governance capacity is achieved around complex urban problems via processes and devices of composition and cohering. We do so by examining an emergent urban energy governance dispositif focused around top-tier commercial office space in Sydney, Australia: a key site around which multiple elements have been composed in a complex, entangled dispositif to produce effective urban governance capacity and accomplish substantive gains in office building energy performance. We characterise the socio-material elements involved and, more particularly, identify and analyse the processes and devices that compose the dispositif and cohere its governance capacity and we draw out the diverse forms of power that are immanent in these processes. These are, we argue, key steps in refining systematic understandings of the contemporary functioning and politics of the distributed urban governance of complex urban challenges. We conclude with key observations suggested by our analysis for urban governance scholarship.

Linking human-building interactions in shared offices with personality traits

Occupant behavior influences office building energy performance. The level of human-building interactions (HBIs) in shared offices strongly influences building energy use and occupant well-being. This study explored the link between occupant personality types and their behaviors of sharing energy and environment control systems and interactions with their colleagues. Inspired by the Five-Factor Model (FFM), we classified HBI behaviors into four dimensions: willingness to share control, knowledge of control, group decision behavior, and adaptive strategies. These four variables can be mapped to the four personality traits proposed by the FFM: agreeableness, openness, extraversion, and conscientiousness. Our cluster analysis identified six behavioral patterns: average (17.7%), reserved (15.3%), environmentally friendly (16.6%), role model (24.2%), self-centered (17.2%), and mechanist (9.0%). We further applied association rules, a widely utilized machine learning technique, to discover how demographics, building-related contextual factors, and perception-attitudinal factors influence HBI behaviors. Country, control feature accessibility, and group dynamics were found to be the three most influential factors that determine occupants’ HBI behaviors. The study provides insights about building design and operation, as well as policy to promote socially and environmentally desirable HBI behaviors in a shared office environment.

The uncertainty of manual shade control on west-facing facades and its influence on energy performance

Due to the stochastic nature of occupant behavior on manual shades, energy prediction based on realistic shade behavior models differs largely from simplified shade assumptions adopted by building energy codes. Three important questions (when is it important to consider shade behavior models, when does shade behavior related energy uncertainty need to be accounted and when can simplified shade assumptions be used instead of behavior models?) remain unanswered. To address these issues, this paper investigates the impact of occupant uncertainty of solar shade control on building energy performance at temporal and spatial scales as well as predicted performance gaps between simplified shade assumptions and shade behavior models. A stochastic model of manual solar shades developed in a previous study based on field measurements was used in this paper. Co-simulation, statistical calculation and uncertainty analysis were conducted. The results show that energy uncertainty should be considered when evaluating the energy performance of a single room at hourly, daily, monthly and total annual scales. In other cases, shade behavior and related energy uncertainty may be ignored. Fully shade open or closed assumptions lead to a significant deviation of predicted energy performance and thus cannot be used for simulating energy performance of manual shades. Simplified shade assumptions (such as half-open in this research), which is capable of representing average shade behavior patterns, can be used to evaluate the annual energy performance of office buildings and to size cooling/heating equipment instead of a shade behavior model. While for commonly used pessimistic assumptions on manual shades (fully open in summer and fully closed in winter), they over-predict maximum cooling/heating rate by at least more than 5% compared to the shade behavior model.

Occupant behavior long-term continuous monitoring integrated to prediction models: Impact on office building energy performance

Given the massive scientific progress on near zero-energy targets, occupant behavior has become a key variable affecting building energy performance. In this view, the paper builds upon previous contributions to analyze real occupancy of an office building with peer occupants monitored for 2 years. After assessing that peers do not behave the same and do not control equivalently the indoors, acknowledged occupancy models and field-collected data are compared through dynamic simulation on daily and annual bases. To this aim data-driven occupancy models are developed based on the collected data. Moreover, neural response tests are performed on selected occupants to study their emotional status. The estimation of annual energy need highlights the influence of building occupancy. In fact, the simulated building energy consumption can vary by up to 20% by only selecting the occupancy simulation scheme. Moreover, non-negligible discrepancies in terms of value gap and time schedule daily profiles are still found between predicted and measured variables when considering the data-driven models, since they do not take into account multi-physical and non-physical (personal) stimuli. The first results of neural experiment show the role of personal non-physical factors in the inconsistent reaction to thermal stimuli, as key driver for the associated behavior.

Sensitivity Analysis of Infiltration Rates Impact on Office Building Energy Performance

Modeling and predicting building infiltration impact on building energy performance presents a challenge. This paper analyses the modeling method of infiltration rates in different simulation programs. Field blower door test results of building infiltration rates are compared and summarized. Based on literature simulation and field study data, this research analyses the building infiltration rates on the office building HVAC energy use under various climate conditions. Suggested and preferred infiltration rates under various climates are listed.

Impact of space layout on energy performance of office buildings coupling daylight with thermal simulation

Space layout design is one of the most important phases in architectural design, and current studies have shown that it can affect building energy performance. However, its influence has not been quantified. This paper aims at investigating the impact of space layouts on building energy performance. We use the floor plan of an office building in the Netherlands as reference, and propose eleven space layouts based on the reference. Calculations are performed with the tools Honeybee and Ladybug in Grasshopper, which are developed based on Daysim and EnergyPlus, to simulate lighting, cooling and heating demand of these layouts. In addition, we couple daylight with thermal simulation, by importing the artificial lighting schedule calculated in Daysim to EnergyPlus. The result shows that the heating demand of the worst layout is 12% higher than the best layout, the cooling demand of the worst layout is 10% higher than the best layout, and the lighting demand of the worst layout is 65% higher than the best layout. The total final energy use of the worst layout is 19% higher than the best layout.

Relationships between design parameters of see-through thin film photovoltaic facade and energy performance of office building in China cold zone

See-through thin film photovoltaic is a substitute for traditional glass in building facade. Three design parameters of photovoltaic facade have the vast influence on the overall energy performance of building. They are orientation, visible light transmittance and comprehensive heat transfer coefficient. In this study, six photovoltaic facades were established by using two kinds of thin film photovoltaic materials with different transmittances, followed by conducting the simulations of ultimate energy consumptions, in five orientations, of the offices located in Tianjin city which belongs to China cold zone. Then, according to the energy consumption of the reference office, the energy-saving rates of offices with photovoltaic facades are calculated. Finally, the sensitivity of each design parameter to the energy-saving rate of buildings is analyzed. The results indicate that when building photovoltaic façade faces south, the highest energy-saving rate is up to 61.22%, and the lowest energy-saving rate is only 13.7% when the PVF looks east. The energy-saving rate of the room is most sensitive to the orientation, and the sensitivity of the three design parameters changes as the orientation changes. When the photovoltaic facade faces south, according to the sensitivity of the parameters from high to low, the order should be orientation, the comprehensive heat transfer coefficient and the visible light transmittance.

A validated low carbon office building intervention model based on structural equation modelling

Building energy performance in existing stocks via facilities management interventions for low carbon building has become expedient and relevant in global climate change discourse. It has raised the consciousness for the need for a unified decision-support model for Facilities Managers and Owners, which could be used for office buildings across countries in achieving cleaner building energy production and use. This paper aimed at examining the factors that affect office Building Energy Performance; their interdependencies; and identify the critical path for interventions. It filled this gap by presenting a combination of interrelated processes (operations, tactics, and strategies) needed to improve building energy performance, reduce costs and greenhouse gas emissions in buildings for organizations. An online questionnaire survey was used in gathering data on current study model variables from participants of case study office buildings in Nigeria and the UK. Structural Equation Modelling technique was used to examine the factors that contribute to improving the energy performance of heterogeneous office buildings in both countries. The result established a strong correlation among observed variables and constructs and high covariance between constructs. This indicates that dependency and interdependence relationships exist amongst constructs, and in between construct and indicators. The finding reveals that an organization needs Sustainability Policy, Facilities Management and Energy Management as a sub-set of Strategic policy incorporated into its core management policy and operations energy management to achieve low carbon building. It also reveals the most critical pathway in the overall model with Strategic Facilities Management discovered to underpin the optimal performance for office buildings.

The Adaptive Comfort Factor in Evaluating the Energy Performance of Office Buildings in the Mediterranean Coastal Cities

This paper examines the thermal comfort conditions during summer and winter in an existing office building in an urban context. It investigates and correlates the results obtained from a questionnaire survey, conducted during summer and winter, with the two comfort models – for mechanically ventilated spaces and non-mechanically ventilated ones - in order to determine the most appropriate one for the energy performance evaluation of the office buildings in the coastal Mediterranean region. The study is carried out within the framework of the Urban Europe project Smart Urban Isle and it specifically refers to the Cyprus case study. The project considers the bioclimatic design of the buildings and of their urban environment, as well as potential energy management systems, in order to define and evaluate urban isles as a basic unit of energy measurement for Smart Cities. The Cyprus case study focuses on the impact of the thermal comfort Standards on the energy performance evaluation of the buildings and it promotes the sustainable and energy efficient design by selecting the most appropriate Standard to assess the thermal comfort for occupants.

Benchmarking by convex non-parametric least squares with application on the energy performance of office buildings

Regression analysis can be used to develop benchmarking systems for the energy performance of office buildings. A linear regression model can be developed using ordinary least squares (OLS) regression analysis to normalize the factors that affect the energy consumption performance of office buildings and develop the benchmarking model. Poor model fit and the assumption of linearity of OLS are the limitations in developing a reliable benchmarking model. In this study, we introduce and discuss the use of convex non-parametric least squares (CNLS) to develop a benchmarking model using the resulting hyperplanes. CNLS is advantageous in that (i) it is a non-parametric regression method, (ii) does not specify the functional form a priori, and (iii) is used to estimate monotonic increasing and convex functions. The resulting benchmarking model can be enhanced with a good model fit using the three advantages. An illustrative application to office buildings is also provided.

Experimental Characterization and Energy Performances of Multiple Glazing Units with Integrated Shading Devices

Modern architecture is characterized by the use of large glazed surfaces. New technologies ensure thermal insulation by multiple glazing units so that, maintaining good solar gains, highly glazed buildings can achieve good energy performance during the heating season. More complicated is the management of the energy performance during the cooling season due to high permeability to solar radiation. External shading devices are a suitable solution but they are often neglected for functional and aesthetic reasons. Solar protection devices can be, however, introduced in the air gap of multiple glazing units, providing solar protection without interfering with the building envelope. Solar and thermal properties of several solution of glazing units with in-gap shading devices were measured with advanced experimental set-up, to be compared with conventional systems. Numerical analyses were also performed to estimate the impact of this technology on the energy performance of office buildings.