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A Review: Simple Tools for Evaluating the Energy Performance in Early Design Stages


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To make performance-based design decisions, an energy performance evaluation should be integrated into the design process. Simple tools can provide easy and rapid performance analysis without requiring detailed information as inputs. This paper presents a review of ten simple tools regarding their application, characteristics, modeling/calculation features and outputs. The key discussion focuses on the establishment of the necessary inputs. This study intends to clarify the effective approach of establishing those necessary inputs and find out the obstacles in this process. Note that building properties (BP) templates can extensively simplify the setup of construction data, internal load data and conditioning data. The lack of a method to efficiently establish energy setting parameters is recognized as the obstacle in the process of BP data setup. Reusing Building Information Model (BIM) data of past well-designed projects is expected to be a good approach to overcome that obstacle.
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Procedia Engineering 146 ( 2016 ) 32 39
1877-7058 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
Peer-review under responsibility of the organizing committee of CCHVAC 2015
doi: 10.1016/j.proeng.2016.06.349
Available online at
8th International Cold Climate HVAC 2015 Conference, CCHVAC 2015
A review: simple tools for evaluating the energy performance in
early design stages
Liwei Wena,
, Kyosuke Hiyamaa
aFaculty of Engineering, Yamaguchi University, 2-16-1, Tokiwadai, Ube-shi, Yamaguchi, 755-8611, Japan
To make performance-based design decisions, an energy performance evaluation should be integrated into the design process.
Simple tools can provide easy and rapid performance analysis without requiring detailed information as inputs. This paper presents
a review of ten simple tools regarding their application, characteristics, modeling/calculation features and outputs. The key
discussion focuses on the establishment of the necessary inputs. This study intends to clarify the effective approach of establishing
those necessary inputs and find out the obstacles in this process. Note that building properties (BP) templates can extensively
simplify the setup of construction data, internal load data and conditioning data. The lack of a method to efficiently establish energy
setting parameters is recognized as the obstacle in the process of BP data setup. Reusing Building Information Model (BIM) data
of past well-designed projects is expected to be a good approach to overcome that obstacle.
© 2016 The Authors. Published by Elsevier Ltd.
Peer-review under responsibility of the organizing committee of CCHVAC 2015.
Keywords: Type your keywords here, separated by semicolons ;
1. Introduction
Increasing requirements of sustainability has prompted architects and engineers to pay more attention to the energy
performance of their design. The design decisions, such as building form, orientation, fenestration, and construction
materials, made in the early design stages have the most impact on the building energy performance [1]. This impact
was also confirmed by the simulation in which intelligent facades was integrated into the design process for hot
* Corresponding author. Tel.: +81-0836-85-9730; fax: +81-0836-85-9730.
E-mail address:
© 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
Peer-review under responsibility of the organizing committee of CCHVAC 2015
Liwei Wen and Kyosuke Hiyama / Procedia Engineering 146 ( 2016 ) 32 – 39
climates [2]. Thus, a preliminary energy performance evaluation must be performed during the early design stages to
enable architects to make performance-based design decisions. American Institute of Architects [3] published the
design guideline that also emphasizes the importance of energy performance prediction in the early design stages
(named as Design Performance Modeling (DPM)). This guideline summarized DPM as being a less complex and less
time consuming approach that allows for rapid exploration of many design parameters. Furthermore, the analysis
results of DPM are not overly specific, generally providing architects with a range of energy performance that are
dependent on the design decision variations. Thus, suitable tools are needed to implement the energy performance
evaluation in the early design stages.
In the past few years, building performance simulation (BPS) has experienced a rapid development. The US
Department of Energy [4] created the building energy software directory, which lists more than 400 BPS. Crawley [5]
compared the characteristics and capacities of twenty widely applied BPS. Most of the BPS were found to focus on
predicting the whole-building energy performance after the design. However, some studies indicated that performing
BPS was still beneficial to support early decision making. For example, BPS was utilized to assist in the generation of
the shape of the building with the minimum energy consumption [6]. The utilization of BPS can obtain an accurate
prediction results. However, a BPS usually requires a large number of inputs. Establishing those inputs for a BPS is
quite time consuming [7]. Another limitation of implementing a BPS in the early design stages is the requirement of
detailed information as input. Such detailed information can be acquired only in design development stages or later.
Note that the quality and reliability of inputs greatly affect the simulation results. Unreliable inputs may cause
questionable simulation results that produce incorrect information for decision making [8]. In addition, good
understanding of the thermal processes and the simulation tools is critical to perform a BPS. However, in early design
stages, the performers are usually not professional engineers but architects. These architects have limited knowledge
in this professional field. Thus, despite the rapid development in the application of BPS, architects still suffer from the
barriers of utilization and selection of such complex BPS [9].
Simplified energy performance prediction tools (simple tools) can provide easy and quick performance analysis,
thus assisting architects in considering design alternatives. Simple tools do not require much detailed information as
inputs. In combination with the characteristics of DPM mentioned above, simple tools are regarded as a very useful
approach to perform preliminary energy performance prediction and inform early design decisions. This paper presents
a review of ten simple tools for evaluating energy performance in the early design stages. The ten simple tools are Cf,
PAL*, ERED, WinSim, TEMMI/MCI3, FACES, BuildingCalc, CooLVent, DPV and EcoDesigner. The key
discussions focus on the necessary inputs of the ten simple tools. This study intends to clarify the effective measures
of establishing those necessary inputs and find out the obstacles in this process.
2. Overview of the ten tools
The ten simple tools reviewed in this paper can be divided into three categories: design index, simple analysis
program and BIM relevant program. Design index tools, including Cf, PAL* and ERED, utilize the performance about
envelope to indicate the approximate energy performance of the buildings. A simple analysis program usually exports
specific calculation results, such as thermal load, indoor air temperature and airflow rate. However, a simple analysis
program requires relatively more inputs. WinSim, TEMMI/MCI3, FACES, BuildingCalc and CooLVent are examples
of simple analysis programs. A BIM relevant program combined with BIM software can automatically generate the
energy model. Examples of BIM relevant programs are DPV and EcoDesigner.
2.1. Cf (shape coefficient)
Cf was designed as an indicator of the heating consumption for residential buildings in a rigorous climate [10]. Cf
is defined as the rate between the external envelope surface area and the inner volume of the building. The authors
performed the trend test on several theoretical buildings and determined that Cf was proportional to heating
consumption. Therefore, outdoor temperature is the largest driver for heating consumption of the residential building
in rigorous climate. However, there is no correlation between Cf and heating consumption in mildest and sunny climate.
34 Liwei Wen and Kyosuke Hiyama / Procedia Engineering 146 ( 2016 ) 32 – 39
2.2. PAL* (Perimeter Annual Load*)
Ministry of Land, Infrastructure, Transport and Tourism, Japan created PAL* to describe the thermal insulation
performance of the building envelope for non-residential buildings [11]. PAL* is defined as the rate between the total
annual load of the perimeter zone and the area of the perimeter zone of the building. In Japan, the energy convention
plan must be proposed for non-residential buildings whose area exceeds 2000 m2. PAL* is adopted as an index to
quantify the energy conservation level. The standard value of PAL* was set according to the application and location
of the project. The calculated PAL* for the target building should be smaller than the standard value.
2.3. ERED (Envelop-Related Energy Demand)
The design indicator ERED was developed to indicate the energy consumption of residential buildings [12]. The
limitation of Cf, i.e., it has no correlation with the energy performance in a mildest climate, is addressed by ERED. It
is the sum of the heat transmission through the envelope and the solar gains through the windows calculated using
some simple formulas and definitions. This indicator is combined with the envelope shape, envelope materials and
window areas.
2.4. WinSim
To facilitate the selection of windows, WinSim was developed to quickly and easily evaluate the thermal
performance of windows [13]. An electric analogy model (two-node) is adopted in this program. The calculation
object is limited to a simple one-zone room. The outputs of WinSim are the annual energy consumption, the amount
of transmitted solar energy and total number hours when the building is under overheated conditions.
This commercial program TEMMI/MCI3 is used to perform thermal analysis for non-residential buildings [14].
This program intends to design building envelope with the minimum thermal load. This program uses an electric
analogy model (three-node) for performing the thermal analysis. The outputs include thermal load and indoor air
temperature. To provide feedback to architects, the program performs an automatic comparison among envelope
design alternatives on the basis of the thermal load.
2.6. FACES (Forecasts of Air-Conditioning System’s Energy, Environment, and Economical Performance by
FACES is a simplified simulation program for choosing a suitable heat source system [15]. The program couples
the dynamic thermal load calculation and the HVAC system simulation. Automatic design algorithms of the building
model and the HVAC system are introduced into FACES. The program is equipped with five building models and
thirteen heat source systems for selection. The outputs are the peak load, the annual thermal load, the amount of energy
consumption, the amount of carbon emissions and the cost.
2.7. BuildingCalc
BuildingCalc was developed to estimate the thermal load and the indoor environment for non-residential buildings
[16]. The program is based on WinSim. Thus, the model and calculation objects are the same as those of WinSim.
The solar gains through the windows are thoroughly described. Beyond the thermal load, the program can also
examine the effects of shading, venting and mechanical ventilation. The program exports the thermal load, the indoor
air temperature, the hours of overheating. It can also export the value of Predicted Percentage of Dissatisfied (PPD)
and Predicted Mean Vote (PMV).
Liwei Wen and Kyosuke Hiyama / Procedia Engineering 146 ( 2016 ) 32 – 39
2.8. CoolVent
CoolVent was developed to evaluate the performance of natural ventilation [17]. A multi-zone coupled thermal
and airflow model is used to predict the zone temperature and the direction, the temperature and the rate of airflow.
The program can perform both transient (24-hour period) and steady calculations. Architects can understand how
some design parameters affect the internal temperature and airflow and confirm the measurable effects from the design
of natural ventilation.
2.9. DPV (Design Performance Viewer)
DPV was combined with the BIM software (Revit from AUTODESK) to access the geometry inputs [18]. DPV
mainly focuses on the heating demand of buildings. A mathematical model was used to perform energy and exergy
analysis. The concept of exergy is defined as the potential of an energy source dispersing from heat generation to
emission into the room. The analysis results of DPV are the energy balance and exergy balance of selected heat chain.
DPV can assist architects in making a balance among building form, building material and technical systems in the
early design stages.
2.10. EcoDesigner
GRAPHISOFT developed EcoDesigner as an add-on application operating inside of ArchiCAD [19]. Multiple
thermal models can be automatically generated in the design environment. EcoDesigner can evaluate key design
decisions, such as materials, glazing and ventilation. The output of EcoDesigner are the yearly energy consumption,
the carbon emissions and the monthly energy balance.
3. Discussion of necessary inputs of ten tools
To promote the utilization of simple tools in design practice, the necessary inputs and whether those necessary
inputs can be easily acquired or not must be considered. Table 1 presents the necessary inputs of the ten simple tools
considered in this study. FACES, DPV and EcoDesigner can also consider the HVAC system to further calculate
specific performance of buildings. However, the use of the thermal load as the objective function is focused on in this
study. Thus, only the inputs related to the thermal load are listed for these three tools. The collected necessary inputs
are divided into three large categories: weather data, building geometry data and building properties (BP) data. BP
data are defined as the non-geometrical inputs required by energy models [20].
Both simple analysis programs and BIM relevant programs use some approaches based on the hourly climate data
to represent the standardized annual climate. Thus, users need to know only the location of their project. ERED is the
only design index tool requiring simple climate inputs. These required inputs can be easily obtained from the “epw”
climate file format that is made freely available to the public by the DOE [21]. Regarding geometry data, a simple
method with the capacity of converting 2D building models to the representative “shoebox” thermal models has been
described [22]. In addition, the “simulation domain model” is able to exchange data between the 3D BIM software
and the simulation domain and makes it possible to directly acquire building information to reduce the efforts required
to handle geometry inputs [23]. The huge progress of typical meteorological years and the BIM technique extensively
simplify the setup of weather and geometry inputs. Hence, an effective solution to set up BP data is urgently required.
BP data can be further divided into general data, construction data, internal load data and conditioning data. General
data represent the building application and site information, including terrain and surrounding building. A majority of
construction data are used to describe the building material properties, which are specified as the properties of opaque
envelope and glazing. The rest of the construction data are used to describe the dimensions of the openings. The
dimensions of the openings are expressed as the window-to-wall ratio (WWR). Internal load data are composed of the
internal heat gain density and their corresponding schedules. Conditioning data are composed of two groups. One
group comprises the indoor environment controlling data to maintain the comfortable level of occupants. The other
group comprises the passive design strategies, such as ventilation and shading devices. General data can be completely
obtained from the client demand, even during the very early design stages. Besides general data, a part of internal load
36 Liwei Wen and Kyosuke Hiyama / Procedia Engineering 146 ( 2016 ) 32 – 39
Table 1. Necessary inputs for ten tools
Design index
Simple analysis program
BIM relevant
Weather data
Outdoor temp.
Wind speed
Wind direction
Solar radiation
geometry data
Number of floors
Floor dimensions
Interior wall length
Floor areas
Exterior wall areas
Internal wall areas
Roof areas
Ground floor areas
Window areas
Atrium dimensions
Building properties data
Terrain information
Construction data
Exterior wall
Roof properties
floor properties
Interior wall
Thermal capacity of
Glazing properties
Frame properties
Exterior wall /roof
Internal load data
Occupation density
Occupation schedule
Equipment density
Equipment schedule
Lighting density
Lighting schedule
Total internal load
Liwei Wen and Kyosuke Hiyama / Procedia Engineering 146 ( 2016 ) 32 – 39
Table 1. Necessary inputs for ten tools (continued)
Design index
Simple analysis program
BIM relevant
Building properties data
Conditioning data
Heating set points
Cooling set points
Heating season
Cooling season
Over temp. limit
Initial building
Artificial lighting
Ventilation type
Window opening
setting temp.
Window opening
ventilation rates
Natural ventilation
Infiltration rate
Shading device
1.Solar heat gain coefficient of the windows with shading device on
2.Users need to define this values when performing a steady calculation
Fig. 1. Reliable sources of building properties data
data and indoor environment controlling data within the conditioning data also depend on the client demand. The
establishment of remnant BP data can be greatly simplified by BP templates [20]. The BP templates proposed for BPS
are defined as a comprehensive database of the thermal zone attribution data. The utilization of BP templates can
38 Liwei Wen and Kyosuke Hiyama / Procedia Engineering 146 ( 2016 ) 32 – 39
greatly reduce the time consumption and the risk of error. The predefined data in BP templates mainly originate from
the reference design guideline and experience. Building material properties data in construction data and the remnant
indoor environment controlling data in conditioning data can be precisely obtained through the BP templates. It is
explained that such data in BP templates are from the design guideline. All of the BP data mentioned above can be
acquired from reliable sources, as shown in Figure 1.
However some data without reliable sources also exists. Those data are generally determined by experiences, such
as WWR, belonging to construction data, and shading device and ventilation strategies, belonging to conditioning
data. The lack of measure to efficiently and rapidly establish those data is recognized as the obstacle in the process of
BP data setup. The target percentage glazing, shade depth, target percentage skylight and conceptual construction-
mass glazing were reported to be very sensitive to the predicted results and should be carefully given in the early
design stages. Such parameters are called energy setting parameters [24]. Energy setting parameters cannot be solely
determined by uniform standards or design guidelines. The issues involved with energy setting parameters are
highlighted by the example of setting up the WWR. The ANSI/ASHRAE/IESNAI Standard 90.1-2010 recommends
the maximum value of WWR should be 40%. However, the analysis results of case studies indicated that the optimal
WWR was greatly influenced by the building design conditions, such as the building scale, location, and operation
mode (daylighting and natural ventilation). For a building with a relatively large floor area and space depth, the largest
WWR was found to be the best solution [25]. This result contradicts the suggested value by ASHARE. As a
consequence, an effective measure must be developed to determine energy setting parameters that cannot be
determined by a regular standard. One feasible method is to reuse the BIM data of past well-designed projects to
generate optimal default values during the early design stages [26].It is critical to find the link between a new project
and past projects for such data inherit. This link refers to not only the building configuration but also the operation
mode. Therefore, the exploration of design conditions sensitive to energy setting parameters is necessary to generate
robust default values. The authors plan to perform relevant studies regarding this issue in the future.
4. Conclusions
To inform early design decisions, we reviewed ten simple tools for energy performance evaluation in the early
design stages. The application, characteristics, modeling/calculation features and outputs of ten simple tools were
examined. The necessary inputs for implementing these ten simple tools were summarized. The setup of BP data was
sufficiently discussed. The general data and a part of the internal load data mainly depended on client demand.
Furthermore, the application of BP templates was highlighted as a means to extensively simplify the setup of
construction data, internal load data and conditioning data. However, some data, such as WWR, shading devices, and
ventilation strategies cannot be determined by a regular standards or design guidelines. The lack of measures to
efficiently and rapidly establish those data is recognized to be an obstacle in the BP data setup process. Reusing BIM
data of past well-designed projects is considered to be an effective approach. To optimize such inherited data, it is
critical to find the link between a new project and past projects. This link refers to not only the building configuration
but also the operation mode. Therefore, the exploration of design conditions sensitive to energy setting parameters is
necessary to generate robust default values.
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... Maile et al. [194] described a selection of five energy simulation engines, stating their functionalities and discussing their respective usage over the different life-cycle stages of a building. Finally, Wen and Hiyama [195] reviewed ten programs, focusing on their simplicity and ease of application. These tools generally consist of two components: a graphical user interface (GUI) and a simulation engine [85]. ...
... Regarding software features, both Wen et al. [195] and Stundon et al. [198] identified that "whole building's energy performance prediction throughout a building's life cycle" is the most popular feature among practitioners. However, as highlighted by multiple authors [21,22,58,90,96,193,, these tools offer numerous other capabilities. ...
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Full-text available
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... Some studies compare the single features of Building Performance Simulation Software. Two good examples are the ones written by Crawley, Hand, Kummert & Griffith (2008) in which 20 BPSS were compared, or the review of 10 tools done by Wen & Hiyama (2016). In these researches, aspects such as input data or capabilities to compute specific simulations were compared and evaluated. ...
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By taking Cairo as a case study, this research builds up on the lessons learned from local and vernacular architecture. Wants to find and test design strategies and passive systems that work in Cairene’s climate. While focusing on the architecture of informal apartment blocks, it seeks to what extent it can meet the end user’s thermal comfort expectations while being energy and environmentally sound. Furthermore, linking the meta topics of vernacular architecture, thermal comfort, and energy consumption brings new insights into the discussion about sustainable urban development in hot and dry climates. With a theoretical and empirical study, the characteristics, and the thermal and energy performance of three Cairene buildings are discussed and compared. An optimisation study of an informal building is conducted. Different strategies, systems, and relative options to increase comfort and decrease energy demand are explored. In addition, some of the wellperforming options are further analysed, and through a costbenefit and a future climate scenario analysis, the consequences of their implementation are discussed. Several sensitivity studies are carried out to find which systems and strategies might affect the end user’s comfort of the informal building. Furthermore, by digitally re-locating the analysed informal building into different urban scenarios, the elements that influence the building performance are further analysed with the help of parametric analysis. This last point leads to a series of recommendations that might be useful when designing a new building within this context or when retrofitting an existing one. Furthermore, limitations and outlook for further research are discussed. A general summary of learnings is made in the closing remarks, and an answer to the research is given. A reflection about the research process and its outcomes is carried out, and the connection to the overarching topics of adaptation and mitigation in Egypt is made.
... Improving the design cycle to deliver high-performing buildings goes beyond modelling capabilities and user expectations [9][10][11][12]. For example, Bambardekar & Poerschke [13] noted the gap between the availability of simulation software and the limited guidance to use such software at early design stages. ...
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Since early-stage decisions have the largest impact on climate related emissions, if modelling is to help deliver zero carbon designs, tools are needed that can be used by those involved at this stage. By contrast, tools that require a detailed description of the building or a specialist have less usefulness at this point in the design cycle. So, just how simple can models be (mathematically and interface-wise), to give meaningful answers to decisions such as the shape of the building and the glazing ratio? The ideal tool would be pedagogical and leave the user with knowledge that they could apply even earlier to the next project. In this work we present ZEBRA, a highly simplified, quick-to-use, model for scoping zero-carbon buildings. The model only requires approximately 33 inputs, no training, considers embodied emissions and renewables and leaves the user upskilled on zero carbon design. The predictions from 5 very low energy buildings placed into 559 climates obtained by this new model are compared to the leading model for high-performing buildings. The average difference was 0.9 kWh·m⁻²·a⁻¹ (SD = 0.6). The mean time taken to model a building by someone not previously exposed to ZEBRA was 35 min (SD = 8), and 17 min (SD = 3) on second use. Therefore, ZEBRA is highly accurate when compared to the best-in-class tool and can be used quickly by the uninitiated. Hence ZEBRA has the potential to be highly useful as a first-pass tool whilst simultaneously rapidly upskilling the industry.
... However, despite the advancement in new techniques and integration between the design and performance (for example, [153], [154]), self-sufficient tools are lacking that effectively aid in developing deep-retrofits. Generally, a combination of building modelling tool, energy performance simulation tool and optimisation tool is required for assessment of retrofit packages [155], [156]. ...
The emerging trends for deep-retrofit of existing buildings in Europe require formulation of strategies for nearly zero-energy buildings (nZEBs) and achieving benchmarks as outlined in the Energy Performance of Buildings Directive (EPBD) recast. The fundamental process of retrofitting to an explicit high performance (both energy and comfort) necessitates the development of robust and diverse methodologies to be used during the early-stages of planning in retrofit projects. The construction sector lacks the extensive use of such methods for early decision-making that are essential to accelerate building renovation in Europe. Therefore, considering the need to upgrade existing buildings to nZEB, the thesis aims at developing decision-making support for deep-retrofits. This research presents the application of combined (i) research techniques, (ii) audit and assessment methods, (iii) building simulation, and (iv) optimisation strategies investigated on an existing building field-study that shall support the decision-making in retrofitting existing buildings to low-energy and comfortable buildings. The overall research methodology incorporated a preliminary scoping study, including literature review and stakeholder analysis, followed by a detailed field-study, building simulation and optimisation for deep-retrofit analysis and solutions. The scoping study was designed to assess the gaps in theory through literature review and practice using surveys, a workshop and focused interviews investigating experience, knowledge, expectation, and needs of retrofit industry stakeholders in Ireland. The results of this scoping study informed the overall methodology for research in this thesis. A systematic field-study was conducted on a partially-retrofitted university building (built during 1970s) in Ireland. The different building performance metrics for energy and comfort were examined for the existing building and their optimisation opportunities were identified. Furthermore, an indoor environmental quality (IEQ) assessment was carried out using standards-based procedures and practices along with detailed energy audits and occupant surveys. The metrics of thermal, visual and acoustic comfort, together with indoor air quality (IAQ), were analysed for occupant satisfaction. This formed the basis for further investigation focusing on achieving nearly zero-energy performance with improved IEQ and led to the identification of proposed retrofit measures. The further investigation involved the development of a whole-building energy simulation models using the field-study data. A novel multi-stage automated-calibration methodology was developed to calibrate the simulation model using genetic algorithm (GA). The methodology combined a rigorous uncertainty analysis of simulation input parameters using the Morris method. The model was calibrated and validated with the energy and environmental reference datasets from the field-study meeting the acceptance criteria outlined in the standards. Furthermore, the impact of several proposed retrofit measures on energy, comfort, and cost were evaluated using the calibrated model, through multi-objective optimisation (MOO) (Pareto fronts), to explore deep-retrofit solution packages. The main objectives of the MOO were primary energy consumption (PEC), discomfort hours (DH) and net present value (NPV) of life cycle-costs (LCC). An additional analysis of IAQ was also conducted, which provided added benefits that were also taken into consideration in the proposed deep-retrofit solution packages. To validate the effectiveness of these solutions, single-step and staged-retrofit approaches were examined for their feasibility in achieving cost-optimal nZEB performance. The overall work concludes with different retrofit approaches for critical assessment tied to the main research methodology that supports the decision-making for non-domestic retrofits from the energy, cost and IEQ perspective. Multi-objective optimisation ensured robust model calibration and analysis of most optimal solutions for the decision making of deep-retrofit packages based on selected objectives. Findings of this research may (i) benefit the non-domestic deep-retrofit projects (and their stakeholders) to develop a systematic approach and processes to achieve nZEBs, (ii) provide evidence that deep-retrofit of non-domestic buildings can significantly reduce their energy consumption, (iii) strengthen and align the focus of retrofit industry on improving IEQ together with energy efficiency, (iii) inform the local legislation into setting up the nZEB benchmarks for existing buildings performance and, (iv) add to the primary case study database on non-domestic buildings outlining the deep-retrofit impact.
... In addition, there are some research materials that are indirectly related to this review. They focus on dynamic simulation models for sustainable building design [26,27], indispensable simulation tools in the design process [28][29][30][31], and computer-based optimization methods [32][33][34]. ...
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As most countries have widespread and growing concerns about the sustainable development of society, the requirement to continuously reduce energy consumption poses challenges for the architecture, engineering and construction (AEC) industry. Performance-oriented architectural design and optimization, as a novel design philosophy and comprehensive evolution technology, has been accepted by architects, engineers, and stakeholders for a period of time. Performance in the context of architecture is a widely discussed definition that has long shown a correlation with visual and cultural attributes. Shifting the paradigm of sustainable development while ensuring that the function and aesthetics of the building are not overlooked has been the focus of public attention. Considering the core design elements that affect energy conservation and style performance, the design and optimization of building envelopes, form, and shading systems were selected as research materials. From the perspective of epistemology and methodology, a systematic review of 99 papers was conducted to promulgate the latest development status of energy-efficiency design. This paper manifests a detailed analysis of the design patterns, research features, optimization objectives, and techniques of current approaches. The review found that performance-oriented design optimization can benefit the entire industry from the heuristic knowledge base and the expansion of the design space while maintaining sustainability. In contrast, challenges such as tools, skills, collaboration frameworks, and calibration models are highlighted.
... This would require the SDGs to be introduced in the early design phases of projects [78]. The IDP, which has become common practice for high-performance and green buildings, offers the opportunity for such early integration while fostering constructive collaboration between the different stakeholders of building projects [26,79,80]. ...
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Building designers are struggling to deeply integrate the 2030 Agenda and its Sustainable Development Goals (SDGs) in projects. The review of the literature revealed that the available research is focused on linking the current practices, including sustainable building practices, with the SDGs. This has, in turn, limited the development of novel approaches as well as new building design methodologies that specifically aim at attaining the agenda's targets. To help building design teams achieve the meaningful integration of the agenda's five Ps, this paper proposes two analytical mapping tools which can be used during the integrated design process to track the integration of SDGs in the building projects, and to analyze the building design approaches and visions in reference to the topics of the goals. The research uses a case study for an energy-positive building in Quebec to test the proposed tools. The analysis focuses on the integration of 8 of 17 SDGs, discusses the specific building features which were used to achieve this integration, and analyzes the team's design visions regarding the goals. The results reveal that in the case studied, the integration of the 8 SDGs moves beyond the current standards by mostly applying design approaches which are future-driven and focused on products and technologies. This research provides important practical tools that can inform building practices in the private and the public sector and contributes to the theory and practice of sustainable building design. It also supports the current effort towards the implementation and localization of the SDGs.
... For example, ZEBO [4] designers used a simulation benchmark to represent high-density apartments in Egyptian cities. Recommendations of the Egyptian Residential Energy Standard will be used to supplement the energy model once the building's site location and type are selected. L. Wen and K. Hiyama [58] investigated the input conditions of 10 simulation tools, which are divided into three categories: design index, simple analysis program, and BIM relevant program. They found the largest obstacle to constructing an energy model database is the absence of effective energy parameters. ...
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Early simulation work in the decision-making stage faces several challenges, including, for example, rapid changes of design, input variable uncertainties, and the lack of design information, although early design work represents a large percentage of energy saving potential. The availability of simulation tools for early design stages can help the architect analyze more alternatives. In this study, the existing simulation tools were explored and classified into three categories: simulation plugins based on the design software, geometry user interfaces for a simulation engine, and self-governing simulation tools. Each category’s typical tools were illustrated with their use, and a uniform standard comparison was conducted to screen tools that are available in the early design stages. The future trends of simulation tools are discussed in the second part: building databases based on existing knowledge, uncertainty and sensitivity analyses, and optimization. Time-consuming simulation is a problem in the use of simulation tools in early design stages. Advanced techniques were developed in this part for fast computing, i.e., cloud computing, parallel computing, meta-models, and more statistical methods. This paper illustrates the practical application of particular simulation tools in the early design stage, presents their limitations, and discusses decision-support tools for specific building design activities.
... It has also been shown that one user can make a variation in simulation results up to 40% among different tools. Moreover, the lack of the effective establishment of energy setting parameters is known as the obstacle in the process of building performance data setup in some of the available tools [90]. Nevertheless, available software and tools play a vital role in building performance simulation. ...
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This paper describes the evolution of the thermal network and its applications for making simplified thermal models of buildings by means of thermal resistances (R) and capacitances (C). In the literature, there are several modelling schemes for buildings. Here, we investigate the advantages, disadvantages, and improvements of thermal networks. The thermal network method has been used in different studies for calculating indoor air temperature and heating load, estimating model parameters, and studying building interactions with heating and cooling systems. This review paper conducts an investigation into the application, system identification, and structure of thermal networks compared to other tools. Within the framework of the thermal network method, we conclude with some new proposals for research in this field to expand the idea of the thermal network to other engineering and energy management fields.
The study outlines the state-of-art on interoperability between Building Information Modeling (BIM) and Building Performance Simulation (BPS). First, the paper organises the result of a Systematic Literature Review (SLR) on the topic into three main strategies to achieve interoperability: the scripting to automate the information transfer between BIM and BPS environments, the pipelines supported by current practices, and the MVD and IFC schema extension approach. Software applications, types of files involved, building features, life cycle phases and model geometry considered by the literature along with reported interoperability issues, are also analysed. Secondly, an expert review of grey literature focusing on EU funded projects, guidelines, reports, best practices and key initiatives on the field of BIM to BPS interoperability is presented. The study wraps up by reporting on six major research trends identified by the review and highlighting future developments. The results of the review seem to indicate that effective interoperability can be achieved with the definition of a commonly accepted strategy, integrating shared guidelines for modelling, a better inclusion of energy evaluations through the whole life cycle of a building and the upgrade of software application for the accurate production of information with open format exchange files.
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Applying data mining techniques on a database of BIM models could provide valuable insights in key design patterns implicitly present in these BIM models. The architectural designer would then be able to use previous data from existing building projects as default values in building performance simulation software for the early phases of building design. The author has proposed the method to minimize the magnitude of the variation in these default values in subsequent design stages. This approach maintains the accuracy of the simulation results in the initial stages of building design. In this study, a more convincing argument is presented to demonstrate the significance of the new method. The variation in the ideal default values for different building design conditions is assessed first. Next, the influence of each condition on these variations is investigated. The space depth is found to have a large impact on the ideal default value of the window to wall ratio. In addition, the presence or absence of lighting control and natural ventilation has a significant influence on the ideal default value. These effects can be used to identify the types of building conditions that should be considered to determine the ideal default values.
Conference Paper
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Developers of building simulation tools have been continuously improving their programs and adding new capabilities over the last thirty years. Time steps of less than an hour are now common and even necessary to properly simulate the complex interactions of building components and systems. For example, some control issues, such as daylighting, require much shorter time steps of minutes—more traditional hourly time steps have been shown to introduce errors as large as 40% in illumination calculations. Despite these increased capabilities, many simulation programs are still using the same limited set of hourly climatic/weather data they started with— temperature, humidity, wind speed and cloud cover or solar radiation. This often forces users to find or calculate missing weather data such as illuminance, solar radiation, and ground temperature from other sources or developers to calculate it within their program. In this paper, we describe a generalized weather data format developed for use with two energy simulation programs. We also compare the new format with previous data sets in use in the US and UK.
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There is a need for decision support tools that integrate energy simulation into early design of zero energy buildings in the architectural practice. Despite the proliferation of simulation programs in the last decade, there are no ready-to-use applications that cater specifically for the hot climates and their comfort conditions. Furthermore, the majority of existing tools focus on evaluating the design alternatives after the decision making, and largely overlook the issue of informing the design before the decision making. This paper presents energy-oriented software tool that both accommodates the Egyptian context and provides informative support that aims to facilitate decision making of zero energy buildings. A residential benchmark was established coupling sensitivity analysis modelling and energy simulation software (EnergyPlus) as a means of developing a decision support tool to allow designers to rapidly and flexibly assess the thermal comfort and energy performance of early design alternatives. Validation of the results generated by the tool and ability to support the decision making are presented in the context of a case study and usability testing.
The purpose of this study is to develop a new system that automatically generates default configurations for simulations during early phases of building design. The system is expected to facilitate front loading, which can contribute to making the building design process more efficient and consistent. The default configuration is generated based on an existing building database created by an architectural firm for each architectural program. The increase in the use of building information modeling (BIM) will allow for the compilation of a sufficient amount of data to utilize this system. The optimal default configuration changes its features automatically to match the objective functions employed by each architectural firm. Moreover, it can be used to create a generic building type, such as green buildings, based on a green building database. In this paper, a basic concept that can be used to produce a default configuration from existing building datasets was proposed. Using a case study, the similarity between the default configuration design and optimal design is illustrated. The study demonstrates the potential ability of this method to prevent designers from making careless mistakes with initial condition inputs and to eliminate the need to rework the simulation process, which facilitates front loading.
Multidisciplinary design optimization (MDO) has been identified as a potential means for integrating design and energy performance domains but has not been fully explored for the specific demands of early stage architectural design. In response a design framework, titled Evolutionary Energy Performance Feedback for Design (EEPFD), is developed to support early stage design decision-making by providing rapid iteration with performance feedback through parameterization, automation, and multi-objective optimization. This paper details the development and initial validation of EEPFD through two identified needs of early stage design: 1) the ability to accommodate formal variety and varying degrees of geometric complexity; and 2) the ability to provide improved performance feedback for multiple objective functions. Through experimental cases the research presents effective application of EEPFD for architectural design.
The envelope shape, the most salient design characteristic in a building, has significant influence on its energy performance. However, in the early design stages, when the envelope shape is defined, energy performance information is normally nonexistent, due to modeling for energy simulation being a time-consuming task, frequently overlooked at this phase. This paper presents a methodology to assist design decisions regarding the building envelope shape considering its implications on energy performance. Basically, this methodology involves a flexible design system, to generate alternative envelope shape designs, with integrated energy simulation, to calculate the energy demand of each design. Shape grammars are particularly suitable to encode architectural design systems, given their ability to encode compositional design principles. Their downside is the complexity in developing computer implementations. This methodology converts a grammar into a parametric design system and is illustrated with an application to the grammar for Frank Lloyd Wright's prairie houses.
The architectural design variables which most influence the energy performance of a building are the envelope materials, shape and window areas. As these start to be defined in the early design stages, designers require simple tools to obtain information about the energy performance of the building for the design variations being considered at this phase. The shape factor is one of those tools, but it fails to correlate with energy demand in the presence of important solar gains. This paper presents a new design indicator of energy performance for residential buildings, the Envelope-Related Energy Demand (ERED), which aims to overcome the shortcomings of the shape factor while maintaining a reasonable simplicity of use. The inputs to ERED are areas of envelope elements (floor, walls, roofs and windows), U-values of envelope materials, solar heat gain coefficients (SHGC) of windows and site related parameters, concerning temperature and solar irradiation. ERED was validated against detailed simulation results of 8000 hypothetical residential buildings, varying in envelope shape, window areas and materials. Results show that there is a strong correlation between ERED and simulated energy demand. These results confirm the adequacy of ERED to assist design decisions in early stages of the design process.
This work aims at relating the heating consumption of the buildings with their shape. This information is dedicated to the architects and engineers. At the beginning of the project, they need global information enabling them to find economical solutions as for energy consumption. First of all, a parameter that has been chosen to characterize the shape of the buildings is introduced. The selection of this coefficient is grounded on the necessary simplicity of its use by conceivers. Thus, the shape coefficient is defined as the ratio between the external skin surfaces and the inner volume of the building. Then, the sample of the studied buildings is described. Fourteen buildings have been chosen according to their varieties in shapes and their representativeness in current constructions. The calculation code used to evaluate the heating consumption is briefly described. This code operates the method of weighting factors. The method is quick and well adapted to the study as the 14 buildings are conceived from the same basic cell. The results show that the energetic consumption is inversely proportional to the compactness (weak shape coefficient) in case of cold severe and scarcely sunny winters. However, it can't be applied in case of mild climates, which leads to no recommendation of compactness.
A two-node model of a room has been implemented in a computer program, WinSim, developed for evaluation of thermal performance of windows in new buildings and in case of retrofitting. The program calculates the annual heating demand and the number of hours with indoor temperatures higher than a user defined limit. WinSim is characterised by the limited amount of required input data. Guidelines for calculation of the effective thermal capacity of the room are given, and results obtained with WinSim have been compared to results from an advanced building simulation program. Good agreement has been found between the two programs with respect to calculated annual heating demand and energy savings due to window exchange, and also the calculated number of hours with overtemperature is similar. Based on the limited examples used for the comparison, it can be concluded that WinSim is well suited for a quick but realistic evaluation of thermal performance of windows.