Simulation-based decision support tool for early stages of zero-energy building design

Attia, Shady; Gratia, Elisabeth; Herde, André De; Hensen, Jlm Jan

doi:10.1016/j.enbuild.2012.01.028

Cited by 352 publications

(224 citation statements)

References 14 publications

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“…The goal of this work is to encourage, first, the utilisation of all possible energy-efficient strategies and, then, the use of renewable energy sources and technologies located on the building [19]. Attia et al [20] developed one of the only decision support building simulation tools that can be used as a proactive guide in the early design stages of residential net zero-energy building design. This tool is designed for a hot climate (Egypt) and allows for the sensitivity analysis of possible variations of nZEB design parameters and elements to inform the decision-making process by illustrating how these variations can affect comfort and energy performance.…”

Section: Zero-energy At the Building Scalementioning

confidence: 99%

A simplified framework to assess the feasibility of zero-energy at the neighbourhood/community scale

Marique

Reiter

2014

Energy and Buildings

134

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a b s t r a c t Zero-energy buildings (ZEBs) are attracting increasing interest internationally in policies aiming at a more sustainably built environment, the scientific literature and practical applications. Although "zero energy" can be considered at different scales (e.g., community, city), the most common approach adopts only the perspective of the individual building. Moreover, the feasibility of this objective is not really addressed, especially as far as the retrofitting of the existing building stock is concerned. Therefore, this paper aims first to investigate the opportunity to extend the "zero-energy building" concept to the neighbourhood scale by taking into account two main challenges: (1) the impact of urban form on energy needs and the on-site production of renewable energy and (2) the impact of location on transportation energy consumption. It proposes a simplified framework and a calculation method that is then applied to two representative case studies (one urban neighbourhood and one rural neighbourhood) to investigate the feasibility of zero-energy in existing neighbourhoods. The main parameters that act upon the energy balance are identified. The potential of "energy mutualisation" at the neighbourhood scale is highlighted. This paper thereby shows the potentialities of an integrated approach linking transportation and building energy consumptions.

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Section: Zero-energy At the Building Scalementioning

confidence: 99%

A simplified framework to assess the feasibility of zero-energy at the neighbourhood/community scale

Marique

Reiter

2014

Energy and Buildings

134

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“…The higher capabilities in calculating detailed outputs -such as heating and cooling sub-hourly loads profiles and indoor thermal hygrometric and visual comfort, imply more complex and detailed inputs (Attia et al 2012). As regards the weather data input, issues related to the development of weather data for BES have been widely investigated in the literature and Barnaby and Crawley (2011) discussed and presented the main aspects, contexts and problems related to their definition.…”

Section: Introductionmentioning

confidence: 99%

Analysis and improvement of the representativeness of EN ISO 15927-4 reference years for building energy simulation

Pernigotto

Prada

Gasparella

et al. 2013

Journal of Building Performance Simulation

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“…For example, Attia et al, 2012 [7] describe the implementation of a simulation-based decision support tool in the conceptual design of zero-energy buildings in order to assess thermal comfort and energy performance options. Elsewhere, Bayesian decision theory has been used to support multicriteria decision-making [8].…”

Section: Introductionmentioning

confidence: 99%

Multi-criteria decision making under uncertainty in building performance assessment

Hopfe

Augenbroe

Hensen

2013

Building and Environment

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134

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Multi-criteria decision making under uncertainty in building performance assessment. Building and Environment, 69, Additional Information:• This is the author's version of a work that was accepted for publication in Building and Environment. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published at: AbstractBuilding performance assessment is complex, as it has to respond to multiple criteria.Objectives originating from the demands that are put on energy consumption, acoustical performance, thermal occupant comfort, indoor air quality and many other issues must all be reconciled. An assessment requires the use of predictive models that involve numerous design and physical parameters as their inputs. Since these input parameters, as well as the models that operate on them, are not precisely known, it is imprudent to assume deterministic values for them. A more realistic approach is to introduce ranges of uncertainty in the parameters themselves, or in their derivation, from underlying approximations. In so doing, it is recognized that the outcome of a performance assessment is influenced by many sources of uncertainty.As a consequence of this approach the design process is informed by assessment outcomes that produce probability distributions of a target measure instead of its deterministic value. In practice this may lead to a "well informed" analysis but not necessarily to a straightforward, cost effective and efficient design process. This paper discusses how design decision making can be based on uncertainty assessments. A case study is described focusing on a discrete decision that involves a choice between two HVAC system designs. Analytical hierarchy process (AHP) including uncertainty information is used to arrive at a rational decision. In this approach, key performance indicators such as energy efficiency, thermal comfort and others are ranked according to their importance and preferences. This process enables a clear group consensus based choice of one of the two options. The research presents a viable means of collaboratively ranking complex design options based on stakeholder's preferences and considering the uncertainty involved in the designs. In so doing it provides important feedback to the design team.

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Simulation-based decision support tool for early stages of zero-energy building design

Cited by 352 publications

References 14 publications

A simplified framework to assess the feasibility of zero-energy at the neighbourhood/community scale

A simplified framework to assess the feasibility of zero-energy at the neighbourhood/community scale

Analysis and improvement of the representativeness of EN ISO 15927-4 reference years for building energy simulation

Multi-criteria decision making under uncertainty in building performance assessment

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