Systematic approach for the life cycle multi-objective optimization of buildings combining objective reduction and surrogate modeling

Carreras, Joan; Pozo, Carlos; Boer, Dieter; Guillén‐Gosálbez, Gonzalo; Ruiz‐Femenia, Rubén; Jiménez, Laureano

doi:10.1016/j.enbuild.2016.07.062

Cited by 40 publications

(21 citation statements)

References 48 publications

(55 reference statements)

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“…Introducing additional parameters, constraints, and value choices will lead to more complex models. Carreras et al [47] showed how multiobjective optimisation can be used as a tool to study trade-off solutions, using nonlinear programming to identify redundant environmental metrics. The approach allows a simplification of multicriteria problems, reducing the computational time to identify the best options.…”

Section: Methodsmentioning

confidence: 99%

From Zero Emission Buildings (ZEB) to Zero Emission Neighbourhoods (ZEN): A Mapping Review of Algorithm-Based LCA

2018

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Abstract:The building industry is responsible for approximately 40% of energy consumption and 36% of greenhouse gas emissions in the European Union (EU). The most efficient way of reducing a building's environmental impact is addressing it in the design stage. Here, design freedom is the greatest, but uncertainty is high and there is a nearly limitless number of design options. Based on experiences with zero emission buildings (ZEB) and zero emission neighbourhoods (ZEN), a mapping review has been conducted to analyse how parametric life cycle assessment (LCA) and algorithms have been used to address neighbourhoods, buildings, and construction materials. Results have identified a general gap of knowledge regarding the use of parametric LCA models for decision-support purposes, demonstrated by the substantial focus on analytical methods compared to procedural methods. Implications for the evolution from ZEB to ZEN are twofold: (i) an integrated approach with multiple tools and methods is required, and (ii) further development of algorithms in the tool are needed to address complexity, sensitivity, and uncertainty. This study is expected to foster the development of algorithmic approaches to improve the ZEB tool as a decision-support tool. Further research should address the key questions of when and how.

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Section: Methodsmentioning

confidence: 99%

From Zero Emission Buildings (ZEB) to Zero Emission Neighbourhoods (ZEN): A Mapping Review of Algorithm-Based LCA

2018

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“…Although GAs do not guarantee finding the global optimum, they have become advanced optimization tool for a wide range of problems. GAs were further applied in a number of the papers quoted in the introduction of this paper [2,5,14,15,[29][30][31][32][33]35,36,38,[40][41][42].…”

Section: Optimization Algorithmmentioning

confidence: 99%

“…The optimization of the insulation thickness of a house considering both economic and environmental concerns is presented by Carreras et al [36]. The authors proposed a systematic framework for the design of buildings that combines a rigorous objective reduction method with a surrogate optimization model.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Variable Optimization of Building Thermal Design Using Genetic Algorithms

Ferdyn-Grygierek

Grygierek

2017

Energies

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Abstract:The building sector is one of the largest energy consumers in the world, comprising about 40% of the total energy consumption in numerous countries. Early design decisions have a significant impact on the energy performance of buildings. The paper presents the multi-variable optimization of the selected design parameters in a single-family building in temperate climate conditions. The influence of four types of windows, their size, building orientation, insulation of external wall, roof and ground floor and infiltration on the life cycle costs (LCC) is analyzed. Optimal selection of the design parameters is carried out using genetic algorithms by coupling the building performance simulation program EnergyPlus with optimization environment. The simulations were conducted for seven optimization cases. The analysis is performed for two variants of a building with heating and cooling systems and with a heating system only. Depending on the analyzed case, the life cycle costs decreased from 7% to 34% LCC value of the reference building. In the case of temperate climate, the building optimization (in terms of heat demand only) substantially reduces the heating costs, yet the summer thermal comfort conditions deteriorate significantly.

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“…A hybrid genetic algorithm and artificial neural net-works was used for the optimization. The optimization of the insulation thickness of a house considering both economic and environmental (eco-indicator 99 methodology) concerns is presented by Carreras et al [33]. The authors proposed a systematic framework for the design of buildings that combines a rigorous objective reduction method with a surrogate optimization model.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of the Envelope of Building with Natural Ventilation

Grygierek

Ferdyn-Grygierek

2018

Energies

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Abstract:A properly designed house should provide occupants with the high level of thermal comfort at low energy demand. On many occasions investors choose to add additional insulation to the buildings to reduce heat demand. This may lead to overheating of the building without a cooling system in summer periods (these prevail in Poland). Additionally, it affects the deterioration of thermal comfort, which can only be improved by increasing ventilation. The paper presents the multi-objective optimization of the selected design parameters in a single-family building in temperate climate conditions. The influence of four types of windows, their size, building orientation, insulation of external wall, roof and ground floor and infiltration on the life cycle costs and thermal comfort is analyzed for the building without cooling. Infiltration changes during the simulation and is controlled by a special controller. Its task is to imitate the behavior of occupants in changing the supply airflow. Optimal selection of the design parameters is carried out using Non-dominated Sorting Genetic Algorithm II (NSGA-II) by coupling the building performance simulation program EnergyPlus with optimization environment. For the single-family house, optimal values of design variables for three different criteria are presented.

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Systematic approach for the life cycle multi-objective optimization of buildings combining objective reduction and surrogate modeling

Cited by 40 publications

References 48 publications

From Zero Emission Buildings (ZEB) to Zero Emission Neighbourhoods (ZEN): A Mapping Review of Algorithm-Based LCA

From Zero Emission Buildings (ZEB) to Zero Emission Neighbourhoods (ZEN): A Mapping Review of Algorithm-Based LCA

Multi-Variable Optimization of Building Thermal Design Using Genetic Algorithms

Multi-Objective Optimization of the Envelope of Building with Natural Ventilation

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