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<p>The paper presents the method of optimal design of the building envelope. The influence of four types of windows, their size, building orientation, insulation of external walls, ceiling to unheated attic and ground floor on the life cycle costs in a single-family building in Polish climate conditions is analyzed. The optimization procedure is developed by means of the coupling between MATLAB and EnergyPlus. The results using three metaheuristic methods: genetic algorithms, particle swarm optimization, and algorithm based on teaching and learning are compared. The analyses have shown the possibility of reducing the life cycle costs through the optimal selection of the building structure. The high initial investment (above the required standard) pays off in the long run when using a building.</p>
</abstract>

The paper presents the method of optimal design of the building envelope. The influence of four types of windows, their size, building orientation, insulation of external walls, ceiling to unheated attic and ground floor on the life cycle costs in a single-family building in Polish climate conditions is analyzed. The optimization procedure is developed by means of the coupling between MATLAB and EnergyPlus. The results using three metaheuristic methods: genetic algorithms, particle swarm optimization, and algorithm based on teaching and learning are compared. The analyses have shown the possibility of reducing the life cycle costs through the optimal selection of the building structure. The high initial investment (above the required standard) pays off in the long run when using a building.

MULTI-VARIABLE OPTIMIZATION MODELS FOR BUILDING ENVELOPE DESIGN USING ENERGYPLUS SIMULATION AND METAHEURISTIC ALGORITHMS

Architecture, Civil Engineering, Environment

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The paper presents the method of optimal design of the building envelope. The influence of four types of windows, their size, building orientation, insulation...

MULTI-VARIABLE OPTIMIZATION MODELS FOR BUILDING ENVELOPE DESIGN USING ENERGYPLUS SIMULATION AND METAHEURISTIC ALGORITHMS

Article Category: review

Online veröffentlicht: 06. Aug. 2019

Seitenbereich: 81 - 90

Eingereicht: 18. Juli 2018

Akzeptiert: 26. Apr. 2019

DOI: https://doi.org/10.21307/acee-2019-025

Schlüsselwörter
Genetic algorithm, Particle swarm optimizer, Teaching-learning-based optimization, Energy consumption, Building simulation, Building envelope.

© 2019 Krzysztof GRYGIEREK et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

MULTI-VARIABLE OPTIMIZATION MODELS FOR BUILDING ENVELOPE DESIGN USING ENERGYPLUS SIMULATION AND METAHEURISTIC ALGORITHMS

Article Category: review

Online veröffentlicht: 06. Aug. 2019

Seitenbereich: 81 - 90

Eingereicht: 18. Juli 2018

Akzeptiert: 26. Apr. 2019

DOI: https://doi.org/10.21307/acee-2019-025

SchlüsselwörterGenetic algorithm, Particle swarm optimizer, Teaching-learning-based optimization, Energy consumption, Building simulation, Building envelope.

© 2019 Krzysztof GRYGIEREK et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Genetic algorithm, Particle swarm optimizer, Teaching-learning-based optimization, Energy consumption, Building simulation, Building envelope.