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Optimization of dwelling design under current and future climates using evolutionary algorithms in EnergyPlus
Designers of low energy dwellings face many challenges in making best use of space, and providing day lit and pleasant spaces, while minimising heat loss and overall carbon emissions to meet various environmental and legislative targets. These also have to be achieved within financial, spatial and planning constraints. In other words, the design exercise is a multi-criteria optimization exercise. Usually this is done using experience through iterative design development, assisted by various software tools ranging from relatively simple models such as the Standard Assessment Procedure (SAP), to detailed thermal simulation. This paper describes the use of parametric simulations using EnergyPlus on a computer cluster to arrive at optimal solutions, for both current and future climates. The tool is applied to some modern house designs proposed for developments in the UK.
Optimization of dwelling design under current and future climates using evolutionary algorithms in EnergyPlus
Designers of low energy dwellings face many challenges in making best use of space, and providing day lit and pleasant spaces, while minimising heat loss and overall carbon emissions to meet various environmental and legislative targets. These also have to be achieved within financial, spatial and planning constraints. In other words, the design exercise is a multi-criteria optimization exercise. Usually this is done using experience through iterative design development, assisted by various software tools ranging from relatively simple models such as the Standard Assessment Procedure (SAP), to detailed thermal simulation. This paper describes the use of parametric simulations using EnergyPlus on a computer cluster to arrive at optimal solutions, for both current and future climates. The tool is applied to some modern house designs proposed for developments in the UK.
Optimization of dwelling design under current and future climates using evolutionary algorithms in EnergyPlus
Wright, Andrew J (author) / Korolija, Ivan (author) / Zhang, Yi (author)
2013-04-12
In: The 2013 CIBSE Technical Symposium. The Chartered Institution of Building Services Engineers (CIBSE): London,UK. (2013)
Paper
Electronic Resource
English
Simulation , energy , optimisation , house
DDC:
690
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