Comparing reduction of building cooling load through green roofs and green walls by EnergyPlus simulations

Dahanayake, Kalani C.; Chow, Cheuk Lun

doi:10.1007/s12273-017-0415-7

Cited by 49 publications

(25 citation statements)

References 43 publications

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“…VGSs not only improve the aesthetics and biodiversity of urban environments, but also enhance the energy efficiency and sustainability of buildings, especially via energy saving through heat insulation and UHI mitigation [1][2][3][4]. The vertical greening of building envelopes can reduce canopy, wall and ambient temperatures through shading effects [5][6][7][8], the insulating capacity of plants and substrates [6,9,10] and evapotranspiration [7,11].…”

Section: Introductionmentioning

confidence: 99%

Effect of plant traits and substrate moisture on the thermal performance of different plant species in vertical greenery systems

Pan

Wei

Lai

et al. 2020

Building and Environment

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Section: Introductionmentioning

confidence: 99%

Effect of plant traits and substrate moisture on the thermal performance of different plant species in vertical greenery systems

Pan

Wei

Lai

et al. 2020

Building and Environment

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“…Nos estudos sobre o revestimento vegetal nas construções, pesquisas sobre telhados verdes são bem mais frequentes, em decorrência da maior utilização e difusão desta técnica, enquanto os jardins verticais compreendem um sistema com pesquisa ainda incipiente (COSTA, 2011;MATHEUS et al, 2016;DAHANAYAKE;CHOW, 2018). Tal tema faz-se relevante, uma vez que estudos apontam que o uso de vegetação nas fachadas constitui uma solução vantajosa.…”

Section: Sistemas De Vegetação Na Envoltória Da Edificaçãounclassified

Influência de paredes verdes no desempenho térmico de habitações sociais

Sousa

Souza

Gomes

2020

PARC Pesq. em Arquit. e Constr.

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A utilização da vegetação como elemento de fachada ainda compreende uma prática bastante incipiente, mas tem se popularizado devido à promessa de melhoria no desempenho térmico das edificações, além de representar uma alternativa de ampliação da biodiversidade no ambiente urbano. Neste trabalho investiga-se a influência das paredes verdes, no contexto climático brasileiro, sobre o desempenho térmico de edifícios habitacionais de interesse social. Como metodologia, utiliza-se a simulação do comportamento termoenergético de um edifício habitacional multifamiliar, por meio do programa EnergyPlus, incluindo-se o modelo HAMT que leva em conta o processo de transferência de umidade através da envoltória, para três zonas bioclimáticas previstas na norma NBR 15.220-2005, clima extremo para inverno (ZB1), clima extremo de verão (ZB8) e para um clima considerado como intermediário (ZB3). Os resultados obtidos demonstram uma diferença na temperatura interna dos ambientes, decorrente dos dois arranjos de fachada analisados: com e sem vegetação. O uso da parede verde proporcionou uma redução na temperatura interna de até 2,8 °C no verão e um aumento de até 1,4 °C no inverno. Observa-se que a vegetação na fachada ajudou a manter a temperatura interna mais baixa durante o dia e amena durante a noite. Logo, as paredes verdes podem representar uma solução sustentável e de baixo custo a ser implantada às edificações, visando melhorar seu desempenho térmico.

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“…EnergyPlus, which is an energy simulation software, is used to simulate different scenarios to generate a large number of reliable data sets for training the ANN model and estimating the energy consumption. 24 In the actual control of intelligent building systems, the controller performance directly affects the regulation of environmental parameters. In the feedback control, the controller aims to minimize the difference between the set and observed values.…”

Section: Wired Communication Systems Include Bacnetmentioning

confidence: 99%

Application of neural network to building environmental prediction and control

Zhang

Liu

et al. 2019

Building Services Engineering Research and Technology

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Energy conservation, environmental protection, and intelligence are topics of interest in intelligent buildings. However, the energy requirement of various electrical equipment in intelligent buildings increases energy consumption. This study presents a neural network-based prediction and control system for the regulation of building environmental parameters. Neural network-based soft sensing technology can detect building environmental parameters through few sensors. The proposed system control algorithm can realize the adaptive adjustment of environmental parameters by using a neural network proportional–integral–derivative controller. Zigbee wireless communication is adopted as the information transmission medium to realize the environmental parameter measurement and network control. The soft sensing technique combined with Zigbee communication technology can effectively reduce energy consumption. The central control system analyzes the data coming from the network and regulates the environmental parameter through lifting temperature, ventilation, and switching curtains by using the neural network proportional–integral–derivative algorithm. The regulation of environmental parameters reduces unnecessary energy consumption. Finally, the effectiveness of the system is verified through simulations. Practical applications: This work reports an energy saving scheme. The building communication system constructed by ZigBee can reduce energy consumption and can be easily expanded. The soft sensing technique based on artificial neural network can predict temperatures by using few sensors. The neural network proportional–integral–derivative control algorithm has good performance in the regulation of environmental parameters for a time-varying system. Building energy consumption can be reduced by conducting these measures.

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Comparing reduction of building cooling load through green roofs and green walls by EnergyPlus simulations

Cited by 49 publications

References 43 publications

Effect of plant traits and substrate moisture on the thermal performance of different plant species in vertical greenery systems

Effect of plant traits and substrate moisture on the thermal performance of different plant species in vertical greenery systems

Influência de paredes verdes no desempenho térmico de habitações sociais

Application of neural network to building environmental prediction and control

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