Thermal and Economic Analyses of Different Glazing Systems for a Commercial Building in Various Moroccan Climates

Lachheb, Amine; Allouhi, A.; Saadani, Rachid; Jamil, A.; Rahmoune, Miloud

doi:10.1615/interjenercleanenv.2020034790

Cited by 4 publications

(1 citation statement)

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“…Kontes et al (2013) proposed a stochastic optimization algorithm to maximize the utility of renewable energy proportion within the HVAC system. Lachheb et al (2020) studied parametric models to investigate the impact of HVAC utility on the glazing size in various regions. Promising results from the data-driven approaches have demonstrated the effectiveness and robustness in modeling and optimizing the HVAC systems.…”

Section: Introductionmentioning

confidence: 99%

Green Building Energy Cost Optimization With Deep Belief Network and Firefly Algorithm

et al. 2021

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In this research, we propose a multi-objective optimization framework to minimize the energy cost while maintain the indoor air quality. The proposed framework is consisted with two stages: predictive modeling stage and multi-objective optimization stage. In the first stage, artificial neural networks are applied to predict the energy utility in real-time. In the second stage, an optimization algorithm namely firefly algorithm is utilized to reduce the energy cost while maintaining the required IAQ conditions. Industrial data collected from a commercial building in central business district in Chengdu, China is utilized in this study. The results produced by the optimization framework show that this strategy reduces energy cost by optimizing operations within the HAVC system.

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Section: Introductionmentioning

confidence: 99%