Intelligent building control systems for thermal comfort and energy-efficiency: A systematic review of artificial intelligence-assisted techniques

Merabet, Ghezlane Halhoul; Essaaidi, Mohamed; Haddou, Mohamed Ben; Qolomany, Basheer; Qadir, Junaid; Anan, Muhammad; Al‐Fuqaha, Ala; Abid, Mohamed Riduan; Benhaddou, Driss

doi:10.1016/j.rser.2021.110969

Cited by 145 publications

(69 citation statements)

References 139 publications

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“…Another open problem worth mentioning is the application of artificial intelligence techniques to model the different components in Figure 7. One may notice that recent surveys dedicated to this topic either focus on specific equipment [212,213] or they have a more general scope [214,215] but do not explain how to use mathematical models to decrease the complexity of the calculation with datadriven methods. To conclude, this work has reviewed the mathematical models of building physics and popular technologies, and has presented assemblable models.…”

Section: Discussionmentioning

confidence: 99%

A Review of Mathematical Models of Building Physics and Energy Technologies for Environmentally Friendly Integrated Energy Management Systems

2022

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The Energy Management System (EMS) is an efficient technique to monitor, control and enhance the building performance. In the state-of-the-art, building performance analysis is separated into building simulation and control management: this may cause inaccuracies and extra operating time. Thus, a coherent framework to integrate building physics with various energy technologies and energy control management methods is highly required. This framework should be formed by simplified but accurate models of building physics and building energy technologies, and should allow for the selection of proper control strategies according to the control objectives and scenarios. Therefore, this paper reviews the fundamental mathematical modeling and control strategies to create such a framework. The mathematical models of (i) building physics and (ii) popular building energy technologies (renewable energy systems, common heating and cooling energy systems and energy distribution systems) are first presented. Then, it is shown how the collected mathematical models can be linked. Merging with two frequently used EMS strategies, namely rule-based and model predictive controls, is discussed. This work provides an extendable map to model and control buildings and intends to be a foundation for building researchers, designers and engineers.

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Section: Discussionmentioning

confidence: 99%

A Review of Mathematical Models of Building Physics and Energy Technologies for Environmentally Friendly Integrated Energy Management Systems

2022

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“…ANNs are strongly linked with energy management (EM), while RL (Mason and Grijalva, 2019) and Genetic algorithm (Luo et al, 2020) are investigated in fewer research. Thermal comfort is another topic of EM (Halhoul Merabet et al, 2021).…”

Section: Fig 5: Main Research Interests On Ai In Aeco (Co-occurrence ...mentioning

confidence: 99%

Artificial intelligence in construction asset management: a review of present status, challenges and future opportunities

Rampini¹,

Cecconi²

2022

ITcon

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The built environment is responsible for roughly 40% of global greenhouse emissions, making the sector a crucial factor for climate change and sustainability. Meanwhile, other sectors (like manufacturing) adopted Artificial Intelligence (AI) to solve complex, non-linear problems to reduce waste, inefficiency, and pollution. Therefore, many research efforts in the Architecture, Engineering, and Construction community have recently tried introducing AI into building asset management (AM) processes. Since AM encompasses a broad set of disciplines, an overview of several AI applications, current research gaps, and trends is needed. In this context, this study conducted the first state-of-the-art research on AI for building asset management. A total of 578 papers were analyzed with bibliometric tools to identify prominent institutions, topics, and journals. The quantitative analysis helped determine the most researched areas of AM and which AI techniques are applied. The areas were furtherly investigated by reading in-depth the 83 most relevant studies selected by screening the articles’ abstracts identified in the bibliometric analysis. The results reveal many applications for Energy Management, Condition assessment, Risk management, and Project management areas. Finally, the literature review identified three main trends that can be a reference point for future studies made by practitioners or researchers: Digital Twin, Generative Adversarial Networks (with synthetic images) for data augmentation, and Deep Reinforcement Learning.

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“…The worsening energy crisis calls for revolutionary energy-saving strategies. − Windows, as one of the main channels for heat and light exchange between buildings and vehicles, serve as a key energy platform for highly efficient energy utilization. − Adjusting the transmission, reflection, or absorption spectrum of sunlight under the conditions of external stimulation or artificial active control has attracted extensive attention. − The exploration of smart windows that enable significantly reduced energy loss is at the core of this great prospective. − In this context, thermochromic materials are emerging as ideal building blocks of smart windows because they can dynamically modulate the transmittance of solar radiation without external energy inputs and greenhouse gas emissions. − It is worth noting that vanadium dioxide (VO 2 ) holds a grand promise for thermochromic smart windows because of its notable optical variation in the near-infrared (NIR) region from transmitting to reflecting upon the semiconductor-to-metal phase transition. − Nevertheless, due to its intrinsic physical properties, the application of VO 2 nanoparticles (NPs) to energy-saving smart windows still faces a series of challenges, such as undesired/noncustomizable color, instability, biosafety, and integration technologies. − Various approaches have been applied to address these issues, including doping, antireflection coating, biomimetic structuring, compositing, photonic structuring, kirigami-inspired structuring, and so forth. However, the trade-off relationship among the three major indexes luminous transmission ( T lum ), solar modulation (Δ T sol ), and phase transition temperature (τ c ) is observed in most cases, which is extraordinarily challenging to balance. ,, …”

Section: Introductionmentioning

confidence: 99%

Superhydrophobic VO₂ Nanoparticle/PDMS Composite Films as Thermochromic, Anti-icing, and Self-Cleaning Coatings

Liu

Sun²,

Jin

et al. 2022

ACS Appl. Nano Mater.

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Windows are considered as one of the least energy-efficient features of the building envelope. Reducing the associated energy consumption while maintaining comfortable conditions and reasonable transparency is still a serious challenge, which requires intelligent system design. Herein, three hierarchical nano/microstructured films based on vanadium dioxide and polydimethylsiloxane (VO2/PDMS) are fabricated. To our surprise, the striped nano/microstructures give rise to superhydrophobic and oleophobic properties, the contact angles for both water and several organic liquids (e.g., benzyl alcohol, formamide, and ethanolamine) are larger than 150°. A number of desired properties for smart windows are simultaneously endowed for the film, including thermochromic, anti-icing, self-cleaning, and anti-corrosion. Compared with the ordinary glass, the icing delay time of the superhydrophobic surface increases almost eight times at −15 °C, and the ice adhesion force reduces to 24.7 kPa. Moreover, the VO2 nanoparticle/PDMS composite film displays remarkable durability against various mechanical and chemical attacks. The unique features render the stripe VO2/PDMS film with great potential to be developed as a generation energy-efficient material and to promote further research of nanomaterials for smart thermal control applications.

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Intelligent building control systems for thermal comfort and energy-efficiency: A systematic review of artificial intelligence-assisted techniques

Cited by 145 publications

References 139 publications

A Review of Mathematical Models of Building Physics and Energy Technologies for Environmentally Friendly Integrated Energy Management Systems

A Review of Mathematical Models of Building Physics and Energy Technologies for Environmentally Friendly Integrated Energy Management Systems

Artificial intelligence in construction asset management: a review of present status, challenges and future opportunities

Superhydrophobic VO₂ Nanoparticle/PDMS Composite Films as Thermochromic, Anti-icing, and Self-Cleaning Coatings

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Intelligent building control systems for thermal comfort and energy-efficiency: A systematic review of artificial intelligence-assisted techniques

Cited by 145 publications

References 139 publications

A Review of Mathematical Models of Building Physics and Energy Technologies for Environmentally Friendly Integrated Energy Management Systems

A Review of Mathematical Models of Building Physics and Energy Technologies for Environmentally Friendly Integrated Energy Management Systems

Artificial intelligence in construction asset management: a review of present status, challenges and future opportunities

Superhydrophobic VO2 Nanoparticle/PDMS Composite Films as Thermochromic, Anti-icing, and Self-Cleaning Coatings

Contact Info

Product

Resources

About

Superhydrophobic VO₂ Nanoparticle/PDMS Composite Films as Thermochromic, Anti-icing, and Self-Cleaning Coatings