Investigation and properties of a novel composite bio-PCM to reduce summer energy consumptions in buildings of hot and dry climates

Boussaba, Lisa; Lefèbvre, Gilles; Makhlouf, Saïd; Grados, Arnaud; Royon, Laurent

doi:10.1016/j.solener.2020.11.060

Cited by 50 publications

(15 citation statements)

References 53 publications

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“…At present, in the process of studying the regional economy, we need to use the energy data of regional enterprises, such as energy consumption, energy demand analysis, and intelligent management of energy data. In order to further realize the intelligent classification of energy structure, we need to adopt multiple types of data analysis strategies; the BP neural network algorithm is a commonly used method in dealing with the coupling input analysis of regional economic energy consumption data [24]. The regional analysis process of energy consumption data in this stage is shown in Figure 1.…”

Section: Methodsmentioning

confidence: 99%

Application of Improved BP Neural Network in the Optimization of Regional Economic Energy Consumption Structure

2022

Wireless Communications and Mobile Computing

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At present, local regions have the problems of low optimization dimension and unbalanced supply side in the energy consumption structure in the process of economic development. Based on this, this paper studies the optimization method of the regional economic energy consumption structure based on big data and BP neural network analysis strategy and designs an intelligent extraction model of the regional economic energy consumption structure based on the BP neural network. According to the correlation and internal matching of energy consumption data involved in the process of economic development in different regions, the quantitative high-value analysis of regional economic energy consumption structure is realized, and the accuracy of the analysis results is analyzed by Newton Leibniz theory. The results show that the optimization model of regional economic energy consumption structure based on the BP neural network can effectively improve the application scope and data utilization of energy consumption structure, effectively complete the intelligent classification of energy consumption of different enterprises, and indirectly improve the energy utilization and matching efficiency of the regional economy.

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Section: Methodsmentioning

confidence: 99%

Application of Improved BP Neural Network in the Optimization of Regional Economic Energy Consumption Structure

2022

Wireless Communications and Mobile Computing

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“…Consequently, among the obtained polyols, LBP‐BO‐5 has the most interesting properties from the TES point of view, having both the highest melting point and the highest latent heat within the prepared LBPs. Although the highest latent heat obtained in this work with the prepared LBPs (53.7 J/g) is far from the 100 J/g achieved by other bio‐PCMs reported in the literature to date, 27–29 the possibility of tuning up the melting point and increase the storage capacity due to the versatile synthetic procedure of the LBPs opens the way to consider lignin‐based PCMs as very promising bio‐PCMs. The prepared PCM (LBP‐BO‐5) due to the low melting point (c.a.…”

Section: Resultsmentioning

confidence: 63%

Sustainable lignin‐based polyols as promising thermal energy storage materials

Perez-Arce

Serrano

Dauvergne

et al. 2021

J of Applied Polymer Sci

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Six lignin-based polyols (LBPs) have been prepared by cationic ring opening polymerization of an oxirane in the presence of an organosolv lignin in tetrahydrofuran (THF) as reaction media and co-monomer. The prepared LBPs have been characterized and tested for the first time as phase change materials (PCMs) for thermal energy storage (TES) at low temperature. It was found a strong influence of the LBPs composition on their performance to storage thermal energy. Thus, LBPs with higher THF wt% content and lower oxirane/THF mass ratio exhibit the highest latent heats. Furthermore, a clear inversely proportional trend between the oxirane/THF mass ratio and the melting temperatures of the prepared LBPs was noticed. Among the prepared LBPs, the highest obtained latent heat was 53.7 J/g demonstrating the potential application of lignin as feedstock for PCMs preparation. To the best of our knowledge, this is the first time that a biomass derived PCM based on lignin has been studied and considered for TES applications at low temperature. LBPs show energetic solid-liquid transitions that point out their promising potential as bio-PCMs. This work paves the way to introduce new bio-based PCMs from lignin in TES systems, for example, in a more sustainable construction sector. K E Y W O R D S bio-based phase change materials, lignin-based phase change materials, lignin upgrading, thermal energy storage, thermodynamic properties

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“…Then, they continued to prepared a biodegradable mineral plate made of recycled biodegradable non-cocoa vegetable fat, natural clay, and cellulose fiber, and proved in subsequent tests that the mineral plate had good thermal and chemical stability, and its strength met the requirements of construction. 166…”

Section: Sspcms In Buildingsmentioning

confidence: 99%

Construction strategies and thermal energy storage applications of shape‐stabilized phase change materials

Yan

Wang

et al. 2021

J of Applied Polymer Sci

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Phase change materials (PCMs) are usually used in latent thermal energy storage systems to address the mismatch between heat energy supply and demand, due to their high energy storage density, high-latent heat, and almost constant temperature during phase change process. However, the low-thermal conductivity of PCMs and severe leakage during phase change limit their practical applications. Thus, extensive efforts have been devoted to constructing shapestabilized PCMs (SSPCMs). In this review, recent advances of the construction strategies and thermal energy storage applications of SSPCMs are summarized. Especially, the microencapsulated PCMs, SSPCMs based on porous scaffolds, as well as their potential applications are highlighted. Finally, the future perspectives and remaining challenges in this research field are prospected.

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Investigation and properties of a novel composite bio-PCM to reduce summer energy consumptions in buildings of hot and dry climates

Cited by 50 publications

References 53 publications

Application of Improved BP Neural Network in the Optimization of Regional Economic Energy Consumption Structure

Application of Improved BP Neural Network in the Optimization of Regional Economic Energy Consumption Structure

Sustainable lignin‐based polyols as promising thermal energy storage materials

Construction strategies and thermal energy storage applications of shape‐stabilized phase change materials

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