Machine learning and numerical simulations for electrical, thermodynamic, and mechanical assessment of modified solar thermoelectric generators

Alobaid, Mohammad; Maduabuchi, Chika; Albaker, Abdullah; Alnami, Hashim; Alkhedher, Mohammad; Chen, Wei‐Hsin

doi:10.1016/j.applthermaleng.2022.119706

Cited by 8 publications

(2 citation statements)

References 87 publications

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“…This includes establishing standardized protocols for data acquisition and sharing, potentially through collaborative efforts among research institutions and industry stakeholders. Additionally, efforts should be directed towards creating simulation datasets [188] that can supplement the lack of real-world data, enabling researchers to explore and refine machine learning models.…”

Section: Discussionmentioning

confidence: 99%

Latest Advancements in Solar Photovoltaic-Thermoelectric Conversion Technologies: Thermal Energy Storage Using Phase Change Materials, Machine Learning, and 4E Analyses

Alghamdi,

Maduabuchi,

Okoli

et al. 2024

International Journal of Energy Research

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In recent times, the significance of renewable energy generation has increased and photovoltaic-thermoelectric (PV-TE) technologies have emerged as a promising solution. However, the incorporation of these technologies still faces difficulties in energy storage and optimization. This review paper addresses these challenges by providing a comprehensive overview of the latest advancements in PV-TE technologies. The paper emphasizes the integration of phase change materials (PCMs) for thermal energy storage, also buttressing the use of encapsulated PCM for thermal storage and efficiency, and the use of hybrid PCM to enhance overall performance. Furthermore, reviews on the use of machine learning techniques for efficient optimization and the integration of thermoelectric modules into tandem perovskite silicon solar cells have been comprehensively analyzed. The advancements in photovoltaic-thermoelectric systems, as reviewed in this article, signify significant progress in attaining sustainable and effective energy production and storage. This review comprehensively addresses the 4Es, underlining their importance. It not only consolidates recent developments but also charts a path for future research in the field of PV-TE technologies, offering precise insights to guide upcoming studies and innovations.

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Section: Discussionmentioning

confidence: 99%

Latest Advancements in Solar Photovoltaic-Thermoelectric Conversion Technologies: Thermal Energy Storage Using Phase Change Materials, Machine Learning, and 4E Analyses

Alghamdi,

Maduabuchi,

Okoli

et al. 2024

International Journal of Energy Research

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show abstract

“…Nevertheless, nanostructured TE materials proved better performance in inorganic bulk materials, [ 13b,46,102 ] and novel TE leg architectures (cascaded, segmented, and asymmetrical) are gaining ground. [ 103 ] Multi‐stage thermoelectric legs; in fact, enable a more efficient utilization of the inherent thermal gradient along the TE leg. This is achieved by segmenting various materials with optimal performance in different temperature ranges or by incorporating a midplane that separates the electrical circuits along the legs and minimizes heat loss.…”

Section: Discussionmentioning

confidence: 99%

Solar Thermoelectricity for Power Generation

Ayachi

Yoon

2023

Advanced Energy Materials

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Thermoelectric materials convert waste heat into electricity, making sustainable power generation possible when a temperature gradient is applied. Solar radiation is one potential abundant and eco‐friendly heat source for this application, where one side of the thermoelectric device is heated by incident sunlight, while the other side is kept at a cooler temperature. This is known as solar thermoelectric generation. Various thermoelectric materials are used for different solar thermoelectric applications, and different methods are explored to enhance the temperature gradient across the material. Solar optical concentrators, thermal and selective absorbers, and other tools are proposed to improve the performance of solar thermoelectrics. Despite continuous research and development, experimental solar thermoelectric efficiencies remain below 10%, and theoretical efficiencies do not surpass 20%. In this review, the different designs of solar thermoelectric generators are examined within the context of thermoelectric elements, optical concentrators, solar absorbers, and other techniques to enhance their performance. Last, an overview of the current state of solar thermoelectrics is provided, areas for improvement are suggested, and the future of these devices is predicted.

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Bayesian neural networks for solar power forecasts in advanced thermoelectric systems

Alghamdi,

Maduabuchi,

Okoli

et al. 2024

Case Studies in Thermal Engineering

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Machine learning and numerical simulations for electrical, thermodynamic, and mechanical assessment of modified solar thermoelectric generators

Cited by 8 publications

References 87 publications

Latest Advancements in Solar Photovoltaic-Thermoelectric Conversion Technologies: Thermal Energy Storage Using Phase Change Materials, Machine Learning, and 4E Analyses

Latest Advancements in Solar Photovoltaic-Thermoelectric Conversion Technologies: Thermal Energy Storage Using Phase Change Materials, Machine Learning, and 4E Analyses

Solar Thermoelectricity for Power Generation

Bayesian neural networks for solar power forecasts in advanced thermoelectric systems

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