The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Thermal energy storage technologies for concentrated solar power – A review from a materials perspective
Abstract
Abstract To compete with conventional heat-to-power technologies, such as thermal power plants, Concentrated Solar Power (CSP) must meet the electricity demand round the clock even if the sun is not shining. Thermal energy storage (TES) is able to fulfil this need by storing heat, providing a continuous supply of heat over day and night for power generation. As a result, TES has been identified as a key enabling technology to increase the current level of solar energy utilisation, thus allowing CSP to become highly dispatchable. This article aims to review different TES technologies that have been investigated and deployed over the past two decades. The review will give a comprehensive overview of TES technologies investigated, demonstrated and/or deployed in CSP plants with a specific emphasis on TES materials perspective. A thorough analysis will also be given on the state-of-the-art of the CSP technologies including commercial development and research innovation. An attempt is also made to use the information gathered along this review to postulate future technology evolution of CSP plants in terms of CSP configurations, TES technologies and location of CSP plants, and to assess the current and future role of TES in CSP field.
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Cites
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Metadata
- Authors
- Palacios, A., Barreneche, C., Navarro, M. E., & Ding, Y.
- Venue
- Renewable Energy
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 156
- Pages
- 1244-1265
- ISSN
- 0960-1481 (ISSN-L)
- OpenAlex
- W2985341795
- Cited by
- 469
- References
- 54
- FWCI
- 6.75
- Type
- journal article
- Language
- en
- Open access
- closed
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- Palacios, A., Barreneche, C., Navarro, M. E., & Ding, Y. (2020). Thermal energy storage technologies for concentrated solar power – A review from a materials perspective. Renewable Energy. https://doi.org/10.1016/j.renene.2019.10.127
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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