A parallel Teaching–Learning-Based Optimization procedure for automatic heliostat aiming-Reference-Cited by-同舟云学术

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A parallel Teaching–Learning-Based Optimization procedure for automatic heliostat aiming

Published:2016-11-10 Issue:1 Volume:73 Page:591-606
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Cruz N. C.,Redondo J. L.,Álvarez J. D.,Berenguel M.,Ortigosa P. M.

Funder

Ministerio de Economía y Competitividad

Consejería de Economía, Innovación, Ciencia y Empleo, Junta de Andalucía

European Social Fund

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s11227-016-1914-5.pdf

Reference24 articles.

1. Alexopoulos S, Hoffschmidt B (2013) Concentrating receiver systems (solar power tower). In: Richter C et al (eds) Solar energy. Springer, New York. doi: 10.1007/978-1-4614-5806-7

2. Avila-Marin A, Fernandez-Reche J, Tellez F (2013) Evaluation of the potential of central receiver solar power plants: configuration, optimization and trends. Appl Energy 112:274–288

3. Behar O, Khellaf A, Mohammedi K (2013) A review of studies on central receiver solar thermal power plants. Renew Sustain Energy Rev 23:12–39

4. Belhomme B, Pitz-Paal R, Schwarzbözl P (2014) Optimization of heliostat aim point selection for central receiver systems based on the ant colony optimization metaheuristic. J Solar Energy Eng 136(1):011005

5. Besarati S, Goswami D (2014) A computationally efficient method for the design of the heliostat field for solar power tower plant. Renew Energy 69:226–232

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2. Real-Time Optimization of Heliostat Field Aiming Strategy via an Improved Swarm Intelligence Algorithm;Applied Sciences;2024-01-02

3. Real-Time Aiming Strategy Optimization of Heliostat Field of Solar Power Tower via a Modified PSO Algorithm(SPSO);2023 China Automation Congress (CAC);2023-11-17

4. Validation of a closed-loop aim point management system at the Jülich solar tower;Solar Energy;2023-11

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