A new method for the design of the heliostat field layout for solar tower power plant

Wei, Xiudong; Lu, Zhenwu; Wang, Zhifeng; Yu, Weixing; Zhang, Hongxing; Yao, Zhihao

doi:10.1016/j.renene.2010.01.026

Cited by 121 publications

(30 citation statements)

References 7 publications

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“…The basic coordinate system and the incidence cosine calculation are, in general, common for all the codes [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. However, the model of the sun position may differ among the codes.…”

Section: General Coordinate System Incidence Cosine and Sun Positionmentioning

confidence: 99%

“…An analytical review of the former convolution codes can be found in [14], also including other Monte Carlo codes, such as SCT-HGM [25] (developed within the research project EU SIREC), and the more recent HFLD from the Chinese Academy of Sciences (CAS) [26,27] (published by 2010). More recent convolution codes not included in former reviews, such as CRS4-2 from the Italian CRS [28] and the MIT code [29], will be commented on later.…”

Section: Introductionmentioning

confidence: 99%

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A review of optimized design layouts for solar power tower plants with campo code

Collado

Guallar

2013

Renewable and Sustainable Energy Reviews

171

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a b s t r a c t Solar power tower (SPT) systems are viewed as one of the most promising technologies for producing solar electricity, in which direct solar radiation is reflected and concentrated by a field of giant mirrors (heliostats) onto a receiver placed at the top of a tower. However, the optimized design of a heliostat field is a rather complex problem because the annual performance of a heliostat is a function of not only the instants of time considered and its own position, but also the relative location of neighbouring heliostats, which cause shadows and blockings. A variety of procedures may be found in the open literature, although there is great lack of information on the details of an optimized layout. This review shows that these complex problems have partially led to the expansion of parabolic trough technologies in USA and Spain in spite of their lower thermodynamic efficiencies compared with solar tower power. As a modest support of SPT systems, the authors have presented elsewhere the abilities of a new code called campo for fast and accurate calculations of the shadowing and blocking factor for each and every heliostat. This work explores a review of the optimized heliostat field layouts yielded by campo. Campo commences the optimization search based on the densest layout, with the worst shadowing and blocking factor, but with good values for the other optical factors, and then progresses towards gradually expanded distributions. The search for maximum annual energy through campo results in a clear, steady and reproducible procedure. Finally, as an example of this new procedure, some options of optimized heliostat field layouts are reviewed using as input parameters the scarce open literature data on Gemasolar, the first solar power tower commercial plant with molten salt storage in the world.

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Section: General Coordinate System Incidence Cosine and Sun Positionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A review of optimized design layouts for solar power tower plants with campo code

Collado

Guallar

2013

Renewable and Sustainable Energy Reviews

171

View full text Add to dashboard Cite

show abstract

“…In addition, to place these heliostats with a higher overall optical efficiency, an optimised field layout design is needed. Wei et al [58] proposed a technique which they called ' YNES'to design the optimised field layout.…”

Section: Heliostat Field Collectorsmentioning

confidence: 99%

A review of solar collectors and thermal energy storage in solar thermal applications

2013

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Thermal applications are drawing increasing attention in the solar energy research field, due to their high performance in energy storage density and energy conversion efficiency. In these applications, solar collectors and thermal energy storage systems are the two core components. This paper focuses on the latest developments and advances in solar thermal applications, providing a review of solar collectors and thermal energy storage systems. Various types of solar collectors are reviewed and discussed, including both non-concentrating collectors (low temperature applications) and concentrating collectors (high temperature applications). These are studied in terms of optical optimisation, heat loss reduction, heat recuperation enhancement and different suntracking mechanisms. Various types of thermal energy storage systems are also reviewed and discussed, including sensible heat storage, latent heat storage, chemical storage and cascaded storage. They are studied in terms of design criteria, material selection and different heat transfer enhancement technologies. Last but not least, existing and future solar power stations are overviewed.

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“…In a solar tower power plant (STPP), solar energy is collected by the heliostat to produce steam to drive electrical generators. From the previous studies [3,7,8], it has found that the heliostat field contributes about 50% to the total cost and causes power losses by 40% in STPPs. For this reason, the design and optimization of the heliostat field layout are very important and the heliostat field remains an active research field.…”

Section: Introductionmentioning

confidence: 99%

Optimization of a Heliostat Field Layout on Annual Basis Using a Hybrid Algorithm Combining Particle Swarm Optimization Algorithm and Genetic Algorithm

Zhai

Yang

2017

Energies

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Of all the renewable power generation technologies, solar tower power system is expected to be the most promising technology that is capable of large-scale electricity production. However, the optimization of heliostat field layout is a complicated process, in which thousands of heliostats have to be considered for any heliostat field optimization process. Therefore, in this paper, in order to optimize the heliostat field to obtain the highest energy collected per unit cost (ECUC), a mathematical model of a heliostat field and a hybrid algorithm combining particle swarm optimization algorithm and genetic algorithm (PSO-GA) are coded in Matlab and the heliostat field in Lhasa is investigated as an example. The results show that, after optimization, the annual efficiency of the heliostat field increases by approximately six percentage points, and the ECUC increases from 12.50 MJ/USD to 12.97 MJ/USD, increased about 3.8%. Studies on the key parameters indicate that: for un-optimized filed, ECUC first peaks and then decline with the increase of the number of heliostats in the first row of the field (Nhel 1 ). By contrast, for optimized field, ECUC increases with Nhel 1 . What is more, for both the un-optimized and optimized field, ECUC increases with tower height and decreases with the cost of heliostat mirror collector.

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A new method for the design of the heliostat field layout for solar tower power plant

Cited by 121 publications

References 7 publications

A review of optimized design layouts for solar power tower plants with campo code

A review of optimized design layouts for solar power tower plants with campo code

A review of solar collectors and thermal energy storage in solar thermal applications

Optimization of a Heliostat Field Layout on Annual Basis Using a Hybrid Algorithm Combining Particle Swarm Optimization Algorithm and Genetic Algorithm

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