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A computational method for optimal design of the multi-tower heliostat field considering heliostats interactions

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  • Piroozmand, Pasha
  • Boroushaki, Mehrdad

Abstract

In multi-tower heliostat fields, although heliostats are capable of aiming at different receivers during the day, due to different orientations, neighboring heliostats might affect shading and blocking efficiency of each other reciprocally. In the proposed method of this paper, considering the mentioned effects and based on a group decision-making approach, each heliostat chooses the best receiver thus ensuring the highest possible instantaneous efficiency of the field. As a case study, this method is applied for the optimal design of a multi-tower field. Then, the field performance is simulated in a case where heliostats make decisions individually without considering the interactions. Finally, these results are compared with separated single tower fields' energy performance. Results of the case study show that, due to the high dependency on shading and blocking factor, the annual efficiency of the multi-tower field without considering the interactions is only slightly higher than the two separated single tower fields. However, using the proposed method, the optical performance of the multi-tower field improves and the annual efficiency of 54.58% is reachable, which is 0.21% higher than the case without considering the interactions and 0.26% higher than the separated single tower fields.

Suggested Citation

  • Piroozmand, Pasha & Boroushaki, Mehrdad, 2016. "A computational method for optimal design of the multi-tower heliostat field considering heliostats interactions," Energy, Elsevier, vol. 106(C), pages 240-252.
    • Handle: RePEc:eee:energy:v:106:y:2016:i:c:p:240-252
    DOI: 10.1016/j.energy.2016.03.049
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    12. Wang, Jianxing & Duan, Liqiang & Yang, Yongping, 2018. "An improvement crossover operation method in genetic algorithm and spatial optimization of heliostat field," Energy, Elsevier, vol. 155(C), pages 15-28.
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