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GPU-based Aim Point Optimization for Solar Tower Power Plants

Oberkirsch, Laurin and Maldonado Quinto, Daniel and Schwarzbözl, Peter and Hoffschmidt, Bernhard (2021) GPU-based Aim Point Optimization for Solar Tower Power Plants. Solar Energy. Elsevier. doi: 10.1016/j.solener.2020.11.053. ISSN 0038-092X.

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In solar tower power plants, aim point optimization is suitable to find aim point distributions resulting in intercept powers close to the theoretical maximum. However, the application in real time operation often faces the problem of long optimization duration. To counteract this issue, the convergence of an existing strategy, the ant colony optimization meta-heuristic, is enhanced. The raytracing is already replaced by pre-calculated flux maps of the individual heliostats in previous works to increase the optimization speed. In this work, the optimization is merged with a grouping strategy and implemented on a GPU to achieve further time reductions. Here, a k-means clustering algorithm performs the heliostats grouping. The use of groups reduces the solution space for the optimizer and additionally the amount of pre-calculated flux maps, so that the data fits in the global memory of the GPU. Over 100 billion flux values can be evaluated per second using this adapted approach. In this way, the algorithm finds suitable aim point distributions within a few seconds up to a minute. The achieved intercepts are 1 % to 4 % higher then those found by a single factor aiming strategy for the evaluated central receiver reference power plant. Moreover, the approach has proved its applicability in clouded environments that lead to spatially fluctuating solar radiation. There, a spillage reduction compared to the single factor aiming of 35 % is reached.

Item URL in elib:https://elib.dlr.de/189242/
Document Type:Article
Additional Information:Dieses Paper ist im Rahmen des Projekts HeliBo entstanden und wurde beim Journal für Solar Energy im Mai 2020 eingereicht und im November 2020 akzeptiert. Es ist nicht Open-Source.
Title:GPU-based Aim Point Optimization for Solar Tower Power Plants
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Oberkirsch, LaurinUNSPECIFIEDhttps://orcid.org/0000-0001-7018-3664UNSPECIFIED
Journal or Publication Title:Solar Energy
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
Keywords:Concentrating solar power, Solar tower power plant, Heliostat aiming, Aim point optimization, Cloud disturbance
HGF - Research field:Energy
HGF - Program:Materials and Technologies for the Energy Transition
HGF - Program Themes:High-Temperature Thermal Technologies
DLR - Research area:Energy
DLR - Program:E SW - Solar and Wind Energy
DLR - Research theme (Project):E - Smart Operation
Location: Köln-Porz
Institutes and Institutions:Institute of Solar Research > Solar Power Plant Technology
Deposited By: Oberkirsch, Laurin
Deposited On:28 Oct 2022 10:39
Last Modified:15 Nov 2022 09:56

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