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Optimized Mirror Cleaning Strategies in PTC Plants Reducing the Water Consumption and the Levelized Cost of Cleaning

机译:PTC植物优化镜面清洁策略降低了耗水量和清洁的平稳成本

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Soiling reduces the optical efficiency of the reflectors in a CSP plant and thus has a negative effect on the plant power output and LCOE. To mitigate this effect, regular cleaning should be performed which in turn increases the operation cost and consumes large amounts of water. In this study, potential improved cleaning strategies were tested through detailed dynamic simulation with an attempt to realize the relation between the cleaning water consumption and the specific cost of cleaning as well as to identify the optimum cleaning strategy for a specific site answering the question when and which collector should be cleaned. The aim of the study is to evaluate different cleaning strategies through a CSP performance model which is able to simulate the behavior of a CSP plant as close as possible to the real conditions. For this reason, spatiotemporal distribution of cleanliness in the solar field and individual loop simulation were taken into account in order to consider the effect of the non-homogenous cleanliness on the outlet temperature of the solar field. Additionally, the cleaning processes have been modelled based on the characteristics of ECILIMP cleaning trucks obtained from several on-site and laboratory scale tests. The simulation results show that the proposed cleaning strategy with variable threshold can reduce the cleaning water consumption by up to 19% and reduce the levelized cost of cleaning by 25% without any negative effect on the plant performance.
机译:污染降低了CSP工厂中反射器的光学效率,因此对植物电源输出和LCoE具有负面影响。为了减轻这种效果,应进行定期清洁,从而增加操作成本并消耗大量的水。在这项研究中,通过详细的动态模拟测试了潜在的改进的清洁策略,并试图实现清洁用水量与清洁成本之间的关系以及确定特定网站的最佳清洁策略回答问题应该清洁哪个收集器。该研究的目的是通过CSP性能模型来评估不同的清洁策略,该模型能够模拟CSP工厂尽可能接近真实条件的行为。因此,考虑了太阳能场和各个环形模拟中的清洁度的时空分布,以考虑非均匀清洁对太阳能场出口温度的影响。另外,清洁过程已经基于从几个现场和实验室测量测试获得的ecilimp清洁卡车的特性进行了建模。仿真结果表明,具有可变阈值的提出的清洁策略可以将清洁用水量降低至多19%,并将清洁成本降低25%,对植物性能没有任何负面影响。

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