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Despite the large number of research studies about Solar Tower plants questions, remain on a wide range of topics including methods for the lifetime assessment of the receiver tubes under creep-fatigue damage. Most of the published works dealing with this task do not consider important aspects such as the impact of clouds passages, plastic deformations, or stress relaxation due to creep. In this study a methodology is proposed to assess the creep-fatigue lifetime of solar receivers based on real weather data. The presented approach requires as input the daily DNI profiles for the selected plant location which are used to assess the heat flux maps on the receiver. Then, the heat transfer phenomena occurring within the receiver are dynamically simulated in order to obtain the history of the temperature distributions on the receiver tubes. Lastly, the creep and fatigue damages accumulated during the operation are evaluated in each receiver point considering the effects of plastic deformations and stress relaxation. The proposed methodology is applied to a simple case study to estimate the creep and fatigue damages accumulated in a receiver flow path during a typical cloudy day. The results show that the fourth panel accumulates the maximum damage and the fatigue damage is negligible compared to the creep. [ABSTRACT FROM AUTHOR]

The reduction of energy production due to heliostat soiling causes generation losses and therefore reduces the contribution and competitiveness of CSP. The optimal cleaning plan for CSP plants must strike the proper balance between the cost for cleaning activities and revenue losses due to a reduced power production. However, uncertainty in future soiling rates, weather conditions, and electricity sale prices (e.g. due to electricity markets, uncertainty in future purchasing agreements) significantly complicate the cleaning optimization. To address these challenges, a bi-objective simulation- optimization approach is developed to optimize the cleaning policy to simultaneously minimize cleaning costs and expected generation losses in the presence of stochastic weather, dust. The outcome of the proposed approach is the optimal number of cleaning trucks and periodic cleaning schedule for non-dominating solutions (Pareto front), which may be used to study the sensitivity of the cleaning schedule to variations in electricity prices. The approach is applied to a case study for a CSP plant located in Woomera, South Australia. The results show that for electricity sale prices between 40-100 AUD/MWh, the optimal number of trucks is 3 and the total cleaning costs are sensitive to the number of trucks purchased, but not to the cleaning frequency. However, as electricity prices increase above 300 AUD/MWh, the total costs become quite sensitive to the cleaning frequency. Finally, a comparison of the simulation-optimization approach and a (simpler) deterministic optimization indicates that the latter approach is suitable for most practical electricity prices. [ABSTRACT FROM AUTHOR]

The components exposed to the highest temperature and heat fluxes in Solar Tower plants are the tubes of the panels composing the central receiver. Their structural integrity is weakened due to fatigue and creep phenomena, likely worsened by a corrosive environment, and their solar power harvesting performance suffers from diminished absorptance of their coating. This paper describes a 2D dynamic thermal model of the tubes of a central receiver, developed following an Object-Oriented modelling paradigm, and applies the model to assess the impact of degradation phenomena such as corrosion, coating deterioration, and soiling of heliostats. The model is verified against steady-state data available in literature both on overall receiver metal maximum temperature, HTF outlet temperature and absorbed heat, and on detailed circumferential analysis of the metal external temperature for a specific tube. The dynamic behavior of the receiver is also assessed, with focus on the impact of cloud events and the induced thermal transients. [ABSTRACT FROM AUTHOR]

The most solar-specific components in a Concentrated Solar Power (CSP) plant are the solar field and the receiver. The latter is exposed to extreme working conditions as it withstands high heat fluxes and temperatures in a corrosive environment during usual and transient conditions. It is then of paramount importance to assess the thermal behavior of such a fundamental component of the plant. The object-oriented modelling paradigm enables precise dynamic analysis of physical systems through the solution of sets of equations derived following an acausal approach. This guarantees modularity and description of interactions through physical connection equations with no causality specification. The application of the object-oriented modelling technique on the external receiver of a CSP tower plant is described in detail in this paper, proving its potentialities and modelling capabilities. The model is first verified against data available in literature and then applied for the analysis of dynamic operations, including typical issues of CSP plants as the impact of clouds and heliostats soiling. [ABSTRACT FROM AUTHOR]

It is well-known that the efficiency of Concentrating Solar Power (CSP) plants depends strongly on maintaining a high level of heliostat reflectivity. To inform cleaning policies, an online assessment of heliostat reflectivity is highly desirable to provide real-time updates of current mirror conditions and optimise the cleaning policy, as necessary. There is currently, however, a lack of an economically feasible technique for performing a detailed online heliostat reflectivity assessment. In this paper, a low-cost heliostat reflectivity monitoring method based on already-installed targeting calibration cameras (e.g. CCD cameras) is proposed and tested. The key idea is to compare calibration camera images to detect the differences of image power caused by losses in heliostat reflectivity. Unlike previous beam characterization systems, the accuracy and sensitivity of reflectivity estimation for individual mirrors under increasingly soiled conditions is tested, and does not require additional sensors (e.g. radiometers or flux gauges). Using data obtained from field experiments conducted at the CSIRO Energy Centre in Newcastle, Australia, a methodology for estimating the mirror reflectivity from filtered calibration camera images was developed, calibrated, and validated. The model predictions showed a maximum absolute reflectivity error of 1% based on 4 consecutive soilings, which is comparable to the variability of (as accurate as) the reflectometer measurements themselves. The results of this study demonstrate the feasibility of using simple calibration camera images for economical reflectivity monitoring by removing the need for extensive manual measurements or expensive additional equipment. Such a methodology would allow assessment of cleaning benefits in the real-time operational context (e.g. weather, electricity market prices) and enable dynamic, data-driven cleaning decisions. [ABSTRACT FROM AUTHOR]

The optical efficiency of the solar field heliostats of a Concentrating Solar Power (CSP) tower plant is a fundamental parameter to assess the productivity of the plant. The optical efficiency is mainly affected by the position of the sun in the sky during the year, and by the cleanliness level of the heliostats, which is related to their reflectance. The reflectance is continuously diminished by the deposition of dust on the heliostat surface (that is, soiling). Natural cleaning events, as rain, are rare in typical locations for CSP plants, so artificial cleaning is the most common technique used to maintain the optical efficiency (heliostat reflectance) as close as possible to its optimal value in order to maximize the overall production and thus the revenues of the CSP plant. This paper provides a methodology to assess the soiling of a heliostat field and then evaluates the impact of artificial cleaning on the optical efficiency, considering different frequencies of cleaning in four different scenarios. The outcome of this study is a considerable step forward towards the optimization of costly cleaning activities to minimize operation costs in solar power technologies. [ABSTRACT FROM AUTHOR]