Search Results (33)

In this work, solar concentrating heliostat fields are modeled using accurate solar-tracking algorithms and a wide range of rotation models to investigate the parameters controlling the mechanical efficiency of these solar facilities. Iterative procedures are first described to determine the rotation angles needed to properly orient a single heliostat for the most commonly used mechanical models, including the azimuth-elevation, tilt-roll, and target-aligned models. These mathematical techniques were integrated into our Light Analysis Modelling (LAM) software and used to study a realistic heliostat field with six different mechanical rotation models for the full year of 2024 and a daily working range of 08:00–16:00 Local Time (LCT). Two locations were chosen, representing the highest and lowest latitudes from the SFERA-III EU list of solar concentrating facilities with heliostat fields: Jülich (Germany) and Protaras (Cyprus). The results obtained show that tilt-roll models require less angular rotation (−15.2% in Jülich, −20.2% in Protaras) and a narrower angular range (−14.5% in Jülich, −20.2% in Protaras) than azimuth-elevation models. Seldom-used target-aligned models are more efficient with tilt-roll rotations (compared with the tilt-roll model: −35.1% rotations in Jülich, −29.2% in Protaras; −12.3% angular range in Jülich, −14.3% in Protaras) and less efficient with azimuth-elevation rotations (compared with the azimuth-elevation model: +53.2% rotations in Jülich, +39.2% in Protaras; +96.2% angular range in Jülich, +87.5% in Protaras). Full article

Predicting the solar flux density distribution formed by heliostats in a concentrated solar tower power (CSP) plant is important for the optimization and stable operation of a CSP plant. However, the high temperature and blackbody attribute of the receiver makes direct measurement of the concentrated solar irradiance distribution a difficult task. To address this issue, indirect methods have been proposed. Nevertheless, these methods are either costly or not accurate enough. This study proposes a ray tracing-assisted deep learning method for the prediction of the concentrated solar flux density distribution formed by a heliostat. Namely, a generative adversarial neural network (GAN) model using Monte Carlo ray tracing results as the input was built for the prediction of solar flux density distribution concentrated by a heliostat. Experiments showed that the predicted solar flux density distributions were highly consistent with the concentrated solar spots on the Lambertian target formed by the same heliostat. This ray tracing-assisted deep learning method can be extended to other heliostats in the CSP plant and pave the way for the prediction of the solar flux density distribution concentrated by the whole heliostat field in a CSP plant. Full article

In this work, solar concentrating heliostat fields are modelled using computer ray-tracing techniques to investigate the parameters controlling the optical efficiency of those solar facilities. First, it is explained how the non-trivial problem of heliostat blocking and shading can be efficiently handled in ray-tracing simulations. These numerical techniques were implemented in our Light Analysis Modelling (LAM) software, which was then used to study realistic heliostat fields for a range of different geometries. Two locations were chosen, with the highest and the lowest latitudes, from the SFERA-III EU list of solar concentrating facilities with heliostat fields: Jülich (Germany) and Protaras (Cyprus). The results indicate that shading and blocking can substantially reduce the radiation collected during the year (up to 20%). Accurate figures of merit are proposed to quantify the thermal efficiency of a heliostat field, independently of its size. Increasing the tower height mostly reduces blocking (especially when the sun is high and most energy is collected), while increasing the distance between heliostats or increasing the ground slope mostly reduces shading (especially when the sun is low and little energy is collected). Full article

To computer-simulate solar-concentrating facilities, an accurate knowledge of the Sun’s position as a function of latitude, longitude, time and date is required. In this work, it is reported first a simplified description of a general algorithm, developed by the astronomy community to accomplish that. Our implementation of this algorithm (included in our Light Analysis Modelling package) has been successfully validated against well trusted astronomy data. The software was then used to produce a wide range of results for 2024, for two well-known research facilities, the most northern (Jülich, Germany) and the most southern (Protaras, Cyprus) heliostat fields listed in the official SFERA-III EU project. This includes altitude and azimuth data, sunrise and sunset data, analemma curves, angular speed data and geocentric Sun trajectories around the observer’s position. Other ray-tracing techniques are also reported to help simulate the Sun vectors reaching the solar devices. The truly inspiring results obtained show how important this type of software is, from the scientific and industrial point of view, to better understand our relationship with our neighbor star, the Sun. Full article

Industrial process heat typically requires large amounts of fossil fuels. Solar energy, while abundant and free, has low energy density, and so large collector areas are needed to meet thermal needs. Land costs in developed areas are often prohibitively high, making rooftop-based concentrating solar power (CSP) attractive. However, limited rooftop space and the low energy density of solar power are usually insufficient to meet a facility’s demands. Maximizing annual CSP energy generation within a bounded rooftop space is necessary to mitigate fossil fuel consumption. This is a different optimization objective than minimizing the Levelized Cost of Energy (LCOE) in typical open-land, utility-scale heliostat layout optimization. Innovative designs are necessary, such as compact, energy-dense central receiver systems with non-flat heliostat field topographies that use spatially efficient Tilt–Roll heliostats or multi-rooftop and multi-height distributed urban systems. A novel ray-tracing simulation tool was developed to evaluate these unique scenarios. For compact systems, optimized annual energy production occurred with maximum heliostat spatial density, and the best non-flat heliostat field topography found is a shallow section of a parabolic cylinder with an East–West focal axis, yielding a 10% optical energy improvement. Tightly packed Tilt–Roll heliostats showed a double improvement in optical energy at the receiver compared to Azimuth–Elevation heliostats. Full article

This study presents a methodology for the development of modern Supervisory Control and Data Acquisition (SCADA) systems aimed at improving the operation and management of concentrated solar power (CSP) plants, leveraging the tools provided by industrial digitization. This approach is exemplified by its application to the CESA-I central tower heliostat field at the Plataforma Solar de Almería (PSA), one of the oldest CSP facilities in the world. The goal was to upgrade the control and monitoring capabilities of the heliostat field by integrating modern technologies such as OPC (Open Platform Communications)) Unified Architecture (UA), a Wi-Fi mesh communication network, and a custom Python-based gateway for interfacing with legacy MODBUS systems. Performance tests demonstrated stable, scalable communication, efficient real-time control, and seamless integration of new developments (smart heliostat) into the existing infrastructure. The SCADA system also introduced a user-friendly Python-based interface developed with PySide6, significantly enhancing operational efficiency and reducing task complexity for system operators. The results show that this low-cost methodology based on open-source software provides a flexible and robust SCADA architecture, suitable for future CSP applications, with potential for further optimization through the incorporation of artificial intelligence (AI) and machine learning. Full article

This paper presents an analysis and optimization of a polygeneration power-production system that integrates a concentrating solar tower, a supercritical CO₂ Brayton cycle, a double-flash geothermal Rankine cycle, and an internal combustion engine. The concentrating solar tower is analyzed under the weather conditions of the Mexicali Valley, Mexico, optimizing the incident radiation on the receiver and its size, the tower height, and the number of heliostats and their distribution. The integrated polygeneration system is studied by first and second law analyses, and its optimization is also developed. Results show that the optimal parameters for the solar field are a solar flux of 549.2 kW/m², a height tower of 73.71 m, an external receiver of 1.86 m height with a 6.91 m diameter, and a total of 1116 heliostats of 6 m × 6 m. For the integrated polygeneration system, the optimal values of the variables considered are 1437 kPa and 351.2 kPa for the separation pressures of both flash chambers, 753 °C for the gasification temperature, 741.1 °C for the inlet temperature to the turbine, 2.5 and 1.503 for the turbine pressure ratios, 0.5964 for the air–biomass equivalence ratio, and 0.5881 for the CO₂ mass flow splitting fraction. Finally, for the optimal system, the thermal efficiency is 38.8%, and the exergetic efficiency is 30.9%. Full article

The tracking pose of heliostats directly affects the stability and working efficiency of concentrated solar power (CSP) plants. Due to occlusion, over-exposure, and uneven illumination caused by mirror reflection, traditional image processing algorithms showed poor performances on the detection and segmentation of heliostats, which impede vision-based 3D measurement of tracking poses of heliostats. To tackle this issue, object detection using deep learning neural networks are exploited. An improved neural network based on YOLO-v5 framework has been designed to solve the on-line detection problem of heliostats. The model achieves a recognition accuracy of 99.7% for the test set, outperforming traditional methods significantly. Based on segmented results, the corner points of each heliostat are found out using Hough Transform and line intersection methods. The 3D poses of each heliostat are then solved out based on the image coordinates of specific feature points and the camera model. Experimental and field test results demonstrate the feasibility of this hybrid approach, which provides a low-cost solution for the monitoring and measurement of tracking poses of the heliostats in CSP. Full article

A solar-powered combined cooling, heating, and power (CCHP) plant integrated with a water electrolysis unit is investigated in terms of energy, exergy, and exergo-economic (3E) assessments. A comprehensive parametric study and optimization is conducted following the thermodynamic and exergo-economic assessment of the proposed system to evaluate the key performance parameters of the system for efficiency and economic factors. This system employs a heliostat field and a receiver tower by taking advantage of thermal energy from the sun and produces a continuous energy supply with an integrated phase-change material (PCM) tank to store the heat. In addition, a supercritical CO₂ Rankine cycle (RC), an ejector refrigeration cooling (ERC) system, and a PEM water electrolyzer are coupled to produce cooling, heating, power, and hydrogen. Thermodynamic analysis indicates that the system exergy efficiency and energy efficiency are improved to $33.50\mathrm{\%}$ and $40.61\mathrm{\%}$, respectively, while the total cost rate is $2875.74 \mathrm{U}\mathrm{S}\mathrm{D}/\mathrm{h}$ and the total product cost per exergy unit is $25.65 \mathrm{U}\mathrm{S}\mathrm{D}/\mathrm{G}\mathrm{J}$. Additionally, the system produces a net generated power, heating load, and cooling load of $11.70$, $13.92,$ and $2.60$ $\mathrm{M}\mathrm{W}$, respectively, and a hydrogen production rate of 12.95 $\mathrm{g}/\mathrm{s}$. A two-objective optimization approach utilizing a non-dominated sorting genetic algorithm (NSGA) was performed, demonstrating that the system’s ideal design point offers a cost rate of $1263.35 \mathrm{U}\mathrm{S}\mathrm{D}/\mathrm{h}$ and an exergetic efficiency of $34.17\mathrm{\%}$. Full article

This paper presents three new methods for calculating the shading and blocking efficiency in Central Receiver Systems (CRSs). All of them are characterized by the calculation of multiple useful and total reflecting areas without the need to resort to parallel calculation in the CPU or GPU, and by low computation times and minimum errors. They are being specially designed for implementation in codes focused on heliostat field design and optimization in CRSs. The proposed methods have been compared against two outstanding “individual” methods (homology and Boolean operations), in addition to a reference case based on the Monte Carlo ray-tracing (MCRT) technique. The results indicate that one of the proposed methods presents reduced error values and high computational speed, even relaxing the restrictions on candidate filtering. At the same error level, the global method is up to 7.80 times faster than the fastest individual method (homology) and up to 194 times faster than the method based on the MCRT technique. The causes of the main errors of each method are also analyzed. Full article

Optimizing the heliostat field aiming strategy is crucial for maximizing thermal power production in solar power tower (SPT) plants while adhering to operational constraints. Although existing approaches can yield highly optimal solutions, their considerable computational cost makes them unsuitable for real-time optimization in large-scale scenes. This study introduces an efficient, intelligent, real-time optimization method based on a meta-heuristic algorithm to effectively and reliably manage SPT plant operations under varying solar conditions, such as cloud shadowing variations. To minimize redundant calculations, the real-time optimization problem is framed in a way that captures the operational continuity of the heliostat, which can be utilized to streamline the solution process. The proposed method is tested in a simulation environment that includes a heliostat field, cylindrical receiver, and cloud movement model. The results demonstrate that the algorithm presented in this paper offers higher intercept efficiency, improved robustness, and reduced optimization time in more complex scenes. Full article

The integration of a CSP tower system with a PV solar field, sharing a thermal energy storage, is modeled and discussed. The tower system uses a new-design solid particle fluidized bed receiver integrated with a thermal storage, where hot particles are directly collected to store daily energy for overnight production of electricity. The PV solar field is aimed to supply the daily energy demand; when there is a surplus of PV energy production, the electric energy is converted to heat and accumulated in the thermal storage too. The integration of the two energy systems is modeled, building efficiency functions for all the sub-components of the integrated plant (heliostat field, receiver, storage, power block, PV field). Yearly simulations are performed for two different locations, Spain and Australia, obtaining that a system with a peak power of 10 MW_e CSP + 15 MW_e PV can supply—with a limited curtailment—a fraction of more than 60% (respectively, 62% and 68%) of a realistic electric load with a peak demand around 10 MW, to be compared with the 45/47% of the same load obtained adopting a PV-only system with the same overall peak power. In the integrated system, PV directly supplies 40/41% of the load, the remaining 23/28% being produced by the power block (mainly fed by the CSP). Full article

Solar thermal power plants are an alternative for the future energy context, allowing for a progressive decarbonisation of electricity production. One way to improve the performance of such plants is the use of supercritical CO₂ power cycles. This article focuses on a solar thermal plant with a central solar receiver coupled to a partial cooling cycle, and it conducts a comparative study from both a thermal and economic perspective with the aim of optimising the configuration of the receiver. The design of the solar receiver is based on a radial configuration, with absorber panels converging on the tower axis; the absorber panels are compact structures through which a pressurised gas circulates. The different configurations analysed keep a constant thermal power provided by the receiver while varying the number of panels and their dimensions. The results demonstrate the existence of an optimal configuration that maximises the exergy efficiency of the solar subsystem, taking into account both the receiver exergy efficiency and the heliostat field optical efficiency. The evolution of electricity generation cost follows a similar trend to that of the exergy efficiency, exhibiting minimum values when this efficiency is at its maximum. Full article

Generating electric power using solar thermal systems is effective, particularly for countries with high solar potential. In order to decide on a relevant location to implement the solar tower plant and develop the mathematical model of a no-blocking heliostat field, a meteorological assessment was discussed in this paper. In addition, a parametric study was examined to evaluate the effect of the designed parameters (heliostat size, heliostat height from the ground, tower height, receiver aperture, and the minimum radius) on the solar field’s performance. The preliminary solar field was then compared to the final design using the optimal design parameters. The obtained results showed that “Tamanrasset City” satisfied the necessary conditions for implementing a solar tower plant. According to preliminary solar field generation, no heliostat blocked its neighbor with a blocking efficiency of 100%. An analysis of its performance revealed that the optimized solar field would be capable of producing 15, 6571 MW, operating at an optical efficiency of 76.95%, and the enhancement rate of both efficiency and power output was 8.1%. Full article

Weather conditions have significant impacts on the solar concentration processes of the heliostat fields in solar tower power plants. The cloud shadow movements may cause varying solar irradiance levels received by each heliostat. Hence, fixed aiming strategies may not be able to guarantee the solar concentrating performance. Dynamic aiming strategies are able to optimize the aiming strategy based on real-time shadowing conditions and short-term forecast, and, therefore, provide much more robust solar concentration performance compared to fixed strategies. In this work, a model predictive control approach for s heliostat field power regulatory aiming strategy was proposed to regulate the total concentrated solar flux on the central receiver. The model predictive control method obtains the aiming strategy, leveraging real-time and forecast shadowing conditions based on the solar concentration model of the heliostat field. The allowable flux density of the receiver and the aiming angle adjustment limits are also considered as soft and hard constraints in the aiming strategy optimization. A Noor III-like heliostat field sector was studied with a range of shadow-passing scenarios, and the results demonstrated the effectiveness of the proposed method. Full article