Heliostat Field Layout Research Articles

Quickly select heliostat candidates and design pattern-free layout using geometric projection method

Central receiver system is one of the most promising solar energy harvesting technologies, which focuses sunlight onto the receiver through heliostats to generate high temperatures for thermal cycling. The optimal layout of the heliostat plays a crucial role, but the pattern-free heliostat field layout requires multiple uses of computationally intensive shadowing and blocking efficiency, which is highly time-consuming. In this work, a new geometric projection method, Projection radius method (PRM), is proposed. It includes two aspects: (i) Quickly and effectively selecting heliostat candidates with shadowing and blocking potential by the incident and reflected ray projection radius; (ii) Designing the pattern-free heliostat field layout by employing overlap radius instead of shadowing and blocking efficiency. The results indicate that, compared to traditional methods, when designing 2650 heliostats, (i) the calculation time for optical efficiency was reduced by 63%; (ii) optical efficiency increased by 1.23%, and designing a pattern-free layout took only 2.78 h. These advancements facilitate the efficient design of large-scale pattern-free heliostat field layouts.

Design of Modular High Temperature Sodium Solar Collection Subsystems

Optimised designs of 11.7MWth solar collection subsystem modules based on high temperature (740°C) sodium central receivers are investigated. Billboard and cavity receivers mounted on steel lattice towers are considered, and radially staggered and Cartesian heliostat field layouts are compared. A billboard receiver paired with a Cartesian heliostat field layout was found to give the overall lowest levelised cost of heat (LCOH), albeit with a significantly taller tower compared to using a radially staggered heliostat field layout.

Optimization Design of Tower Solar Heliostat Field Layout of Based on Wheatfield-PSO Model

Optimization Design of Tower Solar Heliostat Field Layout of Based on Wheatfield-PSO Model

Optimization of Optical Efficiency Modeling and Heliostat Field Layout of Tower Solar Thermal Power Station

The aim of this paper is to study and optimize the layout of heliostat mirror fields in solar photovoltaic power plants to improve energy efficiency. By analyzing the key factors of optical efficiency, the optical efficiency model is constructed. The optical efficiency of a single heliostat mirror is calculated using five efficiency factors, namely, shadow shading efficiency, cosine efficiency, atmospheric transmittance, collector truncation efficiency, and mirror reflectivity. The DELSOL layout is used as the initial mirror field, and the mirror field design is optimized by the particle swarm algorithm. The optimal design parameters of the heliostat mirror field including the position of the absorption tower, the size of the heliostat, and the installation height were calculated by adjusting the positions of the heliostat and the absorption tower many times. The results show that the annual average optical efficiency of the heliostat field is 0.6127, and the annual average thermal power output is 37.4508 MW. Through optimization, the annual average optical efficiency of the heliostat field is increased to 0.75, and the annual average thermal power output reaches 64.98 MW. In addition, the results show that the heliostat field has a seasonal characteristic. The optical efficiency and the annual average thermal power output change monthly.

Techno-Economic Analysis of Central Receiver Plants According to the Optical Error of the Solar Field

Among the concentrated solar power technologies (CSP), the central receiver (CR) technology is the most promissing to achieve the lowest levelized cost of energy (LCOE) and the one expected to play one of the major roles in the energetic mix in the next years. For that purpose, succesful CR projects are needed, starting by the contruction and erection of a reliable heliostat field that fulfils its design specifications. In this work, the loss of energy production and the consequently rise of LCOE is investigated as function of the optical error of the heliostats. For that, a reference CR plant is defined in which the heliostat field layout and the receiver are optimized to collect the maximum annual energy. An aiming strategy is also implemented to obtain more realistic results. For instance, for a reasonable deviation of about 40-50% compared to the optical reference error, the annual collected energy can drop to a considerable 5%.

Research on Optimization Design Based on Heliostat Field

This study aims to deeply explore the mathematical modeling and performance optimization of solar heliostat fields, in order to improve their energy output efficiency. The solar heliostat field is an innovative solar heating system that focuses solar radiation on the absorption tower through a reflector, thereby generating high-temperature heat energy. This article mainly discusses the performance analysis and parameter optimization of the heliostat field to achieve optimal performance while meeting the rated power requirements. A simulated solar model was established using a three-dimensional Cartesian coordinate system, taking into account the effects of solar altitude angle and direct normal irradiance (DNI). The model in this paper comprehensively considers the effects of shadow occlusion loss, cosine efficiency, atmospheric transmittance, collector truncation efficiency, and mirror reflectance on the mirror field. The specific values of each parameter were calculated using model algorithms such as the HFLCAL model, To provide a basis for accurate performance analysis and solve the problem of parameter optimization, this article defines an objective function aimed at improving the energy utilization efficiency of the heliostat field by adjusting the parameters of the reflector, in order to achieve optimal performance. The above parameters are determined by establishing a genetic algorithm to define constants and initial parameters, and initializing the overall layout of the heliostat field to calculate the optical efficiency of the heliostat. In each iteration, the optimal heliostat field layout can be recorded. The final optimal solution includes parameters such as the position coordinates of the absorption tower, heliostat size, installation height, number of heliostats, and heliostat position.

Heliostat Consortium: Gap Analysis on Wind Load for Achieving a Fully Competitive Heliostat Industry

The Heliostat Consortium (HelioCon) Wind Load Subtask was initiated with the aim of bringing research work pertaining to wind load measurement, characterization, and prediction taking place across several tasks, including Advanced Manufacturing, Components and Controls, and Field Deployment. The cross-cutting wind load subtopic in the HelioCon roadmap report [1] highlighted standardized methods and tools that are needed for a more detailed understanding of the static and dynamic loads on a heliostat. This will enable cost reduction of wind-dependent heliostat components to avoid unnecessarily conservative, overly constrained designs and increase field efficiency/reliability, to reduce the risk of component failures due to high-wind events (>15 m/s). Gaps related to heliostat wind load include site characterization for wind measurements, critical load cases for heliostat design, turbulence impacts on heliostat tracking error, testing of heliostat array configurations, understanding spatial variation of maximum loads across the solar field, and heliostat field layout and operating strategies. The recommended highest-priority pathway as first steps taken by HelioCon to address these gaps are to develop site characterization guidelines for heliostat design and field load measurements.

Layout optimization of heliostat field based on genetic algorithm

In order to improve the annual average optical efficiency of a tower solar power plant, a simulated heliostat field layout optimization model is constructed using ray tracing method to calculate the shadow shading efficiency. is constructed using ray tracing method to calculate the shadow shading efficiency. Genetic algorithms are used to encode the variables such as solar pitch angle, solar azimuth angle, and coordinates of heliostat mirrors in chromosomal individuals in binary regions, and to find the near-optimal solutions in iterative populations through the use of ray tracing method. Simulation results show that the model can significantly optimize the layout of the tower solar power system. Simulation results show that the model can significantly optimize the layout of the tower solar power plant and improve the annual average optical efficiency. neighboring heliostats is at 0.398 times the sum of the length and width, the optical efficiency of the Khi Solar One power plant reaches 61.83%, which is an improvement of 15.74% compared to that of the Khi Solar One power plant. improvement of 15.74% compared to this engineering example.

Genetic algorithm optimization of heliostat field layout for the design of a central receiver solar thermal power plant

The heliostat field layout in a central receiver solar thermal power plant has significant optical losses that can ultimately affect the overall output power of the plant. In this paper, an optimized heliostat field layout based on annual efficiency and power of 50 MW for the local coordinates of Quetta, Pakistan, is proposed. The performance of two different heliostat field layouts such as radial staggered and Fermat's spiral distribution are evaluated and different design points in a year are considered for the analysis. The field layouts are then optimized using a rejection sampling based Genetic Algorithm (GA). It considers the output power and mean overall efficiency for vernal equinox, summer solstice, autumnal equinox, and winter solstice as objective functions. The GA optimizes the heliostat field parameters, namely, security distance (DS), tower height (TH), heliostat width to length ratio (WR), and the length of heliostats (LH). The study system was developed in MATLAB for validation. It was observed that for the radial staggered layout, the number of heliostats decreased by 364 and the efficiency was improved by 8.52 % using GA optimization relative to unoptimized results field layout. The annual efficiency for Fermat's spiral configuration was improved by 14.62 % and correspondingly, the number of heliostats decreased by 434.

Optimization Model of Heliostat Field Layout based on Genetic Algorithm

In this paper, starting from the relevant data of the heliostat field, we firstly built an accurate computational model and established a 3D coordinate system with the tower as the origin, and visualized the data through Matplotlib to present the results clearly. Finally, we constructed a reliable mathematical geometric model and explored how to optimize the heliostat field by a genetic algorithm: maximizing the output power per unit area with the annual power already determined.

GA-GOA hybrid algorithm and comparative study of different metaheuristic population-based algorithms for solar tower heliostat field design

A comparative analysis has been carried out between eight metaheuristic algorithms, namely; genetic algorithm (GA), differential evolution (DE), particle swarm optimization (PSO), grey wolf optimization (GWO), improved grey wolf optimization (IGWO), artificial bee colony (ABC), grasshopper optimization algorithm (GOA), and a proposed hybrid genetic-grasshopper (GA-GOA) to optimize the staggered heliostat field of the PS10 plant. The annual weighted efficiency is taken as the objective function for field layout optimization. In addition, the investigated algorithms have been assessed in terms of best energy yield, levelized cost of energy (LCOE), land use factor (LUF), and computational cost. It has been found that evolutionary algorithms outperform swarm intelligence algorithms in terms of efficiency, whereas GOA and GWO converge faster. To get high efficiency with low computational cost, a hybrid GA-GOA algorithm has been proposed. This study found that the hybrid GA-GOA algorithm does indeed deliver improved performance, with an optimum weighted efficiency boosted by 1.45% at a computation cost of ∼63.7 h. In addition, it provides the best optimum LCOE of 26.22 c€/kWh and successfully enhances LUF by 11.2% compared to the PS10 reference plant. Based on these results, the authors can conclude that the proposed hybrid GA-GOA algorithm represents a suitable tool to cost-effectively optimize the design of heliostat field layouts and reduce their land footprint.

Optical-thermal-mechanical analysis of high-temperature receiver integrated with gradually sparse biomimetic heliostat field layouts for the next-generation solar power tower

Three gradually sparse biomimetic (GSB) heliostat field layouts, which gradually extend from the inside to the outside, are proposed herein. Annual optical performance is compared with the standard biomimetic (SB) layout and the widely used staggered layout. In the end, the receiver’s optical-thermal–mechanical performance is analyzed with the above five heliostat fields for the next-generation solar power tower (SPT) with the receiver’s outlet temperature at 720 °C. The results show that the GSB layout with a linear increasing factor (Linear-GSB) has the best optical performance. Compared with the staggered layout and the SB layout, the Linear-GSB layout can increase the annual intercepted energy (Eann) by 1.5% and 1.3% under the same heliostat number, respectively. Moreover, GSB layouts can simultaneously reduce the receiver’s maximum heat flux (qmax), maximum thermal stress (σw,max) and improve its heat flux distribution homogeneity. Compared with the staggered layout, qmax, σw,max, and heat flux maldistribution index of the receiver under the Linear-GSB layout at noon of spring equinox are decreased by 4.2%, 4.3%, and 19.8%, respectively. Meanwhile, the Linear-GSB layout can achieve slightly higher receiver efficiency compared with the staggered layout.

Accurate interpolation methods for the annual simulation of solar central receiver systems using celestial coordinate system

Heliostat field layout optimization bases on simulations of the annual energy production. To reduce the computation time of the optimization process, one can try to reduce the number of simulation points of the annual domain, while keeping similar accuracy. For the temporal domain, there exist already different approaches as aggregation of days. To further reduce the number of needed simulation points, in this paper we decouple the power computation from the irradiation, such that we just regard the computation of the power plant efficiency. This time-dependent parameter is transformed into a celestial coordinate system where the solar angle-dependent efficiency will be approximated using suitable multi-dimensional interpolation methods.We distinguish between an accurate approximation of the received annual optical energy and the electrical energy of each moment of a year. These methods are demonstrated for the existing heliostat field layouts PS10 and Gemasolar in Seville, while using realistic weather conditions. With this new approach just around 40 simulation points suffice to reach an accuracy of 99.9% for the received power for smaller power plants as PS10, and for larger plants as Gemasolar. Compared to a state-of-the-art method, this investigation helps to accelerate the simulation by factor three.

Solar tower on an uneven terrain: methodology and case study

We develop a tool to estimate the potentiality of heliostat-field based central solar tower technology in an uneven terrain. SolarPILOT is a recently developed tool to design such heliostat field layout. Even though, individual heliostat elevation, where available, can be incorporated in obtaining the shading and blocking from immediate neighbours, the layout optimization in SolarPILOT assumes a flat field. The tool presented in this work supplements this shortcoming of SolarPILOT and extends its range of applicability in heliostat field design particularly on a hilly terrain. The developed tool is applied to two case-studies on real terrains, at real locations. By computing the shading and blocking profile, the annual up-time for individual heliostat is estimated. For the chosen terrains, 10%–30% heliostats remain ineffective more than 50% of the time due to shading or blocking, hence, can be eliminated to minimize cost. If such ineffective heliostats are removed from the installation on an uneven terrain, a significant cost-reduction is achieved at the expense of low reduction in heat collection potential of the field, lowering the LCOE by higher than a factor of two. The current study is an attempt towards development of a universal design-tool for heliostat fields. • Utilization of uneven land having no other use can reduce cost for heliostat fields. • Open source tool, SolarPILOT, is limited by the flat-field assumption. • Shading and blocking due to relative altitude need inclusion for undulated terrain. • We develop a tool which extends the applicability of SolarPILOT to uneven terrains. • Based on annual up-time estimation, heliostat field is truncated to reduce cost.

Pattern-free heliostat field layout optimization using physics-based gradient

In this paper, the alternating direction method is proposed to perform heliostat field layout optimization, which includes two new strategies: (1) pattern-free layout optimization using the proposed physics-based gradient of optical efficiencies, and (2) new initial designs obtained by changing a scaling factor (k). To obtain the physics-based gradient, insolation weighted optical efficiency is divided into two terms – shading/blocking efficiency and non-shading/blocking efficiency, and for more efficient and accurate layout optimization, the proposed alternating direction method performs layout optimization along alternating directions obtained from the physics-based gradient. The proposed alternating direction method is validated using two field layouts – PS10 and a field layout obtained by SolarPILOT – with two objective functions, optical efficiency and levelized cost of electricity (LCOE). The validation results show that both the insolation weighted optical efficiency and LCOE are much improved by the proposed optimization method.

Perspective of concentrating solar power

In this perspective paper, the present status and development tendency of concentrating solar power (CSP) are analyzed from two aspects: (1) Potential pathways to efficient CSP through improving operation temperature to above 700 °C; (2) Technologies for efficient solar collection, thermal storage, and power generation at >700 °C. Based on the analyses, barriers on the way to the high-temperature CSP are summarized. They are: (1) the lack of methodology for heliostat design and field layout optimization, (2) significant performance degradations of solar-thermal conversion, heat storage and transfer in receiver and thermal energy storage due to high temperature, (3) the lack of suitable supercritical CO2(S–CO2) Brayton cycle for CSP and mature design methods for S–CO2 components. To overcome these issues, perspectives on following three aspects are proposed. Firstly, optimization approaches for optimal heliostat size and layout, and game-changing techniques for heliostat structure design should be brainstormed. Secondly, receivers and thermal storage devices designed through efficiency-improving approaches and fabricated by durable materials should be developed to maintain efficient and reliable operation. Thirdly, the developments of novel S–CO2 cycle and corresponding key components are eagerly desired to achieve efficient thermal-electric conversion. Perspectives from this paper would present possible approaches to efficient CSP.

Rose pattern for heliostat field optimization with a dynamic speciation‐based mutation differential evolution

Concentrated solar power technology is one of the most promising technologies in energy field. Arguably, the heliostat field layout is a crucial component in solar power tower system. Numerous studies have been developed for heliostat field optimization. However, most of the existing layouts which utilize radial staggered patterns are based on only two or four variables, leading to relatively rigid modes due to strong configuration constraints. In this article, we propose a new method called rose layout, which divides the regular radial staggered pattern into six sectors and they are optimized separately. Therefore, the radial increments between consecutive rows are not restricted to zones or rows, only relevant to which sector they belong to. This arrangement is more flexible and also efficient. Furthermore, a new differential evolution algorithm with a dynamic speciation-based mutation strategy (DSM-DE) is developed to solve this high-dimensional problem. In order to validate the proposed rose pattern and DSM-DE, three sets of comparative experiments were carried out. The first set of tests were operated with the conventional four optimization variables, the second series optimized total 43 radial increments between consecutive rows, whereas the third series employed the rose layout. All sets of cases were optimized by four competitive variants of differential evolution algorithm, ie, JADE, SHADE, EB-LSHADE, and DSM-DE. Experimental results verified that the rose layout can obtain higher overall optical efficiency and less land coverage than previous methods and DSM-DE is superior to other DE variants for this high-dimensional problem. The heliostat field studied in this article is simulated in Qinghai, China. By integrating rose layout with DSM-DE, the field unweighted efficiency progressed from 44.386% to 53.972%, and the annual weighted efficiency reached 59.091%, which was 0.318% higher than the 43-variable optimization.

Optimization of a heliostat field site in central receiver systems based on analysis of site slope effect

This paper proposes a methodology to select a site for a heliostat field to further improve its optical efficiency. Site selection implies to select a location with advantageous geographical features for optical efficiency improvement. Therefore, analysis on the site slope effect and guideline to select the most optically efficient site type are the main concerns of this study. The paper consists of two parts: (1) analysis of the site slope effect and determination of the most efficient site type at each latitude, and (2) optimization of heliostat layout on the optimal site for further improvement. Latitude is treated as a control variable since it changes all the solar characteristics, so the site effects at different latitudes are examined independently in this study. Surrogate modeling and genetic algorithm are utilized for efficient and accurate optimization of the heliostat field layout. This study reveals that the optimal site type varies according to the latitude, and utilization of the most efficient heliostat field site improves the optical efficiency by up to 1.65% point that can hardly be achieved by field layout optimization only. Furthermore, this study suggests the applicability of central receiver system (CRS) at high latitude with appropriate site selection and layout optimization.

Small scale solar tower coupled with micro gas turbine

This paper studies a small-scale CSP system composed of a solar tower and a recuperative air micro gas turbine (i.e. net power in the 100–200 kWe range). A code is developed to determine the optical performance of the heliostat field coupled with a secondary concentrator, while another code computes the thermal engine performance. The 832 m2 heliostat field layout is taken from a real plant, while the secondary optics is studied to maximize the optical-thermal efficiency. The selected secondary concentrator (CPC), with an aperture diameter of 0.5 m and an acceptance angle of 35° tilted of 52.5°, guarantees an overall optical efficiency of 77.9% in design conditions (Spring equinox, solar noon) and of 66.9% on yearly basis. For every Effective DNI (EDNI) and ambient temperature the turbine operation is optimized allowing to achieve a yearly solar-to-electricity efficiency of 16.3%. Summing up the cost of each component, an overall plant cost of about 2300 €/kW (peak) and a LCOE of 175 €/MWh are obtained. A sensitivity analysis on design EDNI, impacting on turbine size, is performed showing that its reduction from 700 W/m2 to 550 W/m2 allows reducing the LCOE down to 158 €/MWh, a value competitive with large-scale solar towers. The possibility of hybridization of plant (i.e. improving the gas turbine power output in selected hours, by means of biomethane or natural gas combustion) was considered to further reduce the LCOE.

Rapid design of a heliostat field by analytic geometry methods and evaluation of maximum optical efficiency map

Many procedures have been developed to design and optimize a heliostat field, however it is a rather challenging work partly because many influencing factors of a heliostat optical efficiency, especially the shading and blocking efficiency, are computationally intensive. And it’s difficult to judge whether a heliostat field layout is an ideal design intuitively and reliable. In this paper, two concise and accurate analytic geometry methods (AGM-I and AGM-II) are developed to identify the heliostats with the possibilities of shadowing or blocking a given heliostat firstly. The results compared with the Sassi method and bounding sphere & Sassi method show that the same accurate results are obtained while the computational time is significantly reduced by 32% and 23%, respectively. Then an intuitive approach is proposed to optimize and evaluate the rationality of a heliostat field layout by applying the maximum optical efficiency map (MOEM). Finally, a heliostat field based on the Gemasolar plant is studied, whose optical efficiency is optimized and evaluated by the proposed methods. Compared with the un-optimized result and the result optimized by using the reference method, the MOEM optimization result of the heliostat field with higher instantaneous optical efficiency and annual optical efficiency is more reasonable.