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At least 271 records · Page 15

Durability and Accelerated Aging Test of the Polymeric Mirror-Film Prototype (CRADA Final Report)

The participant is developing a low-cost liquid metal coating for concentrated solar power (CSP) polymeric mirrors. Current CSP technology uses bulky and costly glass mirrors. As a lighter alternative, polymeric mirror film is cheaper than glass mirrors, yet expensive to manufacture. The participant is working to develop a room temperature liquid-metal thin-film deposition technique and CSP polymeric mirror film that will reduce expenditures by 80% and film cost by 50%.

14 SOLAR ENERGY↗

Continuous Purification of Molten Chloride Salt: Electrochemical Behavior of MgOHCl Reduction

We present a study on the electrochemical behavior of magnesium hydroxide (MgOH + ) reduction on a tungsten (W) cathode in molten chloride salt (MgCl 2 -KCl-NaCl) across the temperature range of 475 °C–525 °C. MgOH + , which forms within the salt upon exposure to moisture, is a leading cause of corrosion. Corrosion is a major barrier to deployment of chloride salts across a number of applications, including concentrating solar power plants and nuclear power plants. While pre-purification protocols have been developed to ensure MgOH + is removed from molten chloride salts prior to deployment, MgOH + forms in situ during operation of chloride-salt based plants. Thus, methods for continuous purification during plant operation are needed. Continuous electrochemical purification via electrolysis using a Mg anode and W cathode has been proposed, but little has been done to assess scalability. Here, we assess fundamental properties of electrochemical removal of MgOH + to enable future scale up of this method.

14 SOLAR ENERGY↗

Solar Field Layout and Aimpoint Strategy Optimization

The existing methods that determine heliostat aiming strategies for concentrating solar power (CSP) central receiver plants typically use heuristics and/or are computationally expensive, and they lack flexibility for different desired flux profiles and receiver geometries. Because of the interaction between layout and aimpoint strategy, considering the former without accounting for the latter may yield solutions with superfluous heliostats that cannot be used efficiently without compromising receiver flux constraints. To that end, we develop a software decision tool that uses innovative optimization methods to both optimize aimpoint strategies and improve candidate layouts for the solar collection field of a CSP central receiver plant. A CSP plant’s effectiveness relies on the optical efficiency of the solar field, which may be limited by losses due to (i) the cosine effect, (ii) atmospheric attenuation, (iii) interference (i.e., shading and blocking) between heliostats, (iv) spillage as a result of heliostat positioning and geometry, and (iv) some heliostats’ inability to direct irradiance to the receiver without damage due to excessive thermal flux. The goal of this work is to obtain optimized aiming strategies and improved solar field layouts that reduce capital cost and increase field optical efficiency and utilization, while meeting the power requirements of a given CSP receiver design. We formulate the aimpoint optimization problem as a mixed-integer linear programming model, which we then decompose into submodels that we solve in parallel. The decomposition subdivides the solar field into sections, and aimpoint strategies for each section are obtained independently of the others. To improve existing layouts, we develop a utilization-weighted efficiency metric that we use to relocate heliostats to sections of the solar field with similar efficiency and higher utilization. Finally, to connect our software to high-fidelity flux models, we develop a Python application programming interface for SolarPILOT, a mature software package that characterizes solar field performance and generates the heliostat layouts and flux maps that serve as input to our models.

14 SOLAR ENERGY↗

Hydride-based thermal energy storage

Abstract The potential and research surrounding metal hydride (MH) based thermal energy storage is discussed, focusing on next generation thermo-chemical energy storage (TCES) for concentrated solar power. The site availability model to represent the reaction mechanisms of both the forward and backward MH reaction is presented, where this model is extrapolated to a small pilot scale reactor, detailing how a TCES could function/operate in a real-world setting using a conventional shell & tube reactor approach. Further, the important parameter of effective thermal conductivity is explored using an innovative multi-scale model, to providing extensive and relevant experimental data useful for reactor and system design. Promising high temperature MH material configurations may be tuned by either destabilisation, such as using additions to Ca and Sr based hydrides, or by stabilisation, such as fluorine addition to NaH, MgH 2 , or NaMgH 3 . This versatile thermodynamic tuning is discussed, including the challenges in accurately measuring the material characteristics at elevated temperatures (500 –700 °C). Attention to scale up is explored, including generic design and prototype considerations, and an example of a novel pilot-scale pillow-plate reactor currently in development; where materials used are discussed, overall tank design scope and system integration.

25 ENERGY STORAGE↗

Mechanical Failure Risk Management for In-Service CSP Nitrate Hot Tanks

The hot thermal energy storage tanks in many operating (Gen2) concentrating solar power plants are designed to contain molten nitrate solar salt at 565 Degrees Celsius and are constructed from 347H stainless steel (SS). From previous work, it is known that 347H SS weldments are potentially susceptible to stress-relaxation cracking (SRC), particularly in the heat-affected zone above 540 Degrees Celsius when no post-weld heat-treatment (PWHT) is performed. However, residual stresses can be reduced when weldments receive PWHT, while at the same time a crack-resistant microstructure is being generated. The overarching goal of this project was to optimize cost-effective, thickness-dependent, localized PWHT procedures and to investigate for feasible non-destructive evaluation (NDE) at commercial scale for hot tanks in Gen2 CSP using 347H SS.

14 SOLAR ENERGY↗

A Comparative Radiative Property Evaluation of Sintered Bauxite and AMS4003 Ceramic Particles

The radiative properties of sintered bauxite (ACCUCAST ID80) and AMS4003 particles were measured and compared to assess their performances as direct absorption and heat transfer media for particle-based concentrated solar power (CSP) plants. Reflectance measurements were performed over the spectral range 0.2–20 µm and used to calculate solar and thermal emission properties of the particles. In addition, reflectance was measured as a function of temperature up to 1000 °C for the spectral range 1–20 µm. The solar absorptance of AMS4003 was greater than that of ACCUCAST both before and after thermal cycling of the materials at 1000 °C, although thermal cycling was found to substantially decrease the solar absorptance of both materials. The thermal emittance of AMS4003 was also greater than that of ACCUCAST at all temperatures tested. Finally, the radiaitve properties measured in this study were used to estimate absorber efficiencies as a way to compare the particles in terms of their performance in a solar receiver. AMS4003 yielded greater efficiencies than ACCUCAST, suggesting its potential as a material for CSP.

14 SOLAR ENERGY↗

OPTOM: Optimization of Parabolic Trough - Operations & Maintenance

The US Department of Energy’s SunShot goals look to reduce the cost of Concentrating Solar Power (CSP) technology to 5¢/kWh for baseload plants. This is about a 50% reduction from current costs. To achieve this cost target, a significant reduction in operation and maintenance (O&M) costs of 40 to 50% is likely needed. Advances are needed in the O&M practices of CSP plants if the technology is to achieve the SunShot cost goals. Digitization of plant performance and O&M data has become a new best practice in the world of renewable energy asset management. Owners and operators of large photovoltaic and wind power plants are working to digitize performance and O&M data at their existing assets, to improve their management of the facilities, to increase performance, reduce O&M costs, and lower the overall life cycle cost of ownership. CSP power plants are behind the curve of other technologies on the digitization of plant information to aid in the plant asset management. This project directly addresses the objective of digitizing the O&M data of the solar field, focusing on three areas: 1) creating a framework for sharing data and information, 2) creating a system for monitoring and managing the maintenance of the solar field collectors, and 3) developing analytic tools to identify issues in the solar field. According to the NREL CSP Best Practices Study, the current practice at many CSP plants is to rely on paper lists, spreadsheets, and email for monitoring and managing problems and maintenance in the solar field. The key element to digitize solar field O&M is the creation of a centralized data archive that all users and systems can interface with. This project developed a centralized relational database framework that allows users and applications to access and share data. Conventional power plants utilize Computerized Maintenance Management Systems (CMMSs) to track the corrective, preventive (scheduled), and predictive maintenance of equipment and subsystems in the power plant. CSP plants use these systems in the power block, but while these systems specialize at tracking maintenance on up to thousands of pieces of equipment, they are not well suited for tracking the tens or hundreds of thousands of components in large commercial CSP or photovoltaic solar fields. In this project we developed a new software application referred to as FieldStatus (TM). This is a specialized database program that is used to track the status of each collector and its components. This application is designed to complement the existing CMMS to enable improved tracking and management of maintenance activities in the solar field. One of the major maintenance tasks for solar fields is maintaining the cleanliness of the mirrors. Although seemingly a relatively straight forward task, it has often proven challenging to maintain high levels of cleanliness in an efficient and cost-effective manner. This project developed new tools and metrics for monitoring and optimizing solar field cleaning resources and overall solar field cleanliness.

14 SOLAR ENERGY↗

Characterizing the Impact of Heliostat Size, Focus Method, and Optical Error on Concentrating Solar Tower Systems

Concentrating Solar Power (CSP) tower systems use heliostat fields to direct solar energy to a central receiver. The efficiency of the heliostat field is crucial for achieving thermal generation targets and is also the largest cost component, making up 30-40% of total project costs. Developers face a tradeoff: reducing heliostat costs may decrease optical performance and increase land use, while improving performance could raise manufacturing costs (through higher precision). The optimal design depends on land, labor, and manufacturing costs. Additionally, inherent performance limitations exist - optical errors result in larger solar images as heliostats move farther from the receiver, increasing spillage and attenuation losses. Ultimately, there exists a point where receiver design power can no longer be achieved at design conditions for a given solar field area. This point depends on key heliostat field design parameters including field layout, heliostats size, focus method, and heliostat optical error. In this work, we explore and characterize the performance trade-offs between heliostat size, focus method, and optical error using Monte Carlo ray-tracing simulations using NREL's high performance computing resources. The goal of this fundamental investigation is to understand practical heliostat design performance impacts that can be used to produce more cost-effective heliostat fields while still achieving plant thermal generation targets.

14 SOLAR ENERGY↗

Improvements in Reflected Target Non-intrusive Assessment (ReTNA)

Accurate optical surfaces are a primary driver of concentrated solar power plant performance. Errors in pointing and tracking mirrors, the canting of individual mirror facets, and the surface slope of the mirror itself can be caused by errors during assembly, transportation, wind loading, gravity, and many other sources. The tools that exist to measure these error sources today largely rely on fringe deflectometry (SOFAST, QDec, others), or photogrammetry with targets attached to the mirror surface. In 2022, NREL presented a new indoor optical measurement system to measure fully assembled heliostats during development and on the assembly line for quality assurance purposes, which has undergone significant development in the last year, including the installation of a new, larger laboratory setup. This system, called ReTNA (Reflected Target Non-intrusive Assessment), uses a printed pattern as a deflectometry target. Using printed pattern features as deflectometry targets instead of fringes allows the software to measure the surface slope in two dimensions, eliminating the need to for changing, projected targets. In the last year, NREL's ReTNA tool has been adapted to use a tall, thin target, that only spans one dimension of the mirror, and a camera moving on an automatic track system. We will present these new developments, including the new setup, target patterns, software methodology for fast, automatic optical analysis, and important lessons learned throughout the process. ReTNA results will be compared to established tools, to establish the uncertainty of this new method. ReTNA leverages recent improvements in computer vision and photogrammetry to remove as much careful calibration from the setup process as possible, making the tool low cost, simple, and portable. While it will not achieve the resolution of a fringe deflectometry system, its advantages make it well suited for CSP evaluation, and allow it to fill a different industry need.

concentrating solar power↗

Measurement of High-temperature Thermophysical Properties of Bulk and Coatings Using Modulated Photothermal Radiometry

This paper presents the development of instrumentation for the measurement of high-temperature thermal conductivity of bulk and coatings using a modulated photothermal radiometry (MPR) method, where a sample is heated by an intensity-modulated laser to probe into different layers of the sample. While MPR has been previously established, most of the previous studies only focus on the measurement at room temperature. The MPR has not been well studied for measurements of bulk and coating materials at high temperatures, which are increasingly important for a multitude of applications, such as materials used in the concentrating solar power (CSP) plants and the nuclear reactors. MPR is a non-contact technique that utilizes the intrinsic thermal emission from the specimens for thermometry, which is favorable for measurements at high temperatures in harsh environment. The authors designed and utilized a sample holder suitable for high temperature measurement up to 973 K with good temperature uniformity within the sample. The high-temperature MPR setup was validated by measuring bulk materials with known thermal conductivity. The setup and technique were then extended to the measurement of black solar-absorbing coatings of 10 to 50 μm thick on various substrates by modulating the frequency of the laser heating beam and the thermal penetration depth. Here, the studies showed that thermal conductivities of typical solar-absorbing coatings are 0.4 ~ 0.8 W m -1 K -1 , indicating a possibly large temperature drop within the coating under high solar irradiation flux, such as over 1000-sun for central solar towers in CSP plants.

14 SOLAR ENERGY↗

Heliostat Aiming Strategies for Arbitrary Flux Profiles for High Temperature Gas-Based Receivers

High temperature gas-based receivers are seen as one potential path toward achieving the next generation of concentrated solar power tower systems. A key challenge associated with high temperature, high pressure heat transfer fluids is the lifetime of receiver containment materials. Achieving the desired lifetime while also designing an efficient receiver requires implementation of unique flux profiles, tailored to place high fluxes at cold fluid injection points. An aimpoint selection methodology was developed in the present study to allow user-defined flux profiles to be prescribed for a receiver. The methodology was implemented in NREL's open-source software SolarPILOT, modifying the existing “image size priority” aimpoint strategy. A case study for a tubular gas-based receiver is presented, examining the effect of various parameters on the ability to replicate the desired flux profile.

41 EE - Solar Energy Technologies Office (EE-4S)↗

A Combined Computer Vision and Deep Learning Approach for Rapid Drone-Based Optical Characterization of Parabolic Troughs

Optical accuracy is a primary driver of parabolic trough concentrating solar power (CSP) plant performance, but can be damaged by wind loads, gravity, error during installation, and regular plant operation. Collecting and analyzing optical measurements over an entire operating parabolic trough plant is difficult, given the large scale of typical installations. Distant Observer, a software tool developed at the National Renewable Energy Laboratory, uses images of the absorber tube reflected in the collector mirror to measure both surface slope in the parabolic mirror and offset of the absorber tube from the ideal focal point. This technology has been adapted for fast data collection using low-cost commercial drones, but until recently still required substantial human labor to process large amounts of data. A new method leveraging advanced deep learning and computer vision tools can drastically reduce the time required to process images. This new method addresses the primary analysis bottleneck, identifying featureless, reflective mirror corner points to a high degree of accuracy. Recent work has shown promising results using computer vision methods. The combined deep learning and computer vision approach presented here proved highly effective and has the potential to further automate data collection and analysis, making the tool more robust. The method presented in this paper automatically identified 74.3% of mirror corners within 2 pixels of their manually marked counterparts and 91.9% within 3 pixels. This level of accuracy is sufficient for practical Distant Observer analysis within a target uncertainty. A commercial drone collected video of over 100 parabolic trough modules at an operating CSP plant to demonstrate the deep learning and computer vision method's usefulness in processing large amounts of data. These troughs were successfully analyzed using Distant Observer, paired with the new deep learning and computer vision algorithm, and can provide plant operators and trough designers with valuable insight about plant performance, operating strategies, and plant-wide optical error trends.

computer vision↗

Helical Fins for Concentrated Solar Receivers: Design Optimization and Entropy Analysis

Concentrated solar power (CSP) with thermal energy storage (TES) has the potential to achieve grid parity. This can be realized by operating CSP systems at temperatures above 700 °C with high-efficiency sCO 2 power cycles. However, operating CSP systems at such temperatures poses several challenges, among which the design of solar receivers to accommodate increased thermal loads is critical. To this end, this work explores and optimizes various swirl-inducing internal fin designs for solar receiver tubes. These fin designs not only improve the thermal performance of receiver tubes but also levelize temperature unevenness caused by non-uniform thermal loading. In this work, the geometric parameters of the fin designs are optimized to maximize the Nusselt number with a constraint on the friction factor. This optimization, however, is computationally intensive, requiring hundreds of simulation calls to computational fluid dynamics (CFD) models. Here, to circumvent this problem, surrogate models are used to approximate the simulation outputs needed during the optimization. In addition, this study also examines the fin designs from an entropy generation perspective. To this end, the entropy contributions from thermal and viscous effects are quantitatively compared while varying the operational Reynolds number.

14 SOLAR ENERGY↗

Wash Vehicle Fleet Sizing for Contingency Planning Against Dust Storms

Wash vehicles containing either high- or low-pressure water sprayers, a collection of rotating brushes, or a combination of these, are frequently utilized in concentrating solar power (CSP) plants to maintain a high level of optical efficiency in the solar field. In recent years, multiple modeling approaches have been developed to obtain fleet sizes and mirror-washing schedules that optimize the tradeoff of vehicle capital and use costs and labor versus lost revenues due to soiling. These planning models cover normal operating conditions well but do not consider rare events such as dust storms which can cause a significant reduction in receiver productivity, or shut down operations until most or all of the solar field's mirrors have been cleaned. To that end, we propose a methodology that evaluates whether additional capital should be deployed to hedge against these events by weighing the net present value of the expected benefits against the capital costs. The output of this method is a breakeven frequency, a metric we sue to determine whether an additional vehicle should be purchased to address the contingency of dust storms by comparing it to the expected annual storm frequency We develop a small collection of case studies using commercial-scale CSP tower plants and obtain breakeven frequencies that mostly fall between 0.1 and 1.0 storms per year, depending on the existing fleet size and storm severity.

concentrating solar power↗

Assessing geothermal/solar hybridization – Integrating a solar thermal topping cycle into a geothermal bottoming cycle with energy storage

Geothermal and concentrating solar power (CSP) technologies typically use heat at different temperatures in their commercial deployments. This enables a technically viable hybridization of a solar topping cycle and a geothermal bottoming cycle at locations where both resources are available. In this article, an underperforming geothermal power system based at Burley, Idaho is used as a baseline to investigate the technical and economic potential of such a hybrid cycle. A direct thermal energy storage (TES) system is also integrated to overcome the intermittency of the solar resource. Design and off-design behavior of key components are modelled to simulate the annual performance of the hybrid system on an hourly basis. The sizing of the solar field and thermal storage is investigated and is seen to significantly impact the annual electricity generation and efficiency. Various cost scenarios for the solar field and thermal energy storage are investigated. An economic metric - levelized cost of electricity (LCOE) - is used to optimize the solar field sizing and TES capacity. The hybrid plant converts the additional solar heat input into additional work with an efficiency of 32.9%. Retrofitting a geothermal plant with solar and eight hours of energy storage can achieve an LCOE of 0.136 $/kWhe in current cost scenarios and 0.081 $/kWhe in a future cost reduction scenario. Although the hybrid system cannot directly compete with current PV systems without batteries, it has an LCOE 32% lower than that of a PV-battery system. This paper provides insights into the research and development of the future grid with a high renewable energy penetration and encourages further study of energy hybridization for improved efficiencies and economics.

15 GEOTHERMAL ENERGY↗

The heat transfer coefficient associated with a moving packed bed of silica particles flowing through parallel plates

Concentrating Solar Power (CSP) with thermal energy storage has the potential to be a renewable energy technology with long duration, inexpensive energy storage. Higher temperature operation increases the conversion efficiency and reduces the cost of energy storage. Several emerging CSP designs utilize particles as the solar receiver due to their high temperature stability and low cost. In some designs, the particles are also used as the thermal energy storage (TES) media. In either configuration, an energy transfer is required between the hot particles and the working fluid in the power cycle in a Particle-to-Fluid Heat Exchanger (PtFHX). Understanding the heat transfer between a moving packed bed and a stationary surface is critical to the successful design of a PtFHX. In this paper, a test facility is described in which a moving packed bed of silica sand with particle size 100–600 μm is introduced into the channel formed by two parallel plates, one of which is heated. The effective static thermal conductivity of the particles used for the test are separately measured over the entire range of test temperatures. The inlet and outlet bulk temperatures of the particle flow are measured as are the surface temperatures at several axial locations along the centerline of the plate. The result is the measurement of heat transfer coefficient as a function of temperature for several velocities. The uncertainty of the measurements is presented and the results are compared to model results found in the literature.

14 SOLAR ENERGY↗

Modern deep neural networks for Direct Normal Irradiance forecasting: A classification approach

The escalating energy demand and the adverse environmental impacts of fossil-fuel use necessitate a shift towards cleaner and renewable alternatives. Concentrated Solar Power (CSP) technology emerges as a promising solution, offering a carbon-free alternative for power generation. The efficiency and profitability of CSP depend on the Direct Normal Irradiance (DNI) component of solar radiation; hence, accurate DNI forecasting can help optimize CSP plants’ operations and performance. The unpredictable nature of weather phenomena, particularly cloud cover, introduces uncertainty into DNI projections. Existing DNI forecasting models use meteorological factors, which are both challenging to estimate numerically over short prediction windows and expensive to model through data at a sufficiently high spatial and temporal resolution. This research addresses the challenge by presenting a novel approach that formulates DNI prediction as a multi-class classification problem, departing from conventional regression-based methods. The primary objective of this classification framework is to identify optimal periods aligning with specific operational thresholds for CSP plants, contributing to enhanced dispatch optimization strategies. We model the DNI classification problem using four advanced deep neural networks – rectified linear unit (ReLU) networks, 1D residual networks (ResNets), bidirectional long short-term memory (BiLSTM) networks, and transformers – achieving accuracies up to 93.5% without requiring meteorological parameters.

14 SOLAR ENERGY↗

Performance analysis of integrated Nuclear-Solar Energy system sharing same molten salt thermal energy storage

Advanced nuclear reactors may be deployed with integrated thermal energy storage to improve flexibility and maximize revenue. This presents opportunities for thermal integration with concentrating solar power (CSP) to generate component synergies and/or improve performance. Here in this study, a computational model is developed for an integrated nuclear and CSP system that both share the same molten salt thermal energy storage (TES). Optimized dispatch schedules are developed subject to various market conditions, and the ratio of the nuclear to CSP thermal output is also varied. Performance of the combined system is compared to separate nuclear and solar plants, to determine if there is an overall benefit that can be derived from sharing the TES. Given sufficient volatility in electricity prices (e.g., under CAISO market conditions), synergies of up to 8% in net revenue are observed as a result of sharing the same TES, primarily due to improved revenue from enabling operation of the turbine closer to its design point, as well as being able to better take advantage of higher electricity prices. The synergy benefits are largest when the nuclear and solar plants have similar thermal output. However, when prices are less volatile the opposite behavior can be observed and it can be preferable to operate the nuclear plant as a baseload generator.

14 SOLAR ENERGY↗