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At least 685 records · Page 38

Grid Integration of Renewable Energy and Energy Storage

Grid integration of renewable energy and energy storage requires forward-looking planning process, and increased emphasizes on reliability, resilience, and equity. Power-electronics based energy generation including solar, wind, distributed energy resources (DERs), and various types of grid-tied energy storage and emerging loads, are reshaping grid operator's understanding on interconnection level performance and responses. This paper will present the ongoing work at PNNL related to power electronics R&D, energy modeling and analysis, and a wide spectrum of grid stability studies and technologies in support of grid integration of renewable energy and energy storage.

Power Electronics, grid integration of renewable e↗

Network Constraints Consideration for Grid-Edge Energy Management System

Increased deployment of distributed energy resources (DER) in distribution system is bringing need for enhanced grid intelligence, control, and flexibility. This is significant at the edge of the grid where DERs, loads or microgrids are located. Integrated DERs in a distribution system need to follow grid codes to avoid violations that results in DER disconnection. To comply with grid code requirements (e.g. IEEE 1547-2018) at the grid edge level, network constrained grid edge energy management system (GEEMS) is proposed in this paper. The objective of GEEMS is to provide economic solution for active and reactive power dispatch set-points at each interval and ensure voltage regulation to support secure interconnection of the grid edge segment to the distribution system. To evaluate the proposed GEEMS framework, four DERs are included into IEEE 13 bus system. GEEMS outperforms the existing economic dispatch-based energy management system by reducing the voltage violation.

Electric vehicle depot charging station↗

Multi-layered Energy Management Framework for Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, and Forecast Uncertainties

To achieve a cost-effective and expeditious charging experience for extreme fast charging station (XFCS) owners and electric vehicle (EV) users, the optimal operation of XFCS is crucial. It is however challenging to simultaneously manage the profit from energy arbitrage, the cost of demand charges, and the degradation of a battery energy storage system (BESS) under uncertainties. This paper, therefore, proposes a multi-layered multi-time scale energy flow management framework for an XFCS by considering long- and short-term forecast uncertainties, monthly demand charges reduction, and BESS life degradation. In the proposed approach, an upper scheduling layer (USL) ensures the overall operation economy and yields optimal scheduling of the energy resources on a rolling horizon basis, thereby considering the long-term forecast errors. A lower dispatch layer (LDL) takes the short-term forecast errors into account during the real-time operation of the XFCS. Per the latest research, monthly demand charges can be as high as 90% of the total monthly bills for EV fast charging stations; to this end, this paper takes the first attempt at the reduction of demand charges cost by considering the trade-off between the energy cost and monthly demand charges. Contrasting literature, this work allocates an energy reserve in the BESS stored energy to deal with the impact of short-term forecast errors on the optimized real-time operation of the XFCS. Moreover, degradation modeling considers the trade-off between short-term benefits and long-term BESS life degradation. As a result, case studies and a comparative analysis prove the efficacy of the proposed framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Convective Heat Transfer Potential of Particles/Airflow Through Single Cell Thick Additively Manufactured Octet-Shaped Lattice Frame Material

Abstract Particle-to-Supercritical Carbon Dioxide (sCO2) heat exchangers are one of the most critical components of the next-generation Concentrating Solar Power (CSP) plants. There have been several efforts to enhance the overall heat exchanger performance which essentially comprises of thermal resistances offered by sCO2 channel, wall (separating sCO2 with particles) thickness, particle-wall contact resistance and particle-side effective heat transfer coefficient. This study is focused towards reducing the particle side thermal resistance by incorporating single unit cell thick reticulated Octet lattice frame structures on the falling particle side to enhance the effective thermal conductivity of the particle channel and to enhance convective heat transfer between the falling particles and the solid phase of the falling particle channel (endwalls and fibers). Steady-state experiments were conducted to measure the effective thermal conductivity of lattice frame material for two cases: a) when void space was occupied by air, b) when void space was occupied with particles. Further, convective heat transfer experiments have been conducted with both air (steady-state) and particles (quasi steady-state) as “working fluid” for panels sandwiching the Octet array. Three different lattice porosities ranging from 0.75 to 0.9 have been tested for a wide range of air flow rates and a fixed particle flow rate (highest potential).

Aider, Youssef↗

solar-fingerprinting

An algorithm for creating a low-dimensional representation (fingerprint) of daily photovoltaic solar power generation signals.

Meyers, Bennet↗

H2Integrate [SWR-23-31]

H2Integrate(H2I) is an open-source Python package for hybrid systems engineering design and technoeconomic analysis. It models and optimizes hybrid energy plants that produce electricity, hydrogen, ammonia, steel, and other products. H2Integrate is designed to be flexible and extensible, allowing users to create their own components and models for various energy systems. The tool currently includes distributed energy generation (wind, solar, wave, tidal), battery storage, hydrogen, ammonia, methanol, and steel technologies. Other elements such as desalination systems, pipelines, compressors, and storage systems can also be included as developed by users. Some modeling capabilities in H2Integrate are provided by integrating existing tools, such as HOPP, PySAM, ORBIT, and ProFAST. The H2Integrate tool is built on top of NASA's OpenMDAO framework, which provides a powerful and flexible environment for modeling and optimization.

King, Jennifer [National Renewable Energy Laborato↗

Characterization of Particle and Heat Losses from a High-Temperature Particle Receiver

High-temperature particle receivers are being pursued to enable next-generation concentrating solar thermal power (CSP) systems that can achieve higher temperatures (> 700 °C) to enable more efficient power cycles, lower overall system costs, and emerging CSP-based process-heat applications. The objective of this work was to develop characterization methods to quantify the particle and heat losses from the open aperture of the particle receiver. Novel camera- based imaging methods were developed and applied to both laboratory-scale and larger 1 MW t on-sun tests at the National Solar Thermal Test Facility in Albuquerque, New Mexico. Validation of the imaging methods was performed using gravimetric and calorimetric methods. In addition, conventional particle-sampling methods using volumetric particle-air samplers were applied to the on-sun tests to compare particle emission rates with regulatory standards for worker safety and pollution. Novel particle sampling methods using 3-D printed tipping buckets and tethered balloons were also developed and applied to the on-sun particle-receiver tests. Finally, models were developed to simulate the impact of particle size and wind on particle emissions and concentrations as a function of location. Results showed that particle emissions and concentrations were well below regulatory standards for worker safety and pollution. In addition, estimated particle temperatures and advective heat losses from the camera-based imaging methods correlated well with measured values during the on-sun tests.

14 SOLAR ENERGY↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Characterization of Particle and Heat Losses from a High-Temperature Particle Receiver (2 nd Ed)

High - temperature particle receivers are being pursued to enable next - generation concentrating solar thermal power (CSP) systems that can achieve higher temperatures (> 700 C) to enable more efficient power cycles, lower overall system costs, and emerging CSP - based process - heat applications. The objective of this work was to develop characterization methods to quantify the particle and heat losses from the open aperture of the particle receiver. Novel camera - based imaging methods were developed and applied to both laboratory - scale and larger 1 MW t on - sun tests at the National Solar Thermal Test Facility in Albuquerque, New Mexico. Validation of the imaging methods was performed using gravimetric and calorimetric methods. In addition, conventional particle - sampling methods using volumetric particle - air samplers were applied to the on - sun tests to compare particle emission rates with regulatory standards for worker safety and pollution. Novel particle sampling methods using 3 - D printed tipping buckets and tethered balloons were also developed and applied to the on - sun particle - receiver tests. Finally, models were developed to simulate the impact of particle size and wind on particle emissions and concentrations as a function of location. Results showed that particle emissions and concentrations were well below regulatory standards for worker safety and pollution. In addition, estimated particle temperatures and advective heat losses from the camera - based imaging methods correlated well with measured values during the on - sun tests.

14 SOLAR ENERGY↗

Common Information Model for Electromagnetic Transients (CIM for EMT): CRADA 533 [Abstract only}

The control and protection functions of inverter-based resources (IBR) have raised concerns with bulk system reliability. Most of the current interest lies with solar photovoltaic generation but increasing amounts of storage would pose the same risks. Newer North American Electric Reliability Corporation (NERC) guidelines call for electromagnetic transient (EMT) studies of IBR and recommend that transmission operators collect distributed energy resource (DER) data to support such modeling. IEEE Standard P2800.1 is defining tests for model parameterization, so good model data should become available from inverter vendors. (EMT studies also apply to large power transformer reliability, and transformer vendors can provide EMT models.) Utilities don’t currently have the rest of the bulk system represented for EMT studies at large scale. An International Electrotechnical Commission (IEC) standard Common Information Model (CIM) provides a way of supporting these detailed models from physical asset data, e.g., conductors, towers, transformer data sheets, control block diagrams, while avoiding software vendor lock-in. CIM-for-EMT, with proposed schema extensions and open-source converters, provides a way to exchange EMT data between organizations and tools. This project leverages Office of Electricity (OE) funding of CIM-for-EMT code base through the GridAPPS-DTM project, and of GridPACKTM (parallelized transmission solver), for interoperability testing in CIM-for-EMT. The project also leverages partner PGSTech investments in EMTP® interoperability with CIM.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Novel Catalytic Membrane Reactor for DME Synthesis from Renewable Resources

Production of liquid fuels or chemicals from CO 2 (captured from the air or flue gases) and renewable hydrogen presents a new approach to producing clean fuels domestically. While significant progress has been made in the area of renewable electricity generation from solar and wind, a large gap remains with respect to the production of renewable liquid fuels/chemicals. Other processes for producing liquid fuels/chemicals from renewable electricity are constrained by thermodynamic limitations, making them prohibitively expensive and impractical. The team is overcoming these limitations and developing catalytic membrane reactor processes with high yields and low energy penalties. Supported by the Advanced Research Projects Agency-Energy (ARPA-E) of the US Department of Energy (DOE), GTI Energy and partners have been developing a technology for the production of renewable dimethyl ether (DME) from carbon dioxide (CO 2 ) and renewable hydrogen (H 2 ) using a novel catalytic membrane reactor and demonstration of this system at a scale of 1 kg/day. DME is a clean-burning, non-toxic fuel with a high cetane value (55-60), making it an excellent diesel alternative. DME can be stored as a liquid under moderate pressure, eliminating the need for the high-pressure containers used for CNG or cryogenics, as in the case of LNG. DME is also approved as a renewable fuel under the U.S. Environmental Protection Agency’s Renewable Fuels Standard (RFS), making it eligible for Renewable Identification Numbers (RINs) credits. By producing DME through the catalytic conversion of captured CO 2 and renewable H 2 , this process will produce renewable liquid transportation fuel and a means of large-scale utilization of captured CO 2 . In the DME synthesis process, CO 2 and H 2 are fed to a hollow fiber catalytic membrane reactor at 300-600 psig that contains a bi-functional catalyst that combines two reactions, methanol synthesis (CO 2 + 3H 2 → CH 3 OH + H 2 O) and methanol dehydration (2CH 3 OH → CH 3 OCH 3 + H 2 O), into a one-step process to produce DME. The bifunctional catalyst converts methanol to DME, enabling higher overall CO 2 conversion. A Cu/ZnO/ZrO 2 /Al 2 O 3 (CZZA) catalyst is used for methanol synthesis and is coupled with a zeolite catalyst H-ZSM-5 for dehydration. This one-step process intensifies a process that would otherwise require multiple reaction steps. However, combining these two reactions results in increased water production which inhibits catalytic activity. Here, the Na + -gated, water-transport membrane (Science, vol. 367, pp. 667, 2020), removes water in situ, shifting the thermodynamic equilibrium towards product formation while decreasing kinetic inhibition from water adsorption onto the catalyst surface. The Na + gated, water-transport nanochannel membrane showed H 2 O/CO 2 selectivity of 560 at 250 °C and 300 psig for H 2 O/CO 2 /CO/H 2 /MeOH gas mixtures. The selectivities of H 2 O/H 2 , H 2 O/CO, and H 2 O/MeOH were 190, 170, and 80, respectively. In a laboratory-scale membrane reactor, DME synthesis testing using this membrane, a DME production rate of 440 g DME /kg cat /h was achieved at 260 °C and 550 psig. Compared to the packed bed reactor, the CO 2 conversion and DME production rate in the membrane reactor were 80% and three times higher, respectively. A prototype test system (1 kg/day) was designed, constructed, and tested. A DME production rate of 1.31 kg/day and a DME productivity of 360 g/h/kg were achieved in the prototype membrane reactor. Good stability was demonstrated during 150-h continuous operation and multiple startups/shutdowns tests.

10 SYNTHETIC FUELS↗

Performance Evaluation of a Prototype Moving Packed-Bed Particle/sCO 2 Heat Exchanger

Particle heat exchangers are a critical enabling technology for next generation concentrating solar power (CSP) plants that use supercritical carbon dioxide (sCO 2 ) as a working fluid. This report covers the design, manufacturing and testing of a prototype particle-to-sCO 2 heat exchanger targeting thermal performance levels required to meet commercial scale cost targets. In addition, the the design and assembly of integrated particle and sCO 2 flow loops for heat exchanger performance testing are detailed. The prototype heat exchanger was tested to particle inlet temperatures of 500 °C at 17 MPa which resulted in overall heat transfer coefficients of approximately 300 W/m 2 -K at the design point and cases using high approach temperature with peak values as high as 400 W/m 2 -K

14 SOLAR ENERGY↗

Monitoring of Photovoltaic (PV) Performance and Degradation: Integrated Renewable Energy Systems (IRES) - PV Monitoring Task

The Integrated Renewable Energy System (IRES) testbed demonstration at the Pacific Northwest National Laboratory (PNNL) Sequim campus includes development of a suite of capabilities for tracking the performance of photovoltaic (PV) renewable energy components located on a floating platform (floating PV) and on a shoreline building rooftop. The marine environment represents potentially harsh and corrosive conditions for PV modules. Compared to terrestrial PV, potential concerns for offshore PV arising from high humidity and occasional contact with saltwater, marine wildlife, and aquaculture. These environmental factors can reduce electricity generation efficiency and increase the risk of electrical faults, polymer insulation or jacketing degradation and hydrolysis of the PV cell encapsulant materials. Offshore PV modules may also be exposed to lower temperatures and buoyant and vibrating motions with a floating platform. It is not clear how the long-term performance of floating PV will be affected by these factors. To understand expected energy generation through solar cells on a floating platform, monitoring of the performance of PV modules in the marine environment is needed. This report outlines a plan for long-term testing of IRES PV components utilizing resources of the PNNL Material Aging and Detection (MAaD) Science team and the Marine and Coastal Research Laboratory (MCRL). Equipment applicable for onsite testing and real-time monitoring of the PV performance associated with environmental conditions including temperature, solar irradiance, shading and soiling is included. In case of performance loss, equipment for fault detection, failure analysis, material testing, and further troubleshooting are also available. Through establishment of this capabilities, the enabling IRES project sets the stage for future research to advance off-shore and near-shore energy options for businesses and communities.

14 SOLAR ENERGY↗

Conversion Kinetics and Ionic Conductivity in Na-β”-Alumina + YSZ (Naβ”AY) Sodium Solid Electrolyte via Vapor Phase Conversion Process

Sodium ion batteries have been receiving increasing attention and may see potential revival in the near future, particularly in large-scale grid energy storage coupling with wind and solar power generation, due to the abundant sodium resources, low cost, and sufficiently high energy density. Among the known sodium ion conductors, the Na-β”-alumina electrolyte remains highly attractive because of its high ionic conductivity. This study focuses on the vapor phase synthesis of a Na-β”-Alumina + YSZ (Naβ”AY) composite sodium electrolyte, which has higher mechanical strength and stability than conventional single phase β”-Alumina. The objectives are the measurement of conversion kinetics through a newly developed weight-gain based model and the determination of sodium ionic conductivity in the composite electrolyte. Starting samples contained ~70 vol% α-Alumina and ~30 vol% YSZ (3 mol% Y 2 O 3 stabilized Zirconia) with and without a thin alumina surface layer made by sintering in air at 1600 °C. The sintered samples were placed in a powder of Na-β”-alumina and heat-treated at 1250 °C for various periods. Sample dimensions and weight were measured as a function of heat treatment time. The conversion of α-Alumina in the α-Alumina + YSZ composite into Naβ”AY occurred by coupled diffusion of sodium ions through Na-β”-alumina and of oxygen ions through YSZ, effectively diffusing Na2O. From the analysis of the time dependence of sample mass and dimensions, the effective diffusion coefficient of Na 2 O through the sample, D eff , was estimated to be 1.74 x 10 -7 cm2 s -1 , and the effective interface transfer parameter, k eff , was estimated as 2.33 x 10 -6 cm s -1 . By depositing a thin alumina coating layer on top of the bulk composite, the chemical diffusion coefficient of oxygen through single phase Na-β”-alumina was estimated as 4.35 x 10 -10 cm 2 s -1 . An AC impedance measurement was performed on a fully converted Naβ”AY composite, and the conductivity of the composite electrolyte was 1.3 x 10 -1 S cm -1 at 300 °C and 1.6 x 10 -3 S cm -1 at 25 °C, indicating promising applications in solid state or molten salt batteries at low to intermediate temperatures.

36 MATERIALS SCIENCE↗

Modeling the Impact of Grain Size on Corrosion Behavior of Ni-Based Alloys in Molten Chloride Salt via Cellular Automata

Molten chloride salts hold significant promise as both thermal transfer and storage media for next-generation concentrated solar power (CSP) systems. However, molten chlorides pose a considerable corrosion risk to structural materials, particularly Ni-based alloys. One approach to enhancing corrosion resistance is through the optimization of grain structure; however, it remains uncertain whether increasing or decreasing grain size enhances corrosion resistance. A cellular automata (CA) program was developed to evaluate the interplay between grain size and corrosion in Ni-based alloy. Our CA program tracks alloy composition, surface roughness, and thickness loss via a graphical user interface, displaying corrosion and diffusion status, and multiple user input cards for tuning the simulation. CA simulations of Inconel 625 indicate enhanced corrosion resistance with increased grain size, with passivating oxides offering limited protection. Additionally, the temporal evolution of alloy surface roughness demonstrates notable fluctuations, with abrupt increases attributed to corrosion along vertical grain boundaries and sudden decreases to grain detachment from the protective film.

Materials Science↗

Generation and Life Cycle of Solar Spicules

The physical mechanism for the creation of solar spicules is proposed with three stages of their life cycle. It is assumed that at stage I the density hump is formed locally in the x-y plane in the lower chromosphere in the presence of temperature gradients of electrons and ions along the z-axis (the vertical direction). In this region, the density structure of quasi-neutral (n i ≃ n e = n) plasma after taking birth is accelerated in the vertical direction owing to the thermal force F th ∝ ∇n(x, y, t) × (∇T e + ∇T i ). The exact time-dependent analytical solution of two-fluid plasma equations is presented assuming that density is maximum at the center of the density structure and decays away from it gradually. The 2D density structure is created as a step function H(t) in time at the bottom of the chromosphere, and consequently, the vertical plasma velocity turns out to be the ramp function of time R(t) = tH(t), whereas the source term S(x, y, t) for the density follows the delta function δ(t) form. The upward acceleration a = a(x, y) $\hat{z}$ produced in this density structure is greater than the downward constant solar acceleration −g ⊙ in the chromosphere. In the transition region, the temperature gradients are steeper; therefore, the upward acceleration increases in magnitude g ⊙ ≪ a and the density hump spends less time there. This is stage II of its life cycle. In stage III, the density structure enters into the corona, where the gradients of temperatures vanish and the structure decelerates to zero velocity under the action of the solar gravitational force.

79 ASTRONOMY AND ASTROPHYSICS↗

Physically Motivated Deep Learning to Superresolve and Cross Calibrate Solar Magnetograms

Abstract Superresolution (SR) aims to increase the resolution of images by recovering detail. Compared to standard interpolation, deep learning-based approaches learn features and their relationships to leverage prior knowledge of what low-resolution patterns look like in higher resolution. Deep neural networks can also perform image cross-calibration by learning the systematic properties of the target images. While SR for natural images aims to create perceptually convincing results, SR of scientific data requires careful quantitative evaluation. In this work, we demonstrate that deep learning can increase the resolution and calibrate solar imagers belonging to different instrumental generations. We convert solar magnetic field images taken by the Michelson Doppler Imager (resolution ∼2″ pixel −1 ; space based) and the Global Oscillation Network Group (resolution ∼2.″5 pixel −1 ; ground based) to the characteristics of the Helioseismic and Magnetic Imager (resolution ∼0.″5 pixel −1 ; space based). We also establish a set of performance measurements to benchmark deep-learning-based SR and calibration for scientific applications.

Muñoz-Jaramillo, Andrés (ORCID:0000000247160840)↗

Modeling Dense Particle Flow in Multistage and Obstructed Flow Receivers Using High Fidelity Simulations

Particles are a leading contender for next-generation, concentrating solar power technologies, and the design of the particle receiver is critical to minimize the levelized cost of electricity. Falling particle receivers (FPRs) are a viable receiver concept, but many new designs feature complex particle obstructions that include dense discrete phase flows. This creates additional challenges for modeling as particle-to-particle interactions (i.e., collisions) and particle drag become more complex. To improve upon existing modeling strategies, a CFD-DEM simulation capability was created by coupling two independent codes: Sierra/Fuego and LAMMPS. A suitable receiver model was then defined using a traditional continuum-based model for the air and a granular model for the particle curtain. A sensitivity study was executed using this model to determine the relevance of different granular model inputs on important quantities of interest in obstructed flow FPRs: the particle velocity and curtain opacity. The study showed that the granular model inputs had little effect on the particle velocity magnitude and curtain opacity after an obstruction.

Mills, Brantley↗