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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A finite difference informed random walker (FDiRW) solver for strongly inhomogeneous diffusion problems

In nature, many complex multi-physics coupling problems exhibit strong diffusivity inhomogeneity. For instance, in the context of radionuclide absorption by porous wasteform materials within a flowing waste stream, the difference of species’ diffusivity in solid and liquid phases spans by 3~8 orders of magnitude. To solve the diffusion equations with strongly inhomogeneous diffusivity, traditional discretization-based methods, such as the Finite Difference Method (FDM), require infinitesimally small time steps (<10 -10 ) as high spatial resolutions are employed in most microstructure evolution processes, leading to prohibitively high computational costs. Here, this work developed an integrated numerical approach (FDiRW: Finite Difference informed Random Walk) to tackle this challenge. The idea is that utilizing the Random Walk concept, the fast diffusion is modeled as a superposition of point source’s solution for a concentration distribution while FDM is used to obtain the point source’s solution at each node. A mesh-coarsening algorithm is developed to generate an exclusive coarse mesh for FDiRW approach to maximize its efficiency. The effectiveness of the coarse mesh-based FDiRW approach is validated by benchmarking Finite Difference solutions. Numerical results demonstrated that FDiRW achieves a remarkable 1000x computational efficiency improvement over FDM while preserving desired accuracy for a medium-sized model of 192 × 192 × 192 grids. Finally, as models scale up, a floating-point operations (PLOPs) analysis of the FDiRW algorithm reveals that its computational complexity grows quadratically in terms of the number of nodes employed in computation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nonlinear Scaling of Water–Ion Interactions and Dynamics in Alkaline Solutions

Water-ion interactions govern many solvent properties critical to solution-phase chemistry and the behavior of liquid water. The water-ion interactions in alkaline conditions were probed using two-dimensional infrared spectroscopy (2D IR), small-angle x-ray scattering (SAXS), and nuclear magnetic resonance spectroscopy (NMR). Energy transfer between the donor molecule KSeCN, used as a 2D IR probe, and the acceptor molecule NaOD was used to track the average separation distance of ions in a D 2 O solution, while SAXS measurements showed effects in the bulk D 2 O solvent. Here, we observe consistent nonlinear scaling in the SeCN - and OD - average separation distance as a function of NaOD concentration while bulk solution D 2 O-to-D 2 O average separation distance remained highly linear. Ultrafast measurements of solution dynamics via 2D IR and polarization-selective pump-probe spectroscopy show consistent scaling in correlation times as a function of concentration. These results suggests that the SeCN - and OD - anions participate in a water-ion network that significantly reduces the degrees of freedom for the distribution of ions in solution below the standard stochastic for ion distribution.

2D IR Spectroscopy↗
DOE OSTI2024

A Solution Method for the Filtered Lifting Line Theory

The filtered lifting line theory presents a continuous form of the inviscid momentum equations of flow over a lifting device, such as a wing or rotor blade, using body forces without mathematical singularities. This theory is also consistent with an actuator line representation of a lifting device. In this work, we present a reformulation of the equations in terms of the local flow angle along the line, which allows solving the stand-alone equations using multivariate root-finding algorithms. This approach can be used to obtain a fast, computationally inexpensive solution of the loading distribution along a wing without the need to perform computational fluid dynamic simulations. We study the requirements in terms of resolution in the spanwise direction and establish the criteria for spacing and minimum amount of points required along the blade to obtain converged solutions. The solutions are compared to results from large-eddy simulations, and we observed excellent agreement with less than a percent difference in quantities along the blade between the methods.

17 WIND ENERGY↗
DOE OSTI2026

Signatures of Thermoreversible Associations in X-ray and Neutron Scattering from Dilute Polyzwitterion Solutions

In aqueous solutions of polyzwitterions (PZs), an interplay between dipole–dipole interactions and hydration of zwitterionic groups can lead to thermoreversible associations, which have been difficult to detect in experiments. Here, in this study, we investigated dilute aqueous solutions of poly(1-(3-sulphonatopropyl)-2-vinylpyridinium) (P2VPPS) using small-angle X-ray and neutron scattering (SAXS and SANS) to probe the structure and neutron spin-echo (NSE) spectroscopy to probe dynamics. The SAXS and SANS data show that the correlation length increases with an increase in the concentration of P2VPPS for three different molecular weights. The addition of 0.1 M NaCl to one of the solutions led to almost no dependence of the correlation length on the concentration. Such a concentration dependence of the correlation length suggests the formation of clusters driven by thermoreversible associations in the solutions. The NSE measurements show that the solutions with a larger correlation length display slower relaxation, reflecting the reduced mobility of larger clusters. These results should be considered as signatures of thermoreversible associations in the solutions of P2VPPS. To establish a quantitative link between local structure (clusters) and dynamics in dilute solutions of P2VPPS, we combined a thermoreversible gelation theory for the structure of PZ solutions (Li, S.-F.; Muthukumar, M. Theory of Thermoreversible Gelation and Anomalous Concentration Fluctuations in Polyzwitterion Solutions. J. Chem. Phys. 2024, 161, 024903) with a model for the dynamics of the clusters (generalized Zimm model), developed in this work. Using such a theoretical framework, we have predicted the distribution of clusters in the solutions probed with SANS and SAXS. With the distributions, the generalized Zimm model has been used to extract the diffusion constant of the clusters and their characteristic size from the NSE data, where the latter agrees with the values estimated from the SAXS/SANS data. These findings confirm the presence of thermoreversible associations and establish a quantitative link between local structure (clusters) and dynamics in dilute solutions of P2VPPS. Furthermore, with growing interest in technological applications, this work can provide useful insights into the structural and dynamical properties of other PZ solutions.

field theory↗
DOE OSTI2026

Powered By CADET

The Capacity Expansion Decision Support for Distribution Networks (CADET) is a Python-based library and framework for creating electrical distribution system capacity planning tools for cost-effective, reliable power delivery. It enables the creation of modular, scalable, and extensible distribution capacity planning tools by providing a high-level optimization interface, parameter and options data managers, optimization constraint and objective libraries, generalized nomenclature, a system for tracking and modifying distribution network changes, optimization solution validation, and other capabilities. This webinar will describe 1) the motivation for creating CADET, 2) key designs, and 3) several use cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Mechanical Solution for Existing Conductors

The rapid growth in energy demand, driven by advancements in AI technology, renewable energy integration, and increased industrial activity, highlights the need for innovative solutions to improve the resiliency and efficiency of the power grid. This report details the fire testing of GridWrap’s Composite WiRe Wrap, to evaluate the wrap's ability to enhance conductor performance under wildfire-simulated conditions. Conductors were prepared and tested in a controlled environment at 400°C for 18 minutes, during which sag and temperature data were recorded. The results demonstrated that the unwrapped conductor sagged 3/16ths of an inch, while the WiRe Wrapped conductor sagged only 1/16th of an inch under identical conditions, indicating a significant improvement in mechanical performance. This project, conducted as part of a collaborative effort between BEA (Idaho National Laboratory’s managing contractor) and GridWrap, Inc., demonstrates the potential of grid-enhancing technologies like WiRe Wrap to reduce sag, increase grid resiliency, and support the future energy landscape. By validating the performance of such technologies in real-world scenarios, this work provides critical insights for industry adoption, benefiting both grid operators and U.S. taxpayers through improved reliability, reduced emissions, and enhanced energy delivery.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Enabling Evaluation of a Southern Company Distribution Feeder on NREL ADMS Test Bed: Cooperative Research and Development (Final Report)

The objective of this project is to enable evaluation of a Southern Company distribution feeder on the Advanced Distribution Management System (ADMS) test bed. The long-term goal is to evaluate a federated distributed energy resource (DER) management solution that aggregates DERs through either direct control, transactive control or an aggregator to provide bulk services while observing distribution system voltage and power constraints. The DER aggregation needs to be coordinated with an ADMS that is responsible for reliable power delivery across the distribution systems. This project takes the first step towards enabling such evaluation by deploying an ADMS from Oracle (Southern Company's ADMS supplier) with a Southern Company feeder at NREL.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

EMPOWERED Distributed Energy Resources Permit Accelerator Pilot

This report summarizes the EMPOWERED Distributed Energy Resources (DER) Permit Accelerator Pilot project. Its primary objective was to streamline the design, installation, permitting, and inspections of targeted Distributed Energy Resource (DER) solutions. Streamlining these processes is critical to strengthening and accelerating the adoption of DER solutions nationwide. Moreover, streamlined processes help expedite the clean energy transition and expand energy resilience by improving understanding and capability among key stakeholders like property owners, code officials, and the general workforce. The project team accomplished this by developing and deploying a set of design and permitting guides for simple DER solutions, which they rolled out via a permitting pilot program. The project team developed nine permitting and inspection guides for simple DER solutions, as follows: 1. Single-Family and Duplex: Electric Vehicle Service Equipment (EVSE), and Storage, Solar + Storage (each in two code cycles) 2. Multi-family and Office: EVSE, Storage, Solar + Storage (each in two code cycles) 3. A permitting process guide to support the implementation of the permitting guides. The guides cover key code requirements via plan review and field inspection checklists for code officials and building owners to follow to streamline the permitting and inspections process for DER solutions. Following the development of the initial set of guides, the project team formed two cohorts, each made up of four jurisdictions, to participate in the Permit Accelerator Pilot. Each cohort received training and technical assistance to support them in incorporating the guides into use. The project successfully engaged jurisdictions in two disparate US regions: Chelsea, Somerville, Natick, and Norwood in metro Boston; and Pima County, Town of Gilbert, Flagstaff, and Sedona in Arizona. Feedback gathered from the project was valuable in refining the guides to better address jurisdictional needs. After the pilot period, the project team developed final versions of the guides based on extensive feedback from the cohorts and from external technical peer review. Feedback included needs and barriers related to implementation, as well as detailed technical improvements from external peer review. The final guides were presented in a series of webinars with a national reach, with 192 attendees from 35 states in the live session of the final webinar, and the final guides are posted online and available for use nationwide. Key findings: • The most receptive jurisdictions were those adjacent to other jurisdictions that had already adopted similar initiatives. The least receptive jurisdictions were those in the midst of adopting new code cycles. • The most common barrier to jurisdictional adoption of new guidelines were internal administrative and process delays, more so than technical barriers. • The main technical barrier to adoption proved to be the concern of fire hazard risks posed by energy storage systems. There is some apprehension in the code enforcement community about the safety of the batteries. Education coordinated with fire and safety services will help alleviate concerns and increase confidence in the acceptance of innovative technologies. • Opportunities to further leverage and advance the guides and related resources include outreach, education, and jurisdictional support; updates to the resources to align with code cycle changes and local requirements; and advancements supporting emerging technologies.

14 SOLAR ENERGY↗
DOE OSTI2026

Machine Learning Approach to Modeling of Neutral Particles Transport in Plasma

A propagator‐based approach is investigated for Monte‐Carlo (MC) modeling of neutral particle transport in fusion boundary plasmas. The propagator is based on a Green's function for the neutral kinetic equation, which depends on the plasma profiles. A neural network (NN)‐based model for the propagator provides a fast and accurate solution for the neutral distribution function in plasma. Preliminary results from a small 1D test problem look encouraging. The proposed approach, a propagator‐based NN model for neutral transport in plasma, has potential for generalization to higher dimensions and efficient coupling with plasma models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Dynamics of heavy quarks in strongly coupled $\mathcal{N}$ = 4 SYM plasma

We calculate the probability distribution P(k) for a heavy quark with velocity v propagating through strongly coupled N = 4 SYM plasma in the ’t Hooft limit (N c → ∞, λ = g 2 N c → ∞) at a temperature T to acquire a momentum k due to interactions with the plasma. This distribution encodes the well-known drag coefficient η D and the transverse and longitudinal momentum diffusion coefficients κ T and κ L . The jet quenching parameter $\hat{q}$ can be extracted from P(k) for v = 1. Going beyond these known Gaussian characteristics of P(k), our calculation determines all of the higher order and mixed moments to leading order in 1/$\sqrt{λ}$ for the first time. These non-Gaussian features of P(k) include qualitatively novel correlations between longitudinal energy loss and transverse momentum broadening at nonzero v. We show that all higher moments scale characteristically with an effective temperature of the boosted plasma in the heavy quark rest frame, and we demonstrate that these non-Gaussian characteristics can be sizable in magnitude and even dominant in physically relevant situations. We use these results to derive a Kolmogorov equation for the evolution of the probability distribution for the total momentum of a heavy quark that propagates through strongly coupled plasma. This evolution equation accounts for all higher order correlations between transverse momentum broadening and longitudinal energy loss, which we have calculated from first principles. It reduces to a Fokker-Planck equation when truncated to only include the effects of η D , κ T and κ L . Remarkably, while heavy quarks do not reach kinetic equilibrium with the plasma if evolved with this Fokker-Planck equation, by showing that the Boltzmann distribution is a static solution of the all-order Kolmogorov equation that we have derived we demonstrate that heavy quarks do reach kinetic equilibrium if evolved with this equation. Our results thus provide a dynamically complete framework for understanding the thermalization of a heavy quark that may be initially far from equilibrium in the strongly coupled N = 4 SYM plasma — as well as new insight into heavy quark transport and equilibration in quark-gluon plasma.

Holography and Hydrodynamics↗
DOE OSTI2026

Reproducible benchmark for the SNAP 8 experimental reactor at operating conditions

This work presents fully reproducible multiphysics benchmark models of the Systems for Nuclear Auxiliary Power (SNAP) 8 Experimental Reactor at operating conditions with coolant flow. Wet experiment (with coolant, at power) validation benchmarks are presented using both deterministic (Serpent-Griffin) and Monte-Carlo (OpenMC-Cardinal) multiphysics frameworks coupled with thermal-hydraulic solvers in MOOSE. Reactivity coefficient measurements including fuel temperature, isothermal temperature, and power coefficients show good agreement with experiments, with discrepancies within experimental uncertainty. Reactivity worth experiments for coolant, samarium, and xenon poisoning are reproduced with differences under 200 pcm. Comparison between Serpent-Griffin and OpenMC-Cardinal frameworks reveal multiphysics coupling introduces positive reactivity effects (100-200 pcm) compared to uniform temperature and density fields at nominal operating conditions. Comparison between Serpent-Griffin and reference Serpent solution shows that power distributions maintain consistent radial and axial peaking behavior. All models, assumptions, thermophysical and thermomechanical properties, and material definitions are thoroughly documented with cited references; model inputs and model generating scripts are stored in the snapReactors GitHub repository.

SNAP↗
DOE OSTI2024

Bayesian reduced-order deep learning surrogate model for dynamic systems described by partial differential equations

We propose a reduced-order deep-learning surrogate model for dynamic systems described by time-dependent partial differential equations. This method employs space–time Karhunen–Loève expansions (KLEs) of the state variables and space-dependent KLEs of space-varying parameters to identify the reduced (latent) dimensions. Subsequently, a deep neural network (DNN) is used to map the parameter latent space to the state variable latent space. An approximate Bayesian method is developed for uncertainty quantification (UQ) in the proposed KL-DNN surrogate model. The KL-DNN method is tested for the linear advection–diffusion and nonlinear diffusion equations, and the Bayesian approach for UQ is compared with the deep ensembling (DE) approach, commonly used for quantifying uncertainty in DNN models. It was found that the approximate Bayesian method provides a more informative distribution of the PDE solutions in terms of the coverage of the reference PDE solutions (the percentage of nodes where the reference solution is within the confidence interval predicted by the UQ methods) and log predictive probability. The DE method is found to underestimate uncertainty and introduce bias. For the nonlinear diffusion equation, we compare the KL-DNN method with the Fourier Neural Operator (FNO) method and find that KL-DNN is 10% more accurate and needs less training time than the FNO method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Full time-dependent SOLPS-ITER simulation of the SPARC tokamak: actuator design for particle and divertor condition control *

Abstract This paper presents the application of full time-dependent SOLPS-ITER simulations for actuator design in the SPARC tokamak. This study employs both the EIRENE module, a neutral solver, and the B2.5 plasma module in a time-dependent mode. This is in contrast to most SOLPS simulations, which focus on steady-state solutions, where the neutral distribution is evolved without any time limit or for a time step of 1 ⋅ 10 − 3 second, which is several orders of magnitude larger than the fluid plasma time step. The time-dependent EIRENE was tested with a fixed B2.5 background and compared with a simple conductance based model in a simplified pump chamber geometry. This comparison aimed to verify the reliability of the neutral relaxation timescale derived from the time-dependent EIRENE. Subsequently, a full time-dependent simulation was performed in a realistic geometry, with the Monte-Carlo neutral time step synchronized with the plasma fluid time step. The numerical setup of the code, including relative time steps and the size of the census data used to store Monte-Carlo particle information is considered. The full-time dependent simulations are then applied to inform the design of the SPARC louver structure, which affects divertor plasma parameters by regulating the neutral conductance from the divertor to the pump. The response of the plasma and neutral parameters was captured on a timescale that enables the design of the actuator to consider time-dependent control capability. It was found that changing the louver opacity has an equivalent effect as varying the gas throughput via puff actuation. Therefore, equivalent divertor plasma conditions can be obtained from both actuators, while the neutral pressure distribution in the pump and divertor differs for each actuator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Utilization of Novel (KNbO 3 ) 1− x (Ba 2 FeNbO 6 ) x ( x = 0.1, 0.2, 0.3) Solid Solutions for Efficient Photo‐Assisted Fenton Degradation of Methylene Blue Dye

Novel (KNbO 3 ) 1− x (Ba 2 FeNbO 6 ) x ( x = 0.1, 0.2, 0.3) solid solutions corresponding to K 0.82 Ba 0.18 Fe 0.09 Nb 0.91 O 3 , K 0.64 Ba 0.36 Fe 0.18 Nb 0.82 O 3 , and K 0.46 Ba 0.54 Fe 0.27 Nb 0.73 O 3 compounds have been synthesized via molten salt method. X‐ray diffraction confirms the formation of solid solutions, while transmission electron microscopy combined with energy‐dispersive spectroscopy results demonstrates a homogeneous distribution of elements. The obtained solid solutions crystallized in a cubic crystal structure, whereas the parent KNbO 3 possesses an orthorhombic structure. The wide bandgap semiconductor KNbO 3 transformed into a visible‐light‐active material, with its bandgap energy reduced from 3.56 eV to ≈2.4 eV. The substitution of K in KNbO 3 with Ba is responsible for structural modification from orthorhombic to cubic symmetry, whereas both structural modification and the substitution of Nb with Fe correlated with optical properties. The photocatalytic activities of all obtained solid solutions are improved compared with the parent KNbO 3 and Ba 2 FeNbO 6 compounds for photocatalytic degradation of methylene blue (MB) dye. Among the series of solid solutions, K 0.82 Ba 0.18 Fe 0.09 Nb 0.91 O 3 photocatalysts show the highest MB removal efficiency owing to its relatively higher surface area, suppressed charge carrier recombination, and more negative conduction band edge. Moreover, K 0.82 Ba 0.18 Fe 0.09 Nb 0.91 O 3 photocatalyst (0.1 g) combined with hydrogen peroxide (H 2 O 2 ) to form a novel photo‐Fenton system, achieving almost complete degradation of 100 mL of 10 mg L −1 MB dye in 30 min.

Avcıoğlu, Celal [Technische Universität Berlin, Fa↗
DOE OSTI2024

Determining reference standard strength for neutron-irradiated reduced activation ferritic/martensitic steel F82H by Bayesian method

The deterministic approach widely adopted in the design of structural components relies on systematically defined design limits using empirically determined safety factors. However, this approach is not always appropriate because structures are subjected to a variety of loads in the practical environment, which may result in excessively conservative design limits. In recent years, a more rigorous probabilistic approach that incorporates material strength distributions has become an important solution. In the probabilistic approach, the probability density functions of material strength properties underpin the design criteria. Here, the objective of this study is to identify the density distribution functions that best describe tensile properties of irradiated F82H to define a reference strength for DEMO design. Due to the limited number of existing data, this study specifically employs a Bayesian prediction method based on Monte Carlo simulations to determine a material reference value with statistical reliability and to investigate its effectiveness. For example, the dependence of tensile properties of 300 °C irradiated materials on irradiation damage and the range predicted by 95% Bayesian estimation was evaluated. As a statistical model for the dose dependence of statistical parameters, the normal distribution exhibited a better fit for 0.2% proof strength and tensile strength, whereas the distribution of total elongation data gave comparable reference values for both the normal and Weibull distribution models. Both models gave comparable criteria for the distribution of total elongation data. The Weibull model also gave better results for uniform elongation. The function best describing the model was a logarithmic law for both 0.2% proof strength and tensile strength, while a power law for both total and uniform elongation, which allowed for more comprehensive data prediction of irradiation data with statistical accuracy for DEMO reactor design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

LandScan Global 2023: Silver Edition

For a quarter of a century, the LandScan Global (LSG) project has annually released a global, high-resolution gridded population dataset representing the ambient or unwarned population at a 30 arcsecond resolution. LSG supports a range of applications such as emergency management, disaster response, and human health and security for understanding populations at risk. The 2023 release of LSG, the LandScan Silver Edition, represents a major methodological leap forward while also leveraging previous knowledge—the previous year was the baseline for the current annual update carrying forward valuable knowledge of the built environment for the past quarter century—to train the machine learning models. Compared with annual releases over the past 24years, multiple advancements were made to different aspects of the methodology to achieve reproducibility, transparency, and consistent global propagation of solutions to modeling or population distribution issues identified during the review process. These novel changes include incorporation of the latest available geospatial inputs across the globe, machine learning models instead of manual modifications, population feature importance analysis, open-source solutions vs. proprietary software, generation of multiple global versions, analytic validations, and human-in-the-loop revisions to produce the final version. Additionally, algorithms—such as anomaly detection—were introduced to quickly identify areas of focus to develop a new and robust systematic review. Significant changes in modeled population distributions were observed between the 2022 and 2023 releases, largely attributable to improvements in data and methods and discussed thoroughly within this report. In summation, the LandScan Silver Edition leverages the best of the past quarter century of LSG legacy knowledge and continues a tradition of applying cutting-edge enhancements to serve as a new benchmark for accurate, actionable gridded population data

Lebakula, Viswadeep↗
DOE OSTI2024

Accurate data-driven surrogates of dynamical systems for forward propagation of uncertainty

Stochastic collocation (SC) is a well-known non-intrusive method of constructing surrogate models for uncertainty quantification. In dynamical systems, SC is especially suited for full-field uncertainty propagation that characterizes the distributions of the high-dimensional solution fields of a model with stochastic input parameters. However, due to the highly nonlinear nature of the parameter-to-solution map in even the simplest dynamical systems, the constructed SC surrogates are often inaccurate. Here, this work presents an alternative approach, where we apply the SC approximation over the dynamics of the model, rather than the solution. By combining the data-driven sparse identification of nonlinear dynamics framework with SC, we construct dynamics surrogates and integrate them through time to construct the surrogate solutions. We demonstrate that the SC-over-dynamics framework leads to smaller errors, both in terms of the approximated system trajectories as well as the model state distributions, when compared against full-field SC applied to the solutions directly. We present numerical evidence of this improvement using three test problems: a chaotic ordinary differential equation, and two partial differential equations from solid mechanics.

42 ENGINEERING↗
DOE OSTI2024

Empowering Rural Electrification in Honduras: An Integrated Assessment of PV/BESS and Productive Uses of Electricity in Gracias a Dios

Honduras faces significant challenges in its energy sector, particularly in rural areas where access to reliable and affordable electricity remains limited. The flagship rural electrification initiative for Honduras Secretary of Energy (SEN) is the Politica de Acceso Universal a la Electricidad (PAUEH - Universal Electricity Access Policy), a key solution for addressing this energy poverty is the deployment of more than 1700 distributed solar and hybrid mini-grid solutions. In late 2023 as a first step towards supporting SEN's electrification efforts, the National Renewable Energy Laboratory (NREL) developed a literature review of SEN electrification policy documents and conducted a series of technical capacity-building workshops with SEN and other energy sector stakeholders in Honduras focused on using NREL's open-source REopt tool to conduct techno-economic assessments and develop least-cost optimizations for potential solar + storage mini-grid systems. Building on some initial capacity building on mini-grid modeling, the National Renewable Energy Laboratory (NREL) worked with SEN to develop a detailed techno-economic assessment for electrifying two schools, a healthcare clinic, and a hospital in a hypothetical community within the department of Gracias a Dios. The analysis also evaluates the business case for cold storage productive use of energy (PUE) applications for the fisheries value chain and how the incorporation of these PUE loads potentially impacts both the viability of the PV+BESS solutions as well as local economic development. By assessing the potential for deployment of integrated PV/BESS systems to both support critical community services like education and healthcare, as well as potential for downstream enterprise and economic development, this analysis represents a first step that can help to inform specific strategies for development of pilot PV+BESS projects aligned with national priorities and sector level planning under PAUEH.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗