Search NASA⌕ Search

SEARCH · Search NASA

Results for “Data aggregation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

PV Fleet Performance Data Initiative Program and Methodology

The US Department of Energy’s PV Fleet Performance Data Initiative has been launched in order to collect and evaluate production data across multiple PV fleet partners. Performance statistics are anonymized, aggregated and shared to represent a snapshot of the US commercial and utility-scale fleet. Production data have been collected from over 1500 systems representing more than 1.3 GWdc capacity. Preliminary analysis indicates median performance loss rates are in line with previous publications of system degradation, on the order of –0.6%/yr to –0.9%/yr (preliminary numbers subject to change). These values are higher than module-only degradation rates which are often used in pro-forma estimates of project performance and economics, potentially exposing owner/operators to increased risk if systems under-perform over time.

41 EE - Solar Energy Technologies Office (EE-4S)↗
NASA NTRS2007

Exploring and Visualizing A-Train Instrument Data

The succession of US and international satellites that follow each other in close succession, known as the A-Train, affords an opportunity to atmospheric researchers that no single platform could provide: Increasing the number of observations at any given geographic location.. . a more complete "virtual science platform". However, vertically and horizontally, co-registering and regridding datasets from independently developed missions, Aqua, Calipso, Cloudsat, Parasol, and Aura, so that they can be inter-compared can be daunting to some, and may be repeated by many. Scientists will individually spend much of their time and resources acquiring A-Train datasets of interest residing at various locations, developing algorithms to match up and graph datasets along the A-Train track, and search through large amounts of data for areas and/or phenomena of interest. The aggregate amount of effort that can be expended on repeating pre-science tasks could climb into the tens of millions of dollars. The goal of the A-Train Data Depot (ATDD) is to enable free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) is accomplished by through the ATDDs Giovanni data analysis and visualization tool. Giovanni brings together data from Aqua (MODIS, AIRS, AMSR-E), Cloudsat (cloud profiling radar) and Calipso (CALIOP, IIR), as well as the Aura (OMI, MLS, HIRDLS, TES) to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. This easy to learn and use exploration tool will allow users to create vertical profiles of any desired A-Train dataset, for any given time of choice. This presentation shows the power of Giovanni by describing and illustrating how this tool facilitates and aids A-Train science and research. A web based display system Giovanni provides users with the capability of creating co-located profile images of temperature and humidity data from the MODIS, MLS and AIRS instruments for a user specified time and spatial area. In addition, Cloud and Aerosol profiles may also be displayed for the Cloudsat and Caliop instruments. The ability to modify horizontal and vertical axis range, data range and dynamic color range is also provided. Two dimensional strip plots of MODIS, AIRS, OM1 and POLDER parameters, co-located along the Cloudsat reference track, can also be plotted along with the Cloudsat cloud profiling data. Center swath pixels for the same parameters can also be shown as line plots overlaying the Cloudsat or Calipso profile images. Images and subsetted data produced in each analysis run may be downloaded. Users truly can explore and discover data specific to their needs prior to ever transferring data to their analysis tools.

Kempler, S.↗
NASA NTRS1996

Soot and Radiation Measurements in Microgravity Jet Diffusion Flames

The subject of soot formation and radiation heat transfer in microgravity jet diffusion flames is important not only for the understanding of fundamental transport processes involved but also for providing findings relevant to spacecraft fire safety and soot emissions and radiant heat loads of combustors used in air-breathing propulsion systems. Our objectives are to measure and model soot volume fraction, temperature, and radiative heat fluxes in microgravity jet diffusion flames. For this four-year project, we have successfully completed three tasks, which have resulted in new research methodologies and original results. First is the implementation of a thermophoretic soot sampling technique for measuring particle size and aggregate morphology in drop-tower and other reduced gravity experiments. In those laminar flames studied, we found that microgravity soot aggregates typically consist of more primary particles and primary particles are larger in size than those under normal gravity. Comparisons based on data obtained from limited samples show that the soot aggregate's fractal dimension varies within +/- 20% of its typical value of 1.75, with no clear trends between normal and reduced gravity conditions. Second is the development and implementation of a new imaging absorption technique. By properly expanding and spatially-filtering the laser beam to image the flame absorption on a CCD camera and applying numerical smoothing procedures, this technique is capable of measuring instantaneous full-field soot volume fractions. Results from this technique have shown the significant differences in local soot volume fraction, smoking point, and flame shape between normal and reduced gravity flames. We observed that some laminar flames become open-tipped and smoking under microgravity. The third task we completed is the development of a computer program which integrates and couples flame structure, soot formation, and flame radiation analyses together. We found good agreements between model predictions and experimental data for laminar and turbulent flames under both normal and reduced gravity. We have also tested in the laboratory the techniques of rapid-insertion fine-wire thermocouples and emission pyrometry for temperature measurements. These techniques as well as laser Doppler velocimetry and spectral radiative intensity measurement have been proposed to provide valuable data and improve the modeling analyses.

Ku, Jerry C.↗
DOE OSTI2023

A review of privacy in energy applications

As the distribution system continues to experience an increase in distributed energy resource (DER) and electric vehicle (EV) penetration, so does the need for new solutions that can help grid operators manage and leverage their capabilities. This will undoubtedly lead to new operational schemes and business opportunities that will transform the traditional consumer into a prosumer who will be more actively engaged in grid operations. Although the field is still under active development, many of the potential use cases presented in literature or industry are built upon edge computing, two-way communications, and other innovative computational constructs to attain their goals. However, at their core, many use cases assume a great level of data access to aid with the decision-making process, an assumption that may need to be revised to ensure fair and equitable operational processes are maintained. This may be particularly true as edge resources are predicted to participate in retail-side, many-to-many, or peer-to-peer markets and thus may lead to financial impacts if data access considerations are ignored. The need to revise data access mechanisms can be further justified by the introduction of new participants into the operational process, who do not have the same level of trust, nor the incentives to focus on energy delivery as their primary objective. At the same time, more consumers are becoming aware of their own data, and the potential impacts of its abuse. To help solution developers better understand these risks, this report has been developed to offer an initial introduction to the topic of privacy. This is achieved by 1) Highlighting the need for privacy-aware solutions; 2) Encouraging system designers to be inquisitive about the status quo; 3) Documenting the existing threat space; 4) Presenting and evaluating tools that may be helpful towards enabling better privacy postures; and 5) Making recommendations to encourage the adoption of better practices. From a technical perspective, the report focuses on evaluating two potential techniques by applying them to the Transactive Energy Space. Based on the obtained results, it can be established that differential privacy (DP) methods may have limited applicability when highly correlated, time-series data records need to be protected. However, DP may be a powerful tool when it is used to aggregate and analyze mid-size and large-size data sets in a more traditional statistical environment. The second tool under evaluation is threshold cryptography, which can guarantee complete secrecy (and thus privacy) but requires the establishment of key management procedures and dedicated communication channels for key coordination. Therefore, due to its increased computational overhead, the use of threshold cryptography must be weighted using a cost/benefit analysis on a per-application basis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2005

The Virtual Solar Observatory: Still a Small Box

Two and a half years after a design study began, and a year and a half after development commenced, version 1.0 of the Virtual Solar Observatory (VSO) was released at the 2004 Fall AGU meeting. Although internal elements of the VSO have changed, the basic design has remained the same, reflecting the team's belief in the importance of a simple, robust mechanism for registering data provider holdings, initiating queries at the appropriate provider sites, aggregating the responses, allowing the user to iterate before making a final selection, and enabling the delivery of data directly from the providers. In order to make the VSO transparent, lightweight, and portable, the developers employed XML for the registry, SOAP for communication between a VSO instance and data services, and HTML for the graphic user interface (GUI's). We discuss the internal data model, the API, and user responses to various trial GUI's as typical design issues for any virtual observatory. We also discuss the role of the "small box" of data search, identification, and delivery services provided by the VSO in the larger, Sun-Solar System Connection virtual observatory (VxO) scheme.

Gurman, J. B.↗
DOE OSTI2025

Data for: Miscanthus × giganteus changes soil structure and increases maximum water holding capacity

The data provided include results from a comparative study evaluating the impact of Miscanthus × giganteus (miscanthus) versus maize on soil structural properties and maximum water holding capacity (MWHC) across two Iowa sites. The dataset includes MWHC values determined using the Funnel Filter Paper Drainage (FFPD) method, as well as additional measurements of MWHC following structural disruption of the soil to isolate the effect of aggregation. It also contains three-dimensional micro-computed tomography (microCT) data used to quantify total porosity and pore size distribution (PSD) of soil aggregates at a 5 µm resolution. All data are provided as raw replicate-level measurements, organized by site, crop, and depth, along with processed summary files in table form in CSV (.csv) format to support reproducibility and downstream analysis.

Misanthus x giganteus↗
NASA NTRS1980

AgRISTARS: Foreign commodity production forecasting. Minutes of the annual formal project manager's review, including preliminary technical review reports of FY80 experiments

The U.S./Canada wheat/barley exploratory experiment is discussed with emphasis on labeling, machine processing using P1A, and the crop calendar. Classification and the simulated aggregation test used in the U.S. corn/soybean exploratory experiment are also considered. Topics covered regarding the foreign commodity production forecasting project include: (1) the acquisition, handling, and processing of both U.S. and foreign agricultural data, as well as meteorological data. The accuracy assessment methodology, multicrop sampling and aggregation technology development, frame development, the yield project interface, and classification for area estimation are also examined.

Source record↗
DOE OSTI2024

Responses of Drying-rewetting (Transient Soil Moisture) and Steady State Soil Moisture Incubation on Soil Organic Carbon Dynamics in Three US Soils, 2017

This data set contains measurements of soil characteristics (aggregate size distribution and mean size, total aggregate associated carbon, extractable organic C, and microbial biomass C), microbial respiration, and soil metabolite concentrations from a transient and steady soil moisture incubation experiment using soils of different textures (sandy, loamy, and clayey). The study investigated mechanisms driving the Birch effect (increased carbon mineralization pulses with wetting following a drying period) in differing soil textures. Three different soils of distinctly different textures were collected from 0-15cm depth in Georgia (sandy, 2017-05-01), Missouri (loamy, 2017-06-14), and Texas (clayey, December 2017). Soils were incubated for 140 days with destructive harvests done on days 1, 29, 33, 56, 112, 116, and 140 in transient soil moisture incubation and on days 1, 33, 116, and 140 in steady state soil moisture incubation. This dataset contains six data files in comma separate (.csv) format. Additional metadata are provided: six data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

1-Methyladenosine concentration↗
DOE OSTI2022

A round-robin approach provides a detailed assessment of biomolecular small-angle scattering data reproducibility and yields consensus curves for benchmarking

Through an expansive international effort that involved data collection on 12 small-angle X-ray scattering (SAXS) and four small-angle neutron scattering (SANS) instruments, 171 SAXS and 76 SANS measurements for five proteins (ribonuclease A, lysozyme, xylanase, urate oxidase and xylose isomerase) were acquired. From these data, the solvent-subtracted protein scattering profiles were shown to be reproducible, with the caveat that an additive constant adjustment was required to account for small errors in solvent subtraction. Further, the major features of the obtained consensus SAXS data over the q measurement range 0–1 Å −1 are consistent with theoretical prediction. The inherently lower statistical precision for SANS limited the reliably measured q -range to <0.5 Å −1 , but within the limits of experimental uncertainties the major features of the consensus SANS data were also consistent with prediction for all five proteins measured in H 2 O and in D 2 O. Thus, a foundation set of consensus SAS profiles has been obtained for benchmarking scattering-profile prediction from atomic coordinates. Additionally, two sets of SAXS data measured at different facilities to q > 2.2 Å −1 showed good mutual agreement, affirming that this region has interpretable features for structural modelling. SAS measurements with inline size-exclusion chromatography (SEC) proved to be generally superior for eliminating sample heterogeneity, but with unavoidable sample dilution during column elution, while batch SAS data collected at higher concentrations and for longer times provided superior statistical precision. Careful merging of data measured using inline SEC and batch modes, or low- and high-concentration data from batch measurements, was successful in eliminating small amounts of aggregate or interparticle interference from the scattering while providing improved statistical precision overall for the benchmarking data set.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Distributed Cross-Channel Hierarchical Aggregation for Foundation Models

Vision-based scientific foundation models hold significant promise for advancing scientific discovery and innovation. This potential stems from their ability to aggregate images from diverse sources—such as varying physical groundings or data acquisition systems—and to learn spatio-temporal correlations using transformer architectures. However, tokenizing and aggregating images can be compute-intensive, a challenge not fully addressed by current distributed methods. In this work, we introduce the Distributed Cross-Channel Hierarchical Aggregation (D-CHAG) approach designed for datasets with a large number of channels across image modalities. Our method is compatible with any model-parallel strategy and any type of vision transformer architecture, significantly improving computational efficiency. We evaluated D-CHAG on hyperspectral imaging and weather forecasting tasks. When integrated with tensor parallelism and model sharding, our approach achieved up to a 75% reduction in memory usage and more than doubled sustained throughput on up to 1,024 AMD GPUs on the Frontier Supercomputer.

Tsaris, Aristeidis (aris) [ORNL] (ORCID:0000000277↗
DOE OSTI2020

Automated Integration of Continental-Scale Observations in Near-Real Time for Simulation and Analysis of Biosphere–Atmosphere Interactions

The National Ecological Observatory Network (NEON) is a continental-scale observatory with sites across the US collecting standardized ecological observations that will operate for multiple decades. To maximize the utility of NEON data, we envision edge computing systems that gather, calibrate, aggregate, and ingest measurements in an integrated fashion. Edge systems will employ machine learning methods to cross-calibrate, gap-fill and provision data in near-real time to the NEON Data Portal and to High Performance Computing (HPC) systems, running ensembles of Earth system models (ESMs) that assimilate the data. For the first time gridded EC data products and response functions promise to offset pervasive observational biases through evaluating, benchmarking, optimizing parameters, and training new machine learning parameterizations within ESMs all at the same model-grid scale. Leveraging open-source software for EC data analysis, we are already building software infrastructure for integration of near-real time data streams into the International Land Model Benchmarking (ILAMB) package for use by the wider research community. We will present a perspective on the design and integration of end-to-end infrastructure for data acquisition, edge computing, HPC simulation, analysis, and validation, where Artificial Intelligence (AI) approaches are used throughout the distributed workflow to improve accuracy and computational performance.

Durden, David J.↗
DOE OSTI2022

Skopi: a simulation package for diffractive imaging of noncrystalline biomolecules

X-ray free-electron lasers (XFELs) have the ability to produce ultra-bright femtosecond X-ray pulses for coherent diffraction imaging of biomolecules. While the development of methods and algorithms for macromolecular crystallography is now mature, XFEL experiments involving aerosolized or solvated biomolecular samples offer new challenges in terms of both experimental design and data processing. Skopi is a simulation package that can generate single-hit diffraction images for reconstruction algorithms, multi-hit diffraction images of aggregated particles for training machine learning classifiers using labeled data, diffraction images of randomly distributed particles for fluctuation X-ray scattering algorithms, and diffraction images of reference and target particles for holographic reconstruction algorithms. Skopi is a resource to aid feasibility studies and advance the development of algorithms for noncrystalline experiments at XFEL facilities.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2018

Narrowband Propagation Statistics of Aeronautical Mobile-Ground Links in the L- and C-Bands

To provide for the safe integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS), command and control (C2) links must be highly reliable. Hence, protected aviation spectrum is required to support such links for UAS that are integrated into controlled non-segregated airspace. For air-ground (i.e., non-satellite) links, protected aviation spectrum to support C2 links is available in the 960-1164 MHz (L) and 5030-5091 MHz (C) bands. The performance of any C2 system is critically dependent upon the characteristics of the air-ground (AG) channel. Therefore, as part of its UAS Integration in the NAS (UAS in the NAS) project, the U.S. National Aeronautics and Space Administration (NASA) performed a series of air-ground propagation flight tests to collect AG channel data for model development and analysis of potential C2 communications links capable of providing the required reliability. NASA's Glenn Research Center (GRC) conducted an extensive air-ground channel propagation measurement campaign (at altitude) for frequencies in the 960-977 MHz and 5030-5091 MHz ranges, for seven different terrain environments. The measurements were conducted in 2013, and produced the largest set of AG channel data ever gathered to date. This data was subsequently processed to develop models for the AG channel. The statistics collected enabled the derivation of channel model parameters for both narrowband and wideband channels. In order to make the propagation data widely available, the resulting narrowband statistics were processed and submitted to the International Telecommunications Union - Radiocommunication Sector (ITU-R) Study Group 3 Data Banks. Formats for data tables were developed, and tables of the aggregate narrowband propagation statistics for the seven ground site terrain environments were prepared, submitted to, and approved by, the ITU-R Study Group 3. This paper provides brief background on the measurement campaign, collection and processing of data, and development of the narrowband data tables. It further provides examples of the data and its use.

radiofrequency spectrum↗
NASA NTRS2018

Narrowband Propagation Statistics of Aeronautical Mobile-Ground Links in the L- and C-Bands

To provide for the safe integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS), command and control (C2) links must be highly reliable. Hence, protected aviation spectrum is required to support such links for UAS that are integrated into controlled non-segregated airspace. For air-ground (i.e., non-satellite) links, protected aviation spectrum to support C2 links is available in the 960-1164 MHz (L) and 5030-5091 MHz (C) bands. The performance of any C2 system is critically dependent upon the characteristics of the air-ground (AG) channel. Therefore, as part of its UAS Integration in the NAS (UAS in the NAS) project, the U.S. National Aeronautics and Space Administration (NASA) performed a series of air-ground propagation flight tests to collect AG channel data for model development and analysis of potential C2 communications links capable of providing the required reliability. NASA's Glenn Research Center (GRC) conducted an extensive air-ground channel propagation measurement campaign (at altitude) for frequencies in the 960-977 MHz and 5030-5091 MHz ranges, for seven different terrain environments. The measurements were conducted in 2013, and produced the largest set of AG channel data ever gathered to date. This data was subsequently processed to develop models for the AG channel. The statistics collected enabled the derivation of channel model parameters for both narrowband and wideband channels. In order to make the propagation data widely available, the resulting narrowband statistics were processed and submitted to the International Telecommunications Union Radiocommunication Sector (ITU-R) Study Group 3 Data Banks. Formats for data tables were developed, and tables of the aggregate narrowband propagation statistics for the seven ground site terrain environments were prepared, submitted to, and approved by, the ITU-R Study Group 3. This paper provides brief background on the measurement campaign, collection and processing of data, and development of the narrowband data tables. It further provides examples of the data and its use.

aircraft communications↗
DOE OSTI2022

Prospects of federated machine learning in fluid dynamics

Physics-based models have been mainstream in fluid dynamics for developing predictive models. In recent years, machine learning has offered a renaissance to the fluid community due to the rapid developments in data science, processing units, neural network based technologies, and sensor adaptations. So far in many applications in fluid dynamics, machine learning approaches have been mostly focused on a standard process that requires centralizing the training data on a designated machine or in a data center. In this article, we present a federated machine learning approach that enables localized clients to collaboratively learn an aggregated and shared predictive model while keeping all the training data on each edge device. We demonstrate the feasibility and prospects of such a decentralized learning approach with an effort to forge a deep learning surrogate model for reconstructing spatiotemporal fields. Our results indicate that federated machine learning might be a viable tool for designing highly accurate predictive decentralized digital twins relevant to fluid dynamics.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Measured and Modeled Vineyard Canopy Development and Water Use

Two publicly available applications relevant to vineyard irrigation management are described. OpenET is a satellite-based system that applies an ensemble of remote sensing methods to enable wide-area monitoring of evapotranspiration (ET) and related measures such as vegetation canopy development (via the NDVI spectral index). Data are freely available at one-quarter acre spatial resolution, and may be automatically aggregated to the individual block level. The satellite-based daily ET data were compared with in-situ eddy covariance measurements collected by micro-meteorological instrumentation in a Central Coast vineyard over a three-year period (2020-2022). Estimation uncertainties were reasonably consistent with prior reports for GRAPEX sites in the Central Valley and North Coast. The CropManage (CM) web application is a free software tool developed and operated U.C. Cooperative Extension for ET-based irrigation scheduling of major specialty crops. CM provides specific guidance for irrigation events in terms of irrigation system runtime. Applied water recommendations are based largely on estimated ET, derived from assumed canopy cover and associated crop coefficients, since the last irrigation or rainfall event. The application was recently adapted to vineyards by accounting for presence of winter/spring cover crop, and vine water stress imposed by regulated deficit irrigation. A 2022 field campaign involved 12 Central Coast and San Joaquin Valley commercial vineyards, and OpenET data were used to help evaluate CM output. Maximum percent vine cover was compared to estimates derived from average July satellite NDVI. The difference for 10 sites lacking midseason groundcover ranged from 0-7% between datasets with average agreement near 4%. Cumulative ET estimates agreed with OpenET to within 12% at the majority of sites, while larger discrepancies at the remaining sites may require additional data collection and analysis during the 2023 season. Satellite based systems such as OpenET have the potential to help parameterize CropManage and similar agricultural decision-support systems.

Measured↗
NASA NTRSDate not supplied

Hydrological Data at the NASA GES DISC: Current Capabilities and New Opportunities

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of twelve NASA Earth science data centers that document, process, archive and distribute data from Earth observation missions and projects. GES DISC maintains an archive of several hydrology datasets, including the Land Data Assimilation Systems (LDAS) and the Gravity Recovery and Climate Experiment (GRACE) Data Assimilation for Drought Monitoring (GRACE-DA-DM) data products. These datasets include model output of heat fluxes, rain, snow, soil temperature, soil moisture, and runoff; and observational forcing data, including surface pressure, temperature, precipitation, downward shortwave and longwave radiation, humidity, and wind. The temporal resolution of the hydrology data at GES DISC ranges from hourly to monthly, and spatial resolutions range from 0.1° to 1.0°. The GES DISC provides services which enable users to aggregate, temporally and spatially subset, regrid, and visualize archived data including the GES DISC Subsetter, Hydrology Data Rods, and the Geospatial Interactive Online Visualization and Analysis Infrastructure (GIOVANNI). The Hydrology Data Rods service optimally reorganizes large hydrological data sets as extended time series, providing more efficient access for the hydrological community. The time series data (aka “data rods”) were integrated into hydrology community tools, such as the Data Rods Explorer on HydroShare. Furthermore, the GES DISC is in the process of migrating its data and services to the cloud. Hydrological data available at the GES DISC are now available in the Amazon Web Services (AWS) cloud (us-west-2 region) providing users Direct S3 data access and the capability for cloud computing operations. In this presentation, the hydrology data products and services currently available at the GES DISC will be summarized. Also discussed are the migration to the cloud, user support through this transition, and the status of migrating the data rods service to the cloud.

Ashley Heath↗
DOE OSTI2025

Pricing Strategy of Electric Vehicle Aggregators Based on Locational Marginal Price to Minimize Photovoltaic (PV) Curtailment

The global climate crisis demands urgent action to mitigate global warming. Using renewable energy sources, such as solar and wind power, for electricity generation is crucial. This shift from centralized to distributed power systems, however, brings challenges, including voltage fluctuations and renewable energy curtailment. The rapid growth of the electric vehicle (EV) industry adds complexity, increasing overall electricity demand and straining the power supply during peak charging times. This paper proposes a scheduling strategy for EV aggregators to reduce renewable energy curtailment and stabilize grid operation by strategically scheduling EV charging. Using Multi -Agent Transport Simulation (MATSim), a traffic simulation tool, EV driving data in Denver, Colorado, USA, were modeled. The EV aggregator adjusts charging fees based on locational marginal prices, encouraging EVs to charge at different stations according to pricing. Simulations on an IEEE 33-bus system with distributed energy resources and EV charging stations validate the proposed algorithm, demonstrating its effectiveness in reducing curtailment by 12.55% and stabilizing grid operation.

33 ADVANCED PROPULSION SYSTEMS↗