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210 results for “energy modelling”
Dataset: Harmonized and Open Energy Dataset for Modeling a Highly Renewable Brazilian Power System
<p>The dataset provided here is intended for publication - Harmonized and Open Energy Dataset for Modeling a Highly Renewable Brazilian Power System.</p> <p>Direct use of our provided datasets is available from Zenodo, and the source code to generate the datasets is published in <a href="https://gitlab.com/dlr-ve/esy/open-brazilian-energy-data">Gitlab</a>. We describe the data collection process in detail and open source the code for data processing and analysis in our publication.</p> <p><br> The assembled dataset includes the following subcategories, as detailed in the methods section of our publication: i) geospatial data for Brazil, ii) aggregated grid network topology, iii) vRES potentials --- profile and installable generation capacity, iv) geographically installable capacity of biomass thermal plants, v) hydropower plants inflow, vi) existing and planned power generators with their capacity, vii) electricity load profile, viii) scenarios of sectoral energy demand and ix) cross-border electricity exchanges. This dataset is resolved geographically by Brazilian federal states, and time series data are resolved by hours, spanning 2012-2020.</p> <p>The dataset can be used as input to popular open energy system models such as PyPSA and any other modelling framework.</p> <p>We encourage you to contribute to improving the datasets.</p>
The Long-term energy planning with highly detailed demand modelling for Egypt: an IOA-MAED-OSeMOSYS soft-linking approach
<p>These files contain an updated model built for Egypt's power system as of 2023, with detailed demand simulation in 3 different scenarios; business as usual, high economic growth and industrial energy efficiency.</p> <p>Also, a multi region model built for Egypt, Sudan and Ethiopia power sector technologies for future cooperation scenarios.</p>
Integration of Renewable Energy Sources into the Water-Energy-Food (WEF) Nexus – Modelling a Demand Side Management Approach and Application to a Microgrid Farm in Morocco Dataset
<p>Here you can find the official data used for the publication "Integration of Renewable Energy Sources into the Water-Energy-Food (WEF) Nexus – Modelling a Demand Side Management Approach and Application to a Microgrid Farm in Morocco"</p> <p>If you want to run the model, please update line 11 in the run.jl file, to select the dataset from the scenario you want to look at. It is also recommended to change the result path, to a directory that corresponts to the current model run in order to find the results files quicker.</p> <p> </p> <p>To create a new plot a file called newPlot.jl can be found, that already take care of most data handling, only lines 136 and 141 need to be changed, in order to read in the result files of the results you want to investigate.</p>
Extended ensemble molecular dynamics study of ammonia–cellulose I complex crystal models: free-energy landscape and atomistic pictures of ammonia diffusion in the crystalline phase.
<p>The data deposited here accompany the manuscript "Extended ensemble molecular dynamics study of ammonia–cellulose I complex crystal models: free-energy landscape and atomistic pictures of ammonia diffusion in the crystalline phase" and include the molecular dynamics trajectories and the AMBER topology (parm) files. Detailed file contents are summarized in the README file.</p>
Data for: Coupling dynamic energy budget and population dynamic models to inform stock enhancement in fisheries management
<p><span>Extensive applications of fishery stock enhancement worldwide bring up broad concerns about its negative effects, creating a pivotal need for science-based assessment and planning of enhancement strategies. However, the lack of mechanistic understanding of enhanced population dynamics, particularly the density-dependent processes, leads to compromise in model development and limits the capacity in predicting enhancement effects. Here, we developed an individual-based model based on dynamic energy budget theory and full life history processes, to understand the mechanism of density dependence in population dynamics that emerge from individual-level processes. We demonstrated the utility of the model framework by applying it </span><span>to an extensively enhanced species, Chinese prawn (<em>Fenneropenaeus chinensis</em></span><span>, Penaeidae</span><span>). The model could yield projections reflecting the observed trajectory of population biomass and yields. The model also delineated the key effects of density dependence on the vital rates of growth, fecundity, and starvation mortality. Regarding the manifold effects of stock enhancement, we demonstrated a dampened shape in population biomass and yields with increasing magnitude of enhancement, and trade-offs between the ecological and economic objectives, i.e., pursuing high benefit might compromise the wild population without proper management. Furthermore, we illustrated the possibility of combining stock enhancement and harvest regulation in promoting population recovery while maintaining fisheries yields. We highlight the potential of the proposed model for understanding density dependence in enhancement program, and for designing integrated management strategies. The approach developed herein may serve as a general approach to assess the population dynamics in stock enhancement and inform enhancement management.</span><span> </span></p>
Figures: Vortex model of the aerodynamic wake of airborne wind energy systems
<p>Figures in .pdf, .png and .fig format.</p><p>Figures in .fig format can be opened with MATLAB or other open source programming languages (e.g., Python thought the command scipy.io.loadmat or Octave)</p><p>Figures were updated after: Trevisi, F., Croce, A., and Riboldi, C. E. D.: Corrigendum to "Vortex model of the aerodynamic wake of airborne wind energy systems", published in Wind Energ. Sci., 8, 999–1016, 2023, https://doi.org/10.5194/wes-8-999-2023-corrigendum"</p>
Remote versus local impacts of energy backscatter on the North Atlantic SST biases in a global ocean model
<p>The data and scripts used to generate the figures in the manuscript "Remote versus local impacts of energy backscatter on the North Atlantic SST biases in a global ocean model".</p>
Composite activity type and stride-specific energy expenditure estimation model for thigh-worn accelerometry
<p>This repository contains code and data for the research project 'Estimation of activity induced energy expenditure using thigh-worn accelerometry and machine learning approaches'.</p> <ul> <li>The <strong>code </strong>subfolder contains Jupyter Notebooks and a Python file with helper functions. Further, the models subfolder contains the trained models.</li> <li>The <strong>data </strong>subfolder contains the raw accelerometer files (AX) as well as the raw data from the indirect calorimetry (CPET). Further, different processing files can be found here. The file log_master.csv contains the sociodemographic and timestamp data.</li> <li>The <strong>figures</strong> subfolder contains all relevant figures, which are created as part of running the Jupyter Notebooks. These figures are also part of the research publication.</li> </ul>
Data for: Coupling dynamic energy budget and population dynamic models to inform stock enhancement in fisheries management
Open the record for dataset details and reuse information.
The impact of metabolic plasticity on winter energy use models
Open the record for dataset details and reuse information.
Community Land Model version 4.5 (CLM4.5) simulations of water, energy, and carbon fluxes for Saddle vegetation communities, 2008 - 2013
Single point simulations of CLM4.5 that include (1) forcing data that were input to the model and subsequent (2) model output for simulations that approximate conditions in fellfield, dry meadow, moist meadow, wet meadow, and snowbed vegetation communities. Forcing data were generated with observed atmospheric conditions from Tvan, Saddle precipitation, and incoming shortwave radiation measured from the AmeriFlux tower site (US-NR1) from 2008-2013. Wintertime precipitation inputs were modified to approximate average snow depth for each vegetation community observed across the Saddle grid. Land models, like CLM, provide a cohesive framework to investigate biogeophysical and biogeochemical effects of environmental change on ecosystem processes. We used CLM4.5 to investigate if a global-scale model can represent local-scale patterns of water, energy, and carbon fluxes in a heterogeneous mountain environment. Specifically, we were interested in generating testable projections of potential ecosystem responses to climate change. Model output includes half-hourly data on fluxes of energy, water, and carbon, as well as vegetation carbon stocks and edaphic conditions. We also conducted sensitivity analyses to look at ecosystem responses to modifications intended to extend growing season length by decreasing snow albedo and warming air temperatures (black sand and M-A warm, respectively). Information on the variables, units, and data are included as attributed in the network Common Data Form (NetCDF) files for this dataset. For users unfamiliar with using NetCDF files, we have included R scripts that write (forcing data) and read (model output) .nc files include in this data archive. More information about NetCDF files is available at http://www.unidata.ucar.edu/software/netcdf/docs/index.html.
Data supplement for Wind Energy Science Paper 'Implementation of the blade element momentum model on a polar grid and its aeroelastic load impact'
<p>Contains the data for most figures in the article, as well as a plotting file written in python that generates the figures.</p>
Data for the publication "Reconciling compensating errors between precipitation constraints and the energy budget in a climate model"
<p>These data are a set of 6yr simulations using the MIROC6-SPRINTARS global aerosol-climate model with different treatments (diagnostic and prognostic) of precipitation under the present-day (PD, aerosol emission at the year 2000) and preindustrial (PI, aerosol emission at the year 1850) conditions.<br> The data are used in the manuscript entitled "Reconciling compensating errors between<br> precipitation constraints and the energy budget in a climate model".</p>
Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model - Simuation results and observed data
<p>This data set contains the simulation results and observed data at NDBC buoy locations.</p> <ul> <li>wave_data.pickle <ul> <li>File containing python data objects which store: station ID data, observed data, model data, and model output dates. Requires python 3.8.</li> </ul> </li> <li>data_access.py <ul> <li>Example python script which reads in a prints the data from wave_data.pickle. It also demonstrates how to access data from the objects stored in the pickle file.</li> </ul> </li> </ul>
Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model - 2 degree WaveWatchIII configuration files
<p>This dataset contains the mesh and model configuration information for a WaveWatchIII run using a 2 degree structured grid.</p> <ul> <li>glo_2d.bot <ul> <li>Bottom depth file for 2 degree structured grid</li> </ul> </li> <li>glo_2d.mask <ul> <li>Mask file for 2 degree structured grid</li> </ul> </li> <li>obstructions_local.glo_2d.in <ul> <li>local obstructions file for use with UOST source term switch</li> </ul> </li> <li>obstructions_shadow.glo_2d.in <ul> <li>shadow obstructions file for use with UOST source term switch</li> </ul> </li> <li>ww3_grid.inp <ul> <li>Input file for the ww3_grid pre-processing program. This file specifies many of the model configuration settings.</li> </ul> </li> <li>ww3_shel.inp <ul> <li>Input file for the ww3_shel program.</li> </ul> </li> </ul>
Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model - unstructured (2 degree to 1/2 degree) WaveWatchIII configuration files
<p>This dataset contains the mesh and model configuration information for a WaveWatchIII run using a global ustructured grid.</p> <ul> <li>mesh.msh <ul> <li>Unstructured mesh file in gmsh format. The unstructured mesh has 2 degree resolution globally with 1/2 degree resolution around the U.S. coastlines. The transition in resolution occurs at 4000m depth with a 10% resolution grading.</li> </ul> </li> <li>obstructions_local.glo_unst.in <ul> <li>local obstructions file for use with UOST source term switch</li> </ul> </li> <li>obstructions_shadow.glo_unst.in <ul> <li>shadow obstructions file for use with UOST source term switch</li> </ul> </li> <li>ww3_grid.inp <ul> <li>Input file for the ww3_grid pre-processing program. This file specifies many of the model configuration settings.</li> </ul> </li> <li>ww3_shel.inp <ul> <li>Input file for the ww3_shel program.</li> </ul> </li> </ul>
Conjunto de dados Modelo de Regressão Aplicado à Previsão de Preços SPOT de Energia Elétrica (Dataset Regression Model Applied to Electric Energy SPOT Price Forecasting)
<p>Esse conjunto de dados utilizou DataSets de duas fontes distintas: CCEE e ONS. Como são órgãos públicos os dados são acurados, transparentes, confiáveis e de boa qualidade. Os dados de entrada possuem as variáveis que são utilizadas no modelo atual do PLD, já citado. São elas: as datas, o armazenamento de água, a ENA, a expectativa de ENA para a próxima semana e a carga.</p> <p>As datas são dados diários entre janeiro de 2013 e janeiro de 2017. O armazenamento de água é dado por submercado e apresentado em porcentagem da capacidade máxima. A ENA e a expectativa dela para a semana seguinte são apresentadas em porcentagem a partir das chuvas realizadas convertidas em MWmédio pelas previsões feitas utilizando dados históricos (1932-2007). A carga está em MWmédio. E o PLD em R$/MWh.</p> <p>Os soma dos dados dos quatro submercados (SE/CO, SU, NE, NO) de cada dado nos fornece a informação do Sistema Nacional Interligado (SIN).</p> <p>As variáveis de carga, armazenamento e ENA foram retiradas do histórico de operações do site da ONS, disponibilizados para download em ‘csv’. E o PLD do site da CCEE, disponibilizados em ‘xls’.</p> <p>Foram mesclados a partir das datas formando o arquivo de entrada para o modelo utilizado nos experimento</p> <p> </p> <p>Metadados / Metadata</p> <p>Storage of water: percentage of storage of water by submarket.<br> ENA and expectative of ENA: presented by percentage of previsions of rains that happen converted on MWmedium by previsions did with a historic (1932-2007). Data are by submarket.<br> Charge: charge by submarket give on MWmedium.<br> PLD: give on R$/MWh<br> The sum of each variable is the data of the total system.</p> <p> </p> <p> </p>
Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. Part I: Adaptive local approximate models
<p>The global search stage of Crystal Structure Prediction (CSP) methods requires a fine balance between accuracy and computational cost, particularly for the study of large flexible molecules. A major improvement in the accuracy and cost of the intramolecular energy function used in the CrystalPredictor II (Habgood, M., Sugden, I. J., Kazantsev, A. V., Adjiman, C. S. & Pantelides, C. C. (2015).<em> J Chem Theory Comput</em> <strong>11</strong>, 1957-1969) program is presented, where the most efficient use of computational effort is ensured via the use of adaptive Local Approximate Model (LAM) placement. The entire search space of relevant molecule’s conformations is initially evaluated using a coarse, low accuracy grid. Additional LAM points are then placed at appropriate points determined via an automated process, aiming to minimise the computational effort expended in high energy regions whilst maximising the accuracy in low energy regions. As the size, complexity, and flexibility of molecules increase, the reduction in computational cost becomes marked. This improvement is illustrated with energy calculations for benzoic acid and the ROY molecule, and a CSP study of molecule XXVI from the sixth blind test (Reilly <em>et al.</em>, (2016).<em> Acta Cryst. B, accepted</em>.), which is challenging due its size and flexibility. Its known experimental form is successfully predicted as the global minimum. The computational cost of the study is tractable without the need to make unphysical simplifying assumptions. </p>
Aerodynamics code used in Wind Energy Science paper "Comparison of a coupled near- and far-wake model with a free-wake vortex code"
<p>This research code has been developed from the start of my PhD as a first step before the HAWC2 implementation of the near wake model.</p> <p>It can be used to make aerodynamic computations of a stiff wind turbine rotor, and it includes</p> <ul> <li>A BEM and far wake model implementation based on the one in HAWC2</li> <li>An attached flow unsteady airfoil aerodynamics model including the modifications described in the WES article</li> <li>Most importantly a near wake model implementation including all major modifications except the recent stand still extension presented at TORQUE 2016</li> </ul> <p>All the data files need to be in a subfolder 'NREL_5MW' located in the same folder as the compiled source code.</p> <p>With the present (hardcoded) settings, the program will simulate the NREL 5 MW reference turbine for 650 seconds, with blade vibrations according to different prescribed mode shapes after steady state is reached. The aerodynamics model is a coupled near and far wake model. The integrated aerodynamic work during 1 period of the different prescribed vibrations will be output in the file 'aerowork.out' .</p> <p>The NREL 5 MW turbine is described in:</p> <p>Jonkman, J., Butterfield, S., Musial,W., and Scott, G.: Definition of a 5-MW Reference Wind Turbine for Offshore System Development, National Renewable Energy Laboratory, 2009.</p>
Data accompanying the paper "Regime-dependent turbulence length scale formulation for NWP models based on turbulence kinetic energy, shear and stratification", submitted to Monthly Weather Review
<p>This repository contains the outputs of MicroHH LES (van Heerwaarden et al., 2017) and ALADIN-CZ single-column model simulations of four idealized cases:</p> <p>1) The continental cumulus case utilizing measurements from the Atmospheric Radiation Measurement (ARM) program, and Cloud and Radiation Testbed (CART) site in Oklahoma (Brown et al. 2002; Lenderink et al. 2004)</p> <p>2) The trade wind cumulus case from the Barbados Oceanographic and Meteorological Experiment (BOMEX; Siebesma et al. 2003)</p> <p>3) A drizzling stratocumulus case based on the first research flight data of the second period of the Dynamics and Chemistry of Marine Stratocumulus (DYCOMS-II) campaign (Stevens et al., 2005)</p> <p>4) A stable planetary boundary layer case based on the Global Energy and Water Cycle Experiment (GEWEX) Atmospheric Boundary Layer Study (GABLS1) data (Beare et al. 2006; Cuxart et al. 2006; Holtslag 2006)</p> <p>The MicroHH LES outputs are taken from Reilley et al. (2022) study and can be also found at https://doi.org/10.5281/zenodo.6372434. Additionally, we provide case study outputs from the ALADIN-CZ 3D NWP model, wherein the fields roughly match those verified/shown in Fig. 9.</p> <p> </p> <p>The files are organized in the following way:</p> <p>1) MicroHH LES model configuration files (.ini) and output files (NetCDF format) are stored in the file "LES.zip" within "conf" and "data" folders, respectivelly. Additionally, a sample script to plot LES-derived Turbulence Length Scales (TLS) and those based on NWP formulations (using LES data as input) is provided (plot.py).</p> <p>2) The vertical profiles of (i) conserved variables and (ii) turbulent fluxes from the ALADIN-CZ single-column model for four idealized cases are provided in the file "single-column_simulations.zip", consisted of individual ASCII files (per case and TLS formulation). A detailed description of its content can be found in the associated README file.</p> <p>3) Chosen surface and upper-air fields for (i) 23 November 2019 inversion and (ii) 24 June 2022 mesoscale convection system cases are provided in the file "case_studies.zip" and consisted of individual GRIB files per field and prognostic hour. A detailed description of its content can be found in the associated README file.</p> <p> </p> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.