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15 results for “power system model”
Model Inputs and Results - The role of coal plant retrofitting strategies in decarbonizing India's power system
<p>These files are the model inputs and results for the submission based on GenX version v0.3.6 - The role of coal plant retrofitting strategies in decarbonizing India’s power system</p>
Dataset for the power system modelling of the West African Power Pool (WAPP)
<p>Input datasets and simulation results for the West African Power Pool (WAPP) simulation with <a href="http://dispaset.eu/">Dispa-SET</a> described in <a href="https://ec.europa.eu/jrc/en/publication/analysis-water-power-nexus-west-african-power-pool">this technical report</a>. All the assumptions and the model are described in the report, the four files contain the input datasets for the "current" and "future" scenario and the simulation results.</p> <p>Full citation to the technical report:</p> <p>DE FELICE, M., GONZÁLEZ APARICIO, I., HULD, T., BUSCH, S., HIDALGO GONZÁLEZ, I.,<em> Analysis of the water-power nexus in the West African Power Pool - Water-Energy-Food-Ecosystems project</em>, EUR 29617 EN, Publications Office of the European Union, Luxembourg, 2019, ISBN 978-92-79-98138-8, doi:10.2760/362802, JRC115157</p>
Data input for the RegMex model experiment on the power system and flexible sector coupling
<p>This file provides the input data used in the power system flexibility model experiment performed within the RegMex project. Comprehensive information about the project can be found in the project report [Lechtenböhmer2018] (in German, see link in the file). In the experiment performed with the data documented here, three scenarios were considered, labelled "Import", "Decentralized" and "Offshore". This file contains the input for all scenarios. All further information on the model and scenario configuration is available from the project report. Many technology parameter have been derived as own assumptions within previous projects, relying on different sources. Details can be found in the cited PhD and masters theses. In the experiment, Germany was modelled with 18 regions reflecting the transmission grid operator zones (see map in the file).</p>
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>
Supplementary Material to 'Exploring the power of data-driven models for groundwater system conceptualization: A case study of the Grazer Feld Aquifer, Austria'
<p>This folder contains the supplementary materials to reproduce the results, tables, and figures from the following publication submitted to the Hydrogeology Journal: </p> <p>Kokimova A., Collenteur, R.A. & Birk, S. Exploring the power of data-driven models for groundwater system conceptualization: A case study of the Grazer Feld Aquifer, Austria.</p>
eELib: Open-Source Model Library for Prosumer Power Systems and Energy Management Strategies (data)
<p>Dataset and results used for the simulations in following publication:</p> <p>Carsten Wegkamp, Henrik Wagner, Eike Niehs, Julien Essers, Marcel Lüdecke, Mattias Hadlak, Bernd Engel:<br>"<strong>eELib: Open-Source Model Library for Prosumer Power Systems and Energy Management Strategies</strong>",<br>Open Source Modelling and Simulation of Energy Systems (OSMSES) 2024, Vienna, Austria, 2024</p> <p> </p> <p>This contains the input (scenario) files for the building & grid scenario and the results of the two simulations.<br>It uses the elenia Energy Library (eELib) with release version 1.0.0: https://gitlab.com/elenia1/elenia-energy-library</p>
Viet Nam Technology Catalogue - Technology data input for power system modelling in Viet Nam
<p>Today, innovations and technology improvements within renewable energy are taking place at a very rapid pace. Long-term energy planning is very dependent on cost and performance of future energy producing technologies.<br> This technology catalogue provides estimates of costs and performance for a wide range of power producing technologies, thereby building one of the key inputs to good energy planning in Vietnam.<br> Due to the multi-stakeholder involvement in the data collection process, the technology catalogue contains data that have been scrutinised and discussed by a broad range of relevant stakeholders including the Ministry of Industry and Trade – MOIT, Vietnam Electricity – EVN, independent power producers, local and international consultants, organizations, associations and universities. This is essential because a main objective is to produce a technology catalogue which is well anchored amongst all stakeholders.<br> The technology catalogue will assist the long-term energy modelling in Vietnam and support government institutions, private energy companies, think tanks and others with a common and broadly recognized set of data for electricity producing technologies in Vietnam in the future.</p>
Data for the Eastern African power pool's energy systems model, developed in OSeMOSYS
<p>This repository consists of the following datasets</p> <p>1. EAPP_reference scenario_datafile.DD- This dataset is a model file that needs to be used with the code available in this <a href="https://github.com/KTH-dESA/OSeMOSYS/blob/master/OSeMOSYS_GNU_MathProg/osemosys_short.txt">GitHub</a> link. This data file (in concurrence with the OSeMOSYS code) can be used to create a linear programming file (LP file) to be solved using any mathematical optimisation solver like GLPSOL/C-PLEX/GUROBI/CBC.</p> <p>2. Main article_EAPP_data for figures.xlsx- This excel file contains the base data used to illustrate the figures in the main article.</p> <p>3. Supplementary article_EAPP_data for figures.xlsx- This excel file contains the base data used to illustrate the figures in the supplementary article.</p>
Comparing power-system- and user-oriented battery electric vehicle charging representation and its implications on energy system modeling
<p>This supplementary material includes data and code for the research described in the paper "Comparing power-system- and user-oriented battery electric vehicle charging representation and its implications on energy system modeling". The code containts an interface between the output files of the agent-based simulation model CURRENT and the energy system optimization model REMix as well as some scripts for analyzing REMix results. The data folder contains input data for REMix, the complete list of all model runs analyzed in the paper in the GAMS format .gdx as well as Excel files containing annual results of the sensitivity runs and respective pivot tables and figures for respective analysis.</p>
European power system infrastructure in the open energy system model PyPSA-Eur
<p>The image is created using the data and scripts in the European open energy system model <a href="https://github.com/PyPSA/pypsa-eur">PyPSA-Eur.</a></p>
OpenFoam model output for "A Fuel Cell Power Supply System Equipped with Artificial Gill Membranes for Underwater Applications"
<p>Dataset of numerical experiments carried out with OpenFOAM v 10 as used in the manuscript "A Fuel Cell Power Supply System Equipped with Artificial Gill Membranes for Underwater Applications" by Lucas Merckelbach and Prokopios Georgopanos.</p> <p> </p>
SimBench - Electrical Power System Benchmark Models
<p>SimBench (<a href="https://www.simbench.net">www.simbench.net</a>) is a research project to create a "simulation database for uniform comparison of innovative solutions in the field of network analysis, network planning and operation", which was conducted for three and a half years from 1.11.2015 to 30.04.2019. It was part of the German Federal Government's 6th Energy Research Program "Research for an Environmentally Friendly, Reliable and Affordable Energy Supply". The project was carried out by the University of Kassel, the Fraunhofer IEE, the RWTH Aachen University and the Technical University of Dortmund in accordance with the authors mentioned above. The project, coordinated by the University of Kassel, was supported by the professional advisory from six German distribution network operators: DREWAG NETZ GmbH, Energie Netz Mitte GmbH, ENSO NETZ GmbH, Netze BW GmbH, Syna GmbH and Westnetz GmbH.</p> <p>The objective of the research project SimBench is the development of a benchmark data set to support research in grid planning and operation. SimBench Grid differs from other benchmark grids under the following key points:</p> <ul> <li>Consideration of a wide range of use cases during the development of data sets</li> <li>Provision of grid data for low voltage (LV), medium voltage (MV), high voltage (HV), extra high voltage (EHV) as well as design of data sets for a suitable interconnection of a grid among different voltage levels for cross-level simulations</li> <li>Ensuring highreproducibility and comparability by providing clearly assigned load and generation time series</li> <li>Validation of the suitability of the data sets with simulation, deliberately determined grid states including suitable dimensioning of grid assets</li> </ul> <p>In total SimBench provides 13 unique electrical power system grids (EHV: 1, HV: 2, MV: 4, LV: 6). Since SimBench is enables multi-voltage simulations, this dataset includes not only 13 folder but many more. Each excerpt of the complete dataset, composed to a folder, is distinctively named by the SimBench code.</p> <p>For further information, please visit <a href="https://www.simbench.net">www.simbench.net</a> and the documentation published there.</p>
Viet Nam Technology catalogue for power generation and storage. Input for power system modelling
<p>The first Viet Nam Technology Catalogue was published in 2019. This new version includes all the technologies from the 2019 version that have been reviewed and updated where necessary. A main focus of the update has been to add new subcategories of technologies (roof-top solar PV, floating offshore wind, low wind speed turbines, improved flexibility of coal fired plants and pollution prevention technologies for coal power) as well as completely new technology descriptions and data sheets (tidal power, wave power, carbon capture and storage, coal CFB boilers and industrial cogeneration).</p> <p>This publication is developed under the Danish-Vietnamese Energy Partnership.</p> <p>The technologies described in this catalogue cover both very mature technologies and emerging technologies, which<br> are expected to improve significantly over the coming decades, both with respect to performance and cost. This<br> implies that the cost and performance of some technologies may be estimated with a rather high level of certainty<br> whereas, in the case of other technologies, both cost and performance today and in the future is associated with a<br> high level of uncertainty. All technologies have been grouped within one of four categories of technological<br> development described in the section on research and development indicating their technological progress, their<br> future development perspectives and the uncertainty related to the projection of cost and performance data.</p> <p>The technologies in the catalogue include the power production unit and the connection to the grid. This means<br> that the boundary for both cost and performance data are the generation assets plus the infrastructure required to<br> deliver the energy to the main grid. For electricity, this is the nearest substation of the transmission grid. This<br> implies that a MW of electricity represents the net electricity delivered, i.e. the gross generation minus the auxiliary<br> electricity consumed at the plant. Hence, efficiencies are also net efficiencies.</p> <p>The text and data have been edited based on Vietnamese cases to represent local conditions. For the mid- and long-<br> term future (2030 and 2050) international references have been relied upon for most technologies since Vietnamese<br> data is expected to converge to these international values. In the short run differences may exist, especially for the<br> emerging technologies. Differences in the short run can be caused by e.g. current rules and regulations and level of<br> market maturity of the technology. Differences in both the short and long run can be caused by local physical<br> conditions, e.g. seabed material and offshore conditions can affect costs of offshore wind farms and wind speed can<br> affect the dimensioning of rotor vs. generator which can influence the cost, or domestic coal quality can affect<br> efficiency and variable cost of coal-fired plants as well.</p> <p>Land use is assessed but the cost of land is not included in the total cost assessment since this depends on local<br> conditions.</p>
Dataset from Denmark for Modeling a Highly Renewable Power System
<p>This is a completed database of Danish electrical transmission system for modeling an electrical system with high penetration of renewable energy.</p>
Probabilistic Model-Based Diagnosis for Electrical Power Systems
We present in this article a case study of the probabilistic approach to model-based diagnosis. Here, the diagnosed system is a real-world electrical power system, namely the Advanced Diagnostic and Prognostic Testbed (ADAPT) located at the NASA Ames Research Center. Our probabilistic approach is formally well-founded, and based on Bayesian networks and arithmetic circuits. We pay special attention to meeting two of the main challenges model development and real-time reasoning often associated with real-world application of model-based diagnosis technologies. To address the challenge of model development, we develop a systematic approach to representing electrical power systems as Bayesian networks, supported by an easy-touse specication language. To address the real-time reasoning challenge, we compile Bayesian networks into arithmetic circuits. Arithmetic circuit evaluation supports real-time diagnosis by being predictable and fast. In experiments with the ADAPT Bayesian network, which contains 503 discrete nodes and 579 edges and produces accurate results, the time taken to compute the most probable explanation using arithmetic circuits has a mean of 0.2625 milliseconds and a standard deviation of 0.2028 milliseconds. In comparative experiments, we found that while the variable elimination and join tree propagation algorithms also perform very well in the ADAPT setting, arithmetic circuit evaluation was an order of magnitude or more faster. **Reference:** O. J. Mengshoel, M. Chavira, K. Cascio, S. Poll, A. Darwiche, and S. Uckun. "Probabilistic Model-Based Diagnosis: An Electrical Power System Case Study”. Accepted to IEEE Transactions on Systems, Man, and Cybernetics, Part A, 2009.
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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)
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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.