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64 results for “energy optimization”
Norway energy policy optimization results
<p>These files contain the raw results from master thesis on Norwegian energy policy directions. The each folder has a html file (with basic plots), a netcdf file and a series of csv files. The four scenarios uploaded are the unconstrained (model is free to install capacity as it wants) and base case (current norwegian policy direction), for both a beyond 2030 and beyond 2050 timeline. These results are part of a Master thesis work. Additional results related to transmission and onshore wind policy available upon request to h.guddingsmo@outlook.com.</p>
Energy and time optimal trajectories in exploratory jumps of the spider Phidippus regius
<p>Supplementary files S1 from the paper Energy and time optimal trajectories in exploratory jumps of the spider <em>Phidippus regius</em>. CT Scan files - A repository with files from CT scanning, composed of: 1. The volume from the CT scan in VGI/VOL format. 2. A VAXML model of the spider (stl meshes tied together with an XML file). 3. A Drishti Prayog model of the volume</p>
Engineering the Compositional Architecture of Core-Shell Upconverting Lanthanide-Doped Nanoparticles for Optimal Luminescent Donor in Resonance Energy Transfer: The Effects of Energy Migration and Storage
<p>Förster Resonance Energy Transfer (FRET) between single molecule donor (D) and acceptor (A) is well understood from fundamental perspective and is widely applied in biology, biotechnology, medical diagnostics and bio-imaging. However, the reliability of molecular FRET measurements can be affected by numerous artefacts which eventually hamper quantitative and reliable analysis, mostly due to issues with the donor and acceptor molecules. Lanthanide doped upconverting nanoparticles (UCNPs) have demonstrated their suitability as alternative donor species. Nevertheless, while they solved most disadvantageous features of organic donor molecules, such as photo-bleaching, spectral cross-excitation and emission bleed-through, the fundamental understanding and practical realizations of bio-assays with UCNP donors remain challenging. Among others, the actual donor ions in individual donor UCNPs are the numerous activator ions randomly distributed in the nanoparticle at various distances to acceptors anchored on the nanoparticle surface. Further, the power dependent, complex energy transfer upconversion and energy migration between sensitizing and activating lanthanide ions within UCNPs complicate the decay based analysis of <strong><em>D</em></strong>-<strong><em>A</em></strong> interaction. In this work, the assessment of designed virtual core-shell nanoparticle (VNP) models led us to the new designs of UCNPs, such as …@Er, Yb@Er, Yb@YbEr, which were experimentally evaluated as donor nanoparticles and compared to the simulations. Moreover, the specific properties of lanthanide-based upconversion motivated us to analyze not only steady-state luminescence and luminescence decay responses of both the UNCP donor and the sensitized acceptor, but also the effects of their luminescence rise kinetics upon RET was discussed in newly proposed disparity measurements. The presented studies help to understand the role of energy-transfer and energy migration between lanthanide ion dopants (due to their concentration and spatial distribution) and how the architecture of core-shell UCNPs affects their performance as FRET donors to organic acceptor dyes.</p>
Spine model and datasets for "Home Energy Optimization using Vehicle-to-Home"
<p>The Spine models are simulated for the publication of "Home Energy Optimization using Vehicle-to-Home" in the journal of Open Reserach Europe.</p> <p>The file lists are explained as follows:</p> <p>"Non-commuter_spine.zip" is the zipped folder of Spine model for non-commuting household.</p> <p>"Spine_commuter.zip" is the zipped folder of Spine model for commuting household.</p> <p>"Recorded Results and Paramater Variation Graphs - ORE.xlsx" describes the figures and outputs applied for the paper.</p> <p>"PV, elec, thermal_non_commuting.zip" denotes the non-commuting model input.</p> <p>"Model_input_commuter (1).zip" denotes the commuting model input.</p> <p>"Model output_commuter (2).xlsx" denotes the commuting model output.</p> <p> </p>
SESMG model scenarios of the study "Indicators for the optimization of sustainable urban energy systems based on energy system modeling"
<p>This folder contains the model scenarios belonging to the publication "<strong>Indicators for the optimization of sustainable urban energy systems based on energy system modeling</strong>" (<a href="https://doi.org/10.1186/s13705-021-00323-3">https://doi.org/10.1186/s13705-021-00323-3</a>).</p> <p>The individual scenarios can be executed and evaluated with the <strong>Spreadsheet Energy System Model Generator (<a href="https://github.com/chrklemm/SESMG">SESMG</a>)</strong> <a href="https://doi.org/10.5281/zenodo.5412027">v0.0.4</a>, respectively <a href="https://doi.org/10.5281/zenodo.5520513">v0.2.0</a>.</p> <p>The file names are to be understood as follows:</p> <p><em>"scenario name"_"(dispatch) optimization criterion"_"scenario concretization"_"further scenario concretization"_"associated program version"</em>.xlsx.</p> <p>For example, the title name "<em>Scenario3_C_4MW_Biogas_SESMGv0.0.4.xlsx</em>" contains the following information:<br> - This file belongs to scenario 3 (see main publication for details).<br> - Dispatch optimized according to energy costs C (see main publication for details).<br> - The scenario contains 4 MW biogas CHP capacity (see main publication for details)<br> - The scenario is to be executed with SESMG version v0.0.4.</p> <p>Another example. The title name "<em>optimization_C_80PercentDemand_70PercentEmissions_SESMGv0.1.1.xlsx</em>" contains the following information:<br> - This file belongs to the optimization scenario (see main publication for details).<br> - The primary optimization criterion is energy costs C (see main publication for details).<br> - Energy demand was capped at 80 percent and emissions at 70 percent of baseline (see main publication for details)<br> - The scenario is to be executed with SESMG version v0.1.1.<br> </p> <p><strong>Acknowledgements:</strong></p> <p>The authors would like to thank Prof. Dr. Peter Vennemann (Münster University of Applied Sciences) for the constructive discussion regarding this article. This research has been conducted within the R2Q project, funded by the German Federal Ministry of Education and Research (BMBF) - grant number 033W102A and the junior research group energy sufficiency funded by the German Federal Ministry of Education and Research (BMBF) as part of its Social-Ecological Research funding priority, funding number 01UU2004A. </p>
Optimal Control of Renewable Energy Communities with Controllable Assets: consumption and production profiles
<p>consumption and production profiles for cases I and II used for computing simulations in Optimal Control of Renewable Energy Communities with Controllable Assets</p>
Greening the financial regulation by optimizing credit limits for renewable energy
<p>Numerical Data used in the empirical part of the paper</p>
Supporting Information - Optimizing hydrogen microgrids to facilitate diesel exit and meet the energy needs of remote and northern communities
<p>This file accompanies "Optimizing hydrogen microgrids to facilitate diesel exit and meet the energy needs of remote and northern communities" by Ian Maynard and Ahmed Abdulla.</p> <p>This supporting information contains:</p> <ul> <li>Nomenclature</li> <li>Data inputs</li> <li>Cost ratios used in cost calculations</li> <li>References</li> <li>Optimization results of 40 communities discussed in the paper above</li> </ul>
Simulation Results of the Distributed Schedule Optimization with Energy Storages using EO-COHDA
<p>This dataset contains the result of the evaluation of an approach to integrate energy storages in distributed flexibility negotiations. The data was created using the implemented approach on https://gitlab.com/digitalized-energy-systems/models/eo-cohda. To work with this results we highly recommend to use eo-cohda as well, because it provides a lot convenient utility functions for this.</p> <p>The dataset has been divided in two parts:</p> <ol> <li>the result of the negotiation, <ul> <li>format: hdf, readable using hdf-viewers/python</li> </ul> </li> <li>the generated schedules of the energy storages used for the negotiation. <ul> <li>format: binary, pickled real power schedules, readable using eo-cohda's utility methods.</li> </ul> </li> </ol> <p> </p>
Modeling and simulation of a new Urban Lightweight Electric Vehicle concept based on the optimized use of renewable energies and the reduction of CO2 emissions
<p>This work has produced a series of scientifc contributions. This library develops different mathematical expressions and assumptions for the dynamic modelling of an smart-grid located within a solar-powered ULEV are derived. The code was developed using Dymola</p>
Data for Paper: A rigorous optimization method for long-term multi-stage investment planning: Integration of hydrogen into a decentralized multi-energy system
<p>Data containing the results and figures presented in the paper "A rigorous optimization method for long-term multi-stage investment planning: Integration of hydrogen into a decentralized multi-energy system" by Luka Bornemann and Jelto Lange and Martin Kaltschmitt, submitted to the Journal Energy Reports.</p>
Dataset for "Convex modeling of pumps in order to optimize their energy use" article
<p>This is the data set about pump optimization used in the submitted article "Convex modeling of pumps in order to optimize their energy use" . The proposed optimization method is shown, and also the two methods to which it is compared to.</p> <p> </p>
Large-area periodically-poled lithium niobate wafer stacks optimized for high-energy narrowband terahertz generation - Dataset
<p>Dataset for the publication "Large-area periodically-poled lithium niobate wafer stacks optimized for high-energy narrowband terahertz generation".</p>
Data for LEELO-LA (Long-term Energy Expansion Linear Optimization - Latin America)
<p>This repository contains the data for LEELO-LA (Long-term Energy Expansion Linear Optimization - Latin America)</p>
Data used for modeling in Energy-water-land-CCUS nexus model: carbon dioxide opportunities based on optimized regional development
<p>In this dataset, the data used for modeling technologies in an energy-water-land-CCUS nexus model in Khark Island in Iran, and the main sources for gathering them are presented.</p>
A real-world energy management data set from a smart company building for optimization and machine learning
Open the record for dataset details and reuse information.
Time-Plan Optimization with Genetic Algorithm for Regain of Energy from Train Tracks
<p>Dataset using for Time-Plan Optimization with Genetic Algorithm for Regain of Energy from Train Tracks</p>
Distributed Multi-objective Optimization in Cyber-Physical Energy Systems
<p>The data includes results for a distributed multi-objective optimization in Cyber-Physical Energy Systems. The respective implementation for the scenarios can be found here: https://github.com/Digitalized-Energy-Systems/MOO-CPES/releases/tag/Distributed_Multi-objective_Optimization_in_Cyber-Physical_Energy_Systems<br>In this case, a multi-agent system exists for the optimization in which agents represent chp units or wind plants. For the optimization using the agents, the agents have to fulfill a target schedule, with contains of the sum of all unit schedules. Regarding the target schedule, three objectives are considered: minimizing the difference between the<br>produced power in sum and the given target schedule, minimizing the emissions and minimizing the uncertainties.</p>
Influence of Nuclear Investment Costs and Baseload Demand on the Optimal Energy Mix
<p>Results from the study on "Influence of Nuclear Investment Costs and Baseload Demand on the Optimal Energy Mix".</p>
Data for the publication "Wind farm layout optimization with alignment constraints", submitted to Wind Energy Science, 2024
<p>The data in pickle format contains the optimal layouts corresponding to the numerical applications of the paper "Wind farm layout optimization with alignment constraints" submitted in Wind Energy Science, 2024.</p>
ScienceDex guides
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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)
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.