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37 results for “heat pump”
Data archive for paper "Energy and environmental impacts of air-to-air heat pumps in a mid-latitude city"
<p><strong>Overview</strong></p> <p>This is the data archive for paper "<a href="https://www.nature.com/articles/s41467-024-49836-3" target="_blank" rel="noopener">Energy and environmental impacts of air-to-air heat pumps in a mid-latitude city</a>". It contains the paper's data archive with model outputs (see <code>notebooks</code> folder) and the Singularity image for (optionally) re-running experiments.</p> <p>For the standalone models to model air conditioners and heat pumps please refer to <a href="https://github.com/dmey/minimal-dx">MinimalDX</a>.</p> <p><strong>Prerequisites</strong></p> <ul> <li>Linux with Bash shell.</li> <li><a>Git</a> version >= 2.</li> <li><a href="https://sylabs.io/">Singularity</a> version >= 3.</li> <li><a href="https://en.wikipedia.org/wiki/Portable_Batch_System">Portable Batch System</a>*.</li> <li><a href="https://en.wikipedia.org/wiki/Intel_Fortran_Compiler">Intel Fortran Compiler</a> [<em>Required for MesoNH simulations</em>].</li> <li>A compatible version of the MPI library implementation version 3 [<em>Required for MesoNH simulations</em>].</li> </ul> <p>Please note that most steps require <a href="https://sylabs.io/">Singularity</a>. If you are looking for information on how to install or use Singularity, please refer to the <a href="https://sylabs.io/docs">Singularity documentation</a>. Please note that depending on your specific system settings and resource availability, you may need to modify PBS parameters at the top of submit scripts stored in the hpc directory.</p> <p><strong>Simulations</strong></p> <p><em><strong>Offline</strong></em></p> <ol> <li>Build Surfex with <code>qsub hpc/surfex_build.pbs</code>.</li> <li>Run scenarios with the following commands: <pre><code> qsub -v case_name=fincap hpc/surfex_run.pbs qsub -v case_name=fincap_extended_autosize hpc/surfex_run.pbs qsub -v case_name=minidx_cop=2.5 hpc/surfex_run.pbs qsub -v case_name=minidx_cop=3.0 hpc/surfex_run.pbs qsub -v case_name=minidx_cop=3.5 hpc/surfex_run.pbs qsub -v case_name=minidx_cop=4.0 hpc/surfex_run.pbs<br> qsub -v case_name=minidx_cop=4.5 hpc/surfex_run.pbs </code></pre> </li> </ol> <p><em><strong>Online</strong></em></p> <p>To run MesoNH simulations, follow the three steps outlined below in the same order. Note: Depending on your system and configuration, submit scripts may require change.</p> <ol> <li>Build MesoNH with <code>qsub hpc/build_mnh_intel.pbs</code>.</li> <li>Run the preprocessing step with <code>qsub hpc/submit_mnh_prep.pbs</code>.</li> <li>Finally run MesoNH cases with the following commands for <code>fincap</code> and <code>minidx</code> simulations respectively: <pre><code> hpc/submit_mnh.sh fincap 20050120 12 1 toulouse hpc/submit_mnh.sh minidx 20050120 12 1 toulouse </code></pre> </li> <li>Post-process the results with <code>qsub hpc/submit_mnh_post.pbs</code></li> </ol> <p><strong>Analyses</strong></p> <pre><code>qsub hpc/postprocess_results.pbs # Plots in notebooks/ </code></pre>
Performance Indicators of Photovoltaic Heat Pumps
<p>Qualitative and quantitaive results included in the review 'Performance Indicators of Photovoltaic Heat Pumps' (DOI:10.1016/j.heliyon.2019.e02691) are given, together with the original data and the corresponding calculations. The files with the simulation info for the SISIFO simulation tool are also available. </p>
Performance simulation of short term alternative refrigerants for plug and play small size reversible heat pump
<p>This dataset is generated by CNR-ITC in order to simulate and compare the thermodynamic performance of short-term alternative refrigerants in HP cycles at various operating conditions. The purpose of this dataset within the project is to select the most promising fluid to be used in the plug and play small size reversible HP prototype developed by HIREF.<br> The generated data are thermodynamic properties and performance (COP, VRE) values from simulation of thermodynamic HP cycles with homemade software developed in Matlab environment.</p>
Recordings of an Air-to-Water Heat Pump
<p>This technical report contains detailed information about anechoic recordings from an air-to-water heat pump system in different operating states. Based on these recordings, a total of 28 stimuli were selected and processed from three different operating states: high-power heating, maximum capacity, and defrost. Additionally, the measurement of the horizontal directivity of the heat pump using 12 microphones is documented in this report. The described data is available under a CC BY 4.0 license and is primarily intended for further scientific use, e.g., in perceptual assessments of heat pumps.</p>
Dataset supporting publication: 'GEOFIT: Ground source heat pump systems for energy efficient building retrofitting'
<p>Dataset supporting publication: Presentation of GEOFIT at the <a href="https://www.hp-summit.de/en">European Heat Pump Summit</a> (2019) </p> <p>Available for download: <a href="https://zenodo.org/record/3901527">GEOFIT Zenodo</a></p> <p>The integration of geothermal systems for heating / cooling solutions in conjunction with heat pump technology is a major challenge, particularly in the case of renovation. In order to find the best solution for the increased flow temperatures compared to a new building for the renovation, various heat pump configurations are evaluated according to energy and economic criteria. A refrigerant with low greenhouse gas potential (GWP) is used as the working medium, e.g. R1234ze (E)) less than 10 used. A favorable refrigeration circuit configuration for high flow temperatures is a twin-circuit system, which essentially consists of two heat pumps with different condensing temperatures and the same evaporation temperatures. An alternative to this is a single-stage configuration with a significantly larger condenser for improved supercooling. Both systems should enable efficient operation when renovating buildings.</p>
Data for Process Design and Energy Assessment of an Onboard Carbon Capture System with Boilers or Heat Pumps for Additional Steam Generation
<p>1. Supporting file includes main stream information used in Aspen HYSYS model, process simulations of boiler and heat pump for model construction.<br> 2. Supporting file also includes main information used in ProMAX model, process simulations of carbon capture process for model construction.</p>
Artifact for the paper "Towards Model-Driven Heat Pump Control in a Multi-Story Building"
<p>This is a reproducibility package for the paper "Towards Model-Driven Heat Pump Control in a Multi-Story Building".</p> <p>Domestic heating systems can provide significant energy flexibility when integrated with heat pumps and hot water buffer tanks, especially with fluctuating day-ahead energy prices. However, optimizing these systems in large buildings with shared resources poses crucial challenges. While most existing studies target single-room or single-family house systems, this study explores the complexities within a three-story building housing six apartments. The building’s heating system consists of a hot water buffer tank, mixing loop, radiant floor heating system, and a Ground Source Heat Pump (GSHP) controlled by a weather-compensated control strategy (WCS). Our approach aims to tackle challenges like integrating real sensor data, scalability, varying weather effects, and diverse resident heat use preferences. We employ the CTSMR software to identify thermal behaviour and use reinforcement learning to design an intelligent/model-driven UPPAAL STRATEGO<br>controller. Our results reveal a 43% reduction in energy costs while maintaining comfort levels compared to a WCS. The temporal validity of the estimated thermal models is also analyzed.</p>
Dataset and code related to the publication "Aligning heat pump operation with market signals: A win-win scenario for the electricity market and its actors?"
<h3>General remarks</h3> <p>This dataset and code was developed and used for the publication</p> <blockquote> <p><em>E. Sperber, C. Schimeczek, U. Frey, K. K. Cao, V. Bertsch: Aligning heat pump operation with market signals: A win-win scenario for the electricity market and its actors? In: Energy Reports, Volume 13, June 2025, pp. 491-513, https://doi.org/10.1016/j.egyr.2024.12.028<br></em></p> </blockquote> <h3>Data description</h3> <p>The dataset "<em>heat_pump_results.zip</em>" includes all relevant results underlying the above publication. </p> <p>The data is organized according to the scenarios considered in the analysis. Therefore, each folder is labelled according to the scenario structure, starting with the building efficiency scenario ("BAU" / "EFF"), followed by the PV scenario ("no-PV" / "with-PV"), the HP operation scenario ("ModFlex_V", "ModFlex_F", "HighFlex_V"), the simulation year (2030 / 2040) and the weather year (2017 / 2019 / 2023).</p> <p>Within each result directory per scenario, the data is further structured according to the results at the market level ("AMIRIS") and at the user level ("GAMS" and "INFLEX"). The "INFLEX" directory contains results for the inflexible reference operation, while the "GAMS" directory contains results for the cost-minimized heat pump operation at the level of building types. The data at the user level is further structured by location. Data is given in hourly resolution.</p> <p>The scenario evaluation indicators presented in the publication, as well as other indicators, are summarized in the "MPI" directory.</p> <p>Abbreviations used:</p> <ul> <li>HP: heat pump</li> <li>SH: space heating</li> <li>DHW: domestic hot water</li> <li>AW: air/water</li> <li>BW: brine/water</li> <li>PV: photovoltaic</li> <li>Ti: indoor air temperature</li> <li>Ttes: temperature of domestic hot water storage tank</li> </ul> <h3>Code description</h3> <p>The code to generate the results is given in "<em>heat_pump_workflow.zip</em>". Please follow the instructions in the README.md that you can find in this archive.</p> <h3>Conctact</h3> <p>Please contact Evelyn Sperber at evelyn.sperber@dlr.de if you have any questions.</p>
2020 Utility Provider Incentive Data for Heat Pump Water Heaters
<p>This data set captures energy efficiency program incentives for heat pump water heaters in the U.S. for the year 2020. The data fields include utility provider, state(s) covered, maximum incentive amount, number of residential customers, incentive type, sector type, requirements, and website link. This is valuable information for understanding which states and regions are promoting heat pump water heater market adoption with incentives.</p>
Assessing inequities in electrification via heat pumps across the U.S.
<p>This repository contains code and publicly available data to reproduce the results of <em>Assessing inequities in electrification via heat pumps across the U.S.</em> published in Joule.</p>
Electrochemically Driven Phase Transformation for High Efficiency Heat Pumping
<p>All datasets reported in the paper and all original code are deposited in this repository.</p>
Performance simulation of short term alternative refrigerants for innovative hybrid high temperature heat pump
<p>This dataset is generated by CNR-ITC in order to simulate and compare the thermodynamic performance of short-term alternative refrigerants in HP cycles at various operating conditions. The purpose of this dataset within the project is to select the most promising fluid in an innovative hybrid high temperature HP developed by HIREF. The generated data are thermodynamic properties and performance (COP, VRE) values from simulation of thermodynamic HP cycles with home made software developed in Matlab environment.</p>
500 Hourly Synthetic Single-Family Household Heat Pump Load Profiles for Karlsruhe, Germany (2021)
<p>We created a synthetic dataset of 500 hourly single-family household water-to-water heat pump load profiles based on the weather profile of Karlsruhe, Germany in 2021. We have applied the open-source methodology published in [1], which applies a k-means clustering process to match daily weather profiles with randomly drawn empirical observations from the high-quality heat pump load profile dataset published in [2]. We have selected a number of 5 clusters, for a good balance between variance of profiles and accuracy, as discussed in [1]. The dataset can be used for modeling large numbers of heat pumps in grid sections or energy communities. </p> <p>The unit of the measurement is Wh. Through the "SFH" identifier, the underlying, randomly drawn households from [2] can be identified. </p> <p>[1] Semmelmann, L., Jaquart, P., & Weinhardt, C. (2023). Generating synthetic load profiles of residential heat pumps: a k-means clustering approach. <em>Energy Informatics</em>, <em>6</em>(Suppl 1), 37.</p> <p>[2] Schlemminger, M., Ohrdes, T., Schneider, E., & Knoop, M. (2022). Dataset on electrical single-family house and heat pump load profiles in Germany. <em>Scientific data</em>, <em>9</em>(1), 56.</p>
The potential of decentral heat pumps as flexibility option for decarbonised energy systems: Balmorel input data
<p><strong>Description</strong></p> <p>This dataset holds all Balmorel model input data as well as the Balmorel code used for the scenarios of the paper 'The potential of decentral heat pumps as a flexibility option for Austria's electricity system in 2030' submitted to 'Applied Energy'.</p> <p>The original Balmorel source code is available under https://github.com/balmorelcommunity/Balmorel under the ISC license. It was adapted in the course of this paper.</p> <p><strong>Data format</strong></p> <p>We provide the data in form of the data folders holding the .inc files for all scenarios.</p>
Source Data Systematic Literature Review Heat Pump Adoption and Use
Open the record for dataset details and reuse information.
A generic methodology for mapping the performances of heat pumps considering part-load behaviour - Supplementary material
<h2>Description</h2> <p>This is the supplementary material provided with the journal article "A generic methodology for mapping the performances of heat pumps considering part-load behaviour" published in Energy and Buildings on 2024, September 01. (<a href="https://doi.org/10.1016/j.enbuild.2024.114490">https://doi.org/10.1016/j.enbuild.2024.114490</a>).</p> <h2>Content</h2> <ul> <li>Datasets are provided as NetCDF files for European maps</li> <li>SCOP/SEER estimations at TMY locations are provided as CSV files</li> <li>COP/EER cruves at TMY locations are provided as CSV files</li> <li>NUTS aggregates of SCOP and Peak COP are provided as CSV files</li> <li>European maps are provided as PDF files.</li> </ul> <h2>Code availability</h2> <p>The code used to generate these datasets is openly available on GitLab (<a href="https://gitlab.com/antoine.rogeau/generic-heatpump-model.git">https://gitlab.com/antoine.rogeau/generic-heatpump-model.git</a>) or on Zenodo (<a title="https://doi.org/10.5281/zenodo.10594143" href="https://doi.org/10.5281/zenodo.10594143">https://doi.org/</a><a title="https://doi.org/10.5281/zenodo.10594143" href="https://doi.org/10.5281/zenodo.10594143">10.5281/zenodo.10594143</a>)</p> <div> <div> <div> </div> <div> <div> <div> </div> <div> <p> </p> <p> </p> </div> </div> </div> </div> </div>
domOS Sion Living Lab: Household and Heat Pump Electricity Consumption Data
<p>This dataset has been collected in context of the domOS H2020 project (<a href="https://www.domos-project.eu/">https://www.domos-project.eu/</a>). The dataset includes data about the electricity consumption of 15 single-family residential households all located around Sion (Switzerland), in the OIKEN service area (<a href="https://oiken.ch">https://oiken.ch</a>). All the households are equipped with an individual heat pump providing energy for both space heating and domestic hot water.</p> <p>The ongoing data collection began in January 2021 and includes the households’ total electricity consumption provided by the Smart Meter. It also includes the specific consumption of the heat pump and the production of the solar panels (where applicable) provided by dedicated sub-meters.</p>
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