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37 results for “Heat pumps”
Technical potential of ground-source heat pumps for Western Switzerland
<p>This dataset contains an estimation of the technical potential of shallow ground-source heat pumps (GSHPs) for Western Switzerland, at a spatial resolution of 200 x 200 m<sup>2</sup>. The technical potential is hereby defined as the maximum energy that could be extracted from GSHP systems in case of their dense deployment, such as to <strong>avoid the over-exploitation</strong> of the heat capacity of the ground. We consider GSHPs with <strong>vertical closed-loop borehole heat exchangers</strong> (BHE) installed at depths of 50 - 200 m. The dataset covers around 80,000 property units (parcels) in the Swiss Cantons of Vaud and Geneva, excluding only the areas of the Alps and the Jura mountains.</p> <p>The estimated potential accounts for:</p> <ul> <li>Norms for geothermal installations set by the Swiss Society of Engineers and Architects (SIA 384/6)</li> <li>Thermal interferences between neighbouring boreholes and their impact on the temperature change in the ground</li> <li>Topographic Landscape data to assess the available area for BHE installation</li> </ul> <p>The methodology used to generate the data is described in:</p> <p>Walch, Alina, Nahid Mohajeri, Agust Gudmundsson, and Jean-Louis Scartezzini. ‘Quantifying the Technical Geothermal Potential from Shallow Borehole Heat Exchangers at Regional Scale’. <em>Renewable Energy</em> 165 (2021): 369–80. <a href="https://doi.org/10.1016/j.renene.2020.11.019">https://doi.org/10.1016/j.renene.2020.11.019</a>.</p> <p><strong>Dataset description</strong></p> <p>As the data is targeted to large-scale applications and potential studies, it is shared in the format of <strong>pixels of 200 x 200 m<sup>2</sup></strong>. Upon request it can be provided at different aggregation levels, as it is generated at the resolution of individual building units (parcels). The potential is provided as <strong>annual</strong> <strong>values</strong>, and it can be converted to monthly values using the provided heating degree weights. For each pixel of 200 x 200 m<sup>2</sup>, we provide the following variables:</p> <ul> <li>Annual total technical heat extraction potential (in MWh)</li> <li>Potential heat delivered <em>to buildings </em>(heat pump output), assuming a heat pump performance (COP) of 4.5 (in MWh)</li> <li>Available area for GSHP installation (in m<sup>2</sup>)</li> <li>Number of installed boreholes </li> <li>Average heat extraction rate (in W/m)</li> <li>Average borehole depth (in m)</li> <li>Average borehole spacing within the parcels located in the pixel (in m)</li> <li>Heating degree weights (i.e. heat demand variation) for each month</li> </ul> <p>A description of the metadata is provided in the document <em>gshp_VD_GE_metadata_V1.pdf.</em></p> <p>This work is part of the PhD Thesis of Alina Walch. </p>
Scenarios of technical and useful ground-source heat pump potential for building heating and cooling in Western Switzerland
<p>This dataset contains an estimation of the useful and technical potential of shallow ground-source heat pumps (GSHPs) for Western Switzerland, at a spatial resolution of 400 x 400 m<sup>2</sup>. The <strong>technical potential</strong> is hereby defined as the maximum energy that could be extracted from GSHP systems in case of their dense deployment, such as to <em>avoid the over-exploitation</em> of the heat capacity of the ground. We consider GSHPs with <em>vertical closed-loop borehole heat exchangers</em> (BHE) installed at depths of 50 - 200 m. The <strong>useful potential</strong> is defined as the potential that could be delivered to building heating and cooling systems via a water-to-water heat pump.</p> <p>The datasets contains future scenarios of heating and cooling demand, space cooling equipment deployment (service sector only) and climate change models and considers the potential use of DHC. The dataset covers around 80,000 property units (parcels) in the Swiss Cantons of Vaud and Geneva, excluding only the areas of the Alps and the Jura mountains.</p> <p>The data package contains information on the available area for GSHP systems, the heating and cooling demand as well as the resulting technical and useful potentials for all simulated scenarios of future cooling demand (200 Monte Carlo runs), for the case of <strong>direct heat supply</strong> (per pixel of 400 x 400 m<sup>2</sup>) as well as for <strong>district heating and cooling</strong> (DHC). In scenarios without DHC (direct heat supply), the results are summarized by pixel of 400 x 400 m<sup>2</sup>. In scenarios with DHC, the results of potentials <em>within</em> DHCs are summarized by DHC (see <em>*_in_dhc.csv</em>) while potentials <em>outside</em> of DHCs are summarized by pixel (see <em>*_outside_dhc.csv</em>).</p> <p>For details on the methodology applied to obtain the results provided in the data package, please refer to the above-mentioned research articles. A description of all files is provided in<em> Dataset documentation.pdf</em> and metadata is provided in <em>Datapackage.json.</em></p>
Experimental HIL datasets of a heat pump controlled by MPC or rule-based controllers for energy flexibility
<p>Hardware-in-the-loop experiment performed in the SEILAB laboratory of IREC<br> Air-to-water heat pump including a DHW tank for production of SH and DHW, which external unit is placed in a climate chamber that reproduces the desired weather conditions dynamically<br> Control is MPC or rule-based, both triggered either by a signal of price or CO2 intensity from the grid (4 series of experiments)<br> Connected to virtual residential building (flat) in Spanish Mediterranean climate<br> More information:<br> https://doi.org/10.1109/ACCESS.2019.2903084</p>
Probabilistic projections of granular energy technology diffusion at subnational level - solar photovoltaics, heat pumps, and battery electric vehicles in Switzerland
<p>The probabilistic projections are part of the work: <br><em>Nik Zielonka, Xin Wen, Evelina Trutnevyte, Probabilistic projections of granular energy technology diffusion at subnational level, PNAS Nexus, Volume 2, Issue 10, October 2023, pgad321, </em><a href="https://doi.org/10.1093/pnasnexus/pgad321"><em>https://doi.org/10.1093/pnasnexus/pgad321</em></a></p> <p>Please cite the article together with the Zenodo link when you use the data.</p> <p>The provided data files contain the estimated probabilistic projections for all Swiss municipalities on the actual diffusion of solar photovoltaics (PV), heat pumps, and battery electric vehicles (BEVs) in Switzerland for the indicated years:</p> <p>Version 2022-2050: Projections for the years 2022-2050 as presented by Zielonka et. al (2023), PNAS Nexus.<br>Version 2023-2050: Projections for the years 2023-2050, using the latest data of 2022.<br>Version 2024-2050: Projections for the years 2024-2050, using the latest data of 2023.</p> <p>The computations were performed at University of Geneva using Baobab HPC service.</p> <p>This research was carried out with the support of the Swiss Federal Office of Energy SFOE as part of the SWEET project SURE (N.Z., E.T.) and the Swiss National Science Foundation Eccellenza Grant as part of the project "Accuracy of long-range national energy projections" (Grant no. 186834, X.W., E.T.). The authors bear sole responsibility for the conclusions and the results.</p>
Test and numerical data of a vapour-injection scroll compressor in a heat pump with R1234ze(E)
<p>The dataset contains the experimental results of a water-to-water heat pump tested at the lab for different water temperatures. The refrigerant used is the HFO R1234ze(E). The scroll compressor is equipped with an eco port. The numerical results of a validated semi-empirical model are also included for a standard suction pressure drop model and an improved one.</p>
Resarch data for common faults tested on a variable-speed propane-charged heat pump on heating mode
<p>Experimental data of common faults emulated on a 10 kW water-to-water variable-speed heat pump charged with propane. The faults emulated are evaporator fouling, compressor valve leakage, liquid line restriction and refrigerant overcharge. The faults are tested with 10 kW and 12 kW load demand.</p> <p>This data can be used to develop fault detection and diagnosis systems.</p>
Research data for Refined heat pump design and results of final testing
<p>In this dataset, the data of the second experimental test campaign of the CO2-ice heat pump is shared. The report, which analyzes the data and makes the necessary explanations, has already been shared as a "Refined heat pump design and results of final testing (Deliverable: D5.6)". The report has already been published on ZENODO.</p>
Research data for Critical review of heat pump prototype operation and required modications
<p>In this dataset, the data of the first experimental test campaign of the CO2-ice heat pump is shared. The report, which analyzes the data and makes the necessary explanations, has already been shared as a "Critical review of heat pump prototype operation and required modifications (Deliverable: D5.5)".</p>
Photovoltaic heat pump experiemental data
<p>A prototype of a photovoltaic heat pump (PV-HP) system has been implemented and characterized for cooling generation. The raw data obtained for two different control algorithms are presented here. </p>
Heat pump connected to floor heating
<p>Heat pump connected to floor heating.</p>
Datasets used for "Heat Pump - Heating Electrification and Climate Change - Grid Impact Studies"
<h2> Summary</h2> <p> </p> <p>In this work, we explore long term patterns in electricity demand driven by the dual effects of space heating electrification and climate change. We use an open source nodal power system model of the Electric Reliability Council of Texas (ERCOT) system to investigate a wide range of future climate and technology scenarios that evolve over time, and report results in terms of market prices, reliability and corresponding relative capacity requirements </p> <h2> About </h2> <p>The technical analysis aimed to:</p> <h3>1) Understand the Long-Term Patterns:</h3> <p>We aim to analyze patterns in peak load, total load, loss of load, and the seasonality of these phenomena, driven by widespread heat pump adoption alongside climate change.</p> <h3>2) Use Extensive Scenario Analysis:</h3> <p>Explore a wide range of future scenarios, including variations in climate pathways, to capture the uncertainty associated with these long-term changes. In total, 1280 simulation years.</p> <h3>3) Use a validated open source DC OPF model(reproducibility)</h3> <p>Use an open-source nodal power system model of the ERCOT system to simulate and understand the potential impacts on market prices, reliability, and relative capacity requirements. Similar models are available for all interconnections of the conterminous US.</p> <h3>4) Assess Grid Vulnerability:</h3> <p>Assess the vulnerability of the grid to these simultaneous changes, identify potential vulnerability.</p> <h3>5) Provide Insights for System Planners:</h3> <p>Offer results that can assist long-term system planners in anticipating and preparing for potential shifts in grid reliability.</p>
Dataset and analysis file for 3-factor solution for heat pump perception study using Q-methodology in Groningen, the Netherlands
<p>Dataset and analysis using KEN-Q method for a 3-factor solution for heat pump perception study using Q-methodology in Groningen, the Netherlands</p>
Heat pumps for all? Distributions of the costs and benefits of residential air-source heat pumps in the United States
<p>Dataset for the "<span>Heat pumps for all? Distributions of the costs and benefits of residential air-source </span><span>heat pumps in the United States" paper</span></p>
Replication data for: Operating Strategies of an Industrial R717 Heat Pump Recovering Waste Heat of a Chiller
<p>This dataset contains the data of the publication:<br> Verdnik, M., Wagner, P., Rieberer, R., 2022. Operating Strategies of an Industrial R717 Heat Pump Recovering Waste Heat of a Chiller. Proc. International Congress of Refrigeration 2023, Paris, France</p>
Performance investigation of an ejector-assisted transcritical CO2 heat pump with brazed plate tri-partite gas cooler for space heating and hot water production
<p>The carbon dioxide (CO<sub>2</sub>) heat pump water heater is recognized as a potential technology for the production of domestic hot water (DHW) and space heating (SH). In this paper, the performance of a transcritical CO<sub>2</sub> heat pump water heater with a tri-partite gas cooler is discussed using a numerical model. The heat pump operates in three modes: (1) DHW mode, (2) SH mode, and (3) DHW+SH mode, which provides space heating at 35 °C and hot water up to 70 °C. The simulation model is validated with the experimental data. The effects of different parameters on system performance are investigated, and the coefficient of performance (COP) of the system under different operating conditions is evaluated. The results show that higher heat sink outlet temperatures lower the COP and increase SH/DHW-Ratio for the investigated cases. The maximum COP is investigated for various heat loads by continuous high-pressure (HP) modulation, reaching highest values at 50 % to 60 % of maximum heat load. The SH/DHW-Ratio is investigated for the presented simulation cases in DHW+SH mode, reaching 0.68 to 1.06 for different heat loads.</p>
Results from the FLEX Model for the paper "Impact of variable electricity price on heat pump operated buildings"
<p>The sqlite database contains the results of the Flex model for the Austrian single family house building stock ( insert GITHUB LINK). The building stock is represented by 36 different representative building archetypes (“OperationScenario_Component_Building”). Each building is simulated in twice. In the "reference" mode the energy demand is simply met and indoor comfort is kept constant. In the "optimization" mode the indoor temperature can be varied and thermal storages are charged and discharged minimizing the households energy cost based on a variable electricity price. The sqlite database “Variable_Price_Paper” contains the results for the building stock without any storage implemented. In “Variable_Price_Paper_TS” all buildings have a 750l hot water buffer storage and a 400l DHW storage implemented. The sqlite files SFH_23/25/27 contain the results for a single building where the maximum inside room temperature was changed to 23, 25 and 27 °C respectively.</p> <p>Following columns were used for generating the results for the Paper:</p> <p>In the hourly results relevant parameters used in the publication were:</p> <ul> <li>ID_Scenario: each building simulated under a different electricity price has a unique scenario number. “OperationScenario” gives an overview of the scenarios.</li> <li>Grid: describes the electricity demand from the grid by the household.</li> </ul> <p>In the yearly results relevant parameters used in the publication were:</p> <ul> <li>ID_Scenario</li> <li>TotalCost: represent the yearly operation cost</li> <li>Grid: electricity demand summed up for the whole year</li> </ul> <p>5 different electricity prices are used for scenario generation. The first price is constant, “electricity_2” is the real time price from 2021 plus a hypothetical grid fee of 20cents/kWh. “electricity_3, electricity_4, electricity_5” are prices generated for 2030 for Austria with the Balmorel model. Their profiles can be found under “OperationScenario_EnergyPrice”.</p> <p> </p>
Replacing gas boilers with heat pumps is the fastest way to cut German gas consumption
<p>This Excel file contains tables S1 to S7 of the paper "Replacing gas boilers with heat pumps is the fastest way to cut German gas consumption"</p>
Simulation results of advanced control for tri-generation heat pumps
<p>The data of this dataset comes from simulations performed in the software TRNSYS. The simulations were performed for the study case of a multi-family building situated in the climate of Tarragona, Spain, where the HVAC systems comprise a centralized dual source heat pump system. </p> <p>The simulations were done for 3 representative weeks selected for different seasons (winter, spring, summer). Each time, the simulation is performed twice: once with a standard reference control, and a second time with the advanced energy management system (AEMS) in control, programmed in GAMS and coupled with the TRNSYS simulation. Hence there are 6 tests in total, one per Excel sheet in the dataset file. The description of the columns is shown in the following table:</p> <table> <tbody> <tr> <td>Name</td> <td>Unit</td> <td>Description</td> </tr> <tr> <td>Tamb</td> <td>ºC</td> <td>Ambient outdoor temperature</td> </tr> <tr> <td>Irr</td> <td>kJ/h.m2</td> <td>Solar irradiation horizontal</td> </tr> <tr> <td>Troom</td> <td>ºC</td> <td>Room temperature</td> </tr> <tr> <td>Troom_set</td> <td>ºC</td> <td>Room set-point temperature</td> </tr> <tr> <td>Pel_FCU</td> <td>kW</td> <td>Electrical power consumption of the FCU</td> </tr> <tr> <td>Qth_cool_FCU</td> <td>kW</td> <td>Thermal cooling power of the FCU</td> </tr> <tr> <td>Qth_heat_RadFl</td> <td>kW</td> <td>Thermal heating power of the radiant floor</td> </tr> <tr> <td>TDHW_up</td> <td>ºC</td> <td>Temperature at the top of the DHW tank</td> </tr> <tr> <td>TDHW_lo</td> <td>ºC</td> <td>Temperature at the bottom of the DHW tank</td> </tr> <tr> <td>TSHC_up</td> <td>ºC</td> <td>Temperature at the top of the SHC tank</td> </tr> <tr> <td>TSHC_lo</td> <td>ºC</td> <td>Temperature at the bottom of the SHC tank</td> </tr> <tr> <td>Pel_HH_kW</td> <td>kW</td> <td>Electrical power consumption of the appliances</td> </tr> <tr> <td>Pel_PV_kW</td> <td>kW</td> <td>Electrical power generation of the PV</td> </tr> <tr> <td>Pel_HVAC_kW</td> <td>kW</td> <td>Electrical power consumption from the HVAC incl. HP</td> </tr> <tr> <td>Pel_Grid_kW</td> <td>kW</td> <td>Electrical exchange with the grid</td> </tr> <tr> <td>Pel_Bat_kW</td> <td>kW</td> <td>Charging/discharging power of the battery</td> </tr> <tr> <td>SOC_Bat</td> <td>%</td> <td>State of charge of the battery</td> </tr> <tr> <td>Qth_SH_kW</td> <td>kW</td> <td>Thermal heating power produced by the HP for space heating</td> </tr> <tr> <td>Qth_SC_kW</td> <td>kW</td> <td>Thermal cooling power produced by the HP for space cooling</td> </tr> <tr> <td>Qth_DHW_kW</td> <td>kW</td> <td>Thermal heating power produced by the HP for DHW</td> </tr> <tr> <td>Pel_HP_kW</td> <td>kW</td> <td>Electrical consumption of heat pump</td> </tr> </tbody> </table> <p>These results were extensively described in the deliverable D6.5 of the TRI-HP project. </p>
Economic assessment of photovoltaic heat pump systems
<p>The economic viability of photovoltaic heat pump systems is assessed for an industrial application, comparing Self-Consumption and Autonomous configurations. </p>
Dataset for "Research on the effect of the refrigerant charge in a variable capacity heat pump"
<p>The Excel file contains raw experimental data of 75 experiments.<br>Measured parameters include: temperatures (T), gauge pressures (P), volumetric flow rates (V), compressor electric power (Welec) and atmopheric pressure.<br>See Figure 1 of the paper for the numbering and position of the different sensors.<br>See Table 2 of the paper for the types of sensors used and their accuracies.</p>
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