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87 results for “Hydropower”
ENTSO-E Hydropower modelling data (PECD) in CSV format
<p>PECD Hydro modelling</p> <p>This repository contains a more user-friendly version of the <code>Hydro modelling data</code> released by ENTSO-E with their <a href="https://www.entsoe.eu/outlooks/seasonal/">latest Seasonal Outlook</a>.</p> <p>The original URLs:</p> <ul> <li>The zipped file: <a href="https://eepublicdownloads.blob.core.windows.net/public-cdn-container/clean-documents/sdc-documents/seasonal/SOR2020/data/Hydro.zip">https://eepublicdownloads.blob.core.windows.net/public-cdn-container/clean-documents/sdc-documents/seasonal/SOR2020/data/Hydro.zip</a></li> <li>The documentation file (v 1.0): <a href="https://eepublicdownloads.blob.core.windows.net/public-cdn-container/clean-documents/sdc-documents/MAF/2019/Hydropower_Modelling_New_database_and_methodology.pdf">https://eepublicdownloads.blob.core.windows.net/public-cdn-container/clean-documents/sdc-documents/MAF/2019/Hydropower_Modelling_New_database_and_methodology.pdf</a></li> </ul> <p>The original ENTSO-E hydropower dataset integrates the PECD (Pan-European Climate Database) released for the <a href="https://www.entsoe.eu/outlooks/midterm/#download">MAF 2019</a></p> <p>As I did for the <a href="https://zenodo.org/record/3702418">wind & solar data</a>, the datasets released in this repository are <strong>only</strong> a more user- and machine-readable version of the original Excel files. As avid user of ENTSO-E data, with this repository I want to share my data wrangling efforts to make this dataset more accessible.</p> <p><strong>Data description</strong></p> <p>The <a href="https://eepublicdownloads.blob.core.windows.net/public-cdn-container/clean-documents/sdc-documents/seasonal/SOR2020/data/Hydro.zip">zipped file</a> contains 86 Excel files, two different files for each ENTSO-E zone.</p> <p>In this repository you can find 6 CSV files:</p> <ul> <li><code>PECD-hydro-capacities.csv</code>: installed capacities</li> <li><code>PECD-hydro-weekly-inflows.csv</code>: weekly inflows for reservoir and open-loop pumping</li> <li><code>PECD-hydro-daily-ror-generation.csv</code>: daily run-of-river generation</li> <li><code>PECD-hydro-weekly-reservoir-min-max-generation.csv</code>: minimum and maximum weekly reservoir generation</li> <li><code>PECD-hydro-weekly-reservoir-levels.csv</code>: weekly reservoir levels</li> <li><code>PECD-hydro-weekly-reservoir-min-max-uniform-levels.csv</code>: weekly minimum and maximum reservoir levels to use outside the climate years</li> </ul> <p><strong>Capacities</strong></p> <p>The file <code>PECD-hydro-capacities.csv</code> contains: run of river capacity (MW) and storage capacity (GWh), reservoir plants capacity (MW) and storage capacity (GWh), closed-loop pumping/turbining (MW) and storage capacity and open-loop pumping/turbining (MW) and storage capacity. The data is extracted from the Excel files with the name starting with <code>PEMM</code> from the following sections:</p> <ul> <li>sheet <code>Run-of-River and pondage</code>, rows from 5 to 7, columns from 2 to 5</li> <li>sheet <code>Reservoir</code>, rows from 5 to 7, columns from 1 to 3</li> <li>sheet <code>Pump storage - Open Loop</code>, rows from 5 to 7, columns from 1 to 3</li> <li>sheet <code>Pump storage - Closed Loop</code>, rows from 5 to 7, columns from 1 to 3</li> </ul> <p><strong>Inflows</strong></p> <p>The file <code>PECD-hydro-weekly-inflows.csv</code> contains the weekly inflow (GWh) for the climatic years 1982-2017 for reservoir plants and open-loop pumping. The data is extracted from the Excel files with the name starting with <code>PEMM</code> from the following sections:</p> <ul> <li>sheet <code>Reservoir</code>, rows from 13 to 66, columns from 16 to 51</li> <li>sheet <code>Pump storage - Open Loop</code>, rows from 13 to 66, columns from 16 to 51</li> </ul> <p><strong>Daily run-of-river</strong></p> <p>The file <code>PECD-hydro-daily-ror-generation.csv</code> contains the daily run-of-river generation (GWh). The data is extracted from the Excel files with the name starting with <code>PEMM</code> from the following sections:</p> <ul> <li>sheet <code>Run-of-River and pondage</code>, rows from 13 to 378, columns from 15 to 51</li> </ul> <p><strong>Miminum and maximum reservoir generation</strong></p> <p>The file <code>PECD-hydro-weekly-reservoir-min-max-generation.csv</code> contains the minimum and maximum generation (MW, weekly) for reservoir-based plants for the climatic years 1982-2017. The data is extracted from the Excel files with the name starting with <code>PEMM</code> from the following sections:</p> <ul> <li>sheet <code>Reservoir</code>, rows from 13 to 66, columns from 196 to 231</li> <li>sheet <code>Reservoir</code>, rows from 13 to 66, columns from 232 to 267</li> </ul> <p><strong>Reservoir levels</strong></p> <p>The file <code>PECD-hydro-weekly-reservoir-levels.csv</code> contains the minimum, maximum and the exact reservoir levels at beginning of each week (scaled coefficient from 0 to 1) for each climate year. The data is extracted from the Excel files with the name starting with <code>PEMM</code> from the following sections:</p> <ul> <li>sheet <code>Reservoir</code>, rows from 13 to 66, column 340 to 375</li> <li>sheet <code>Reservoir</code>, rows from 13 to 66, column 376 to 411</li> <li>sheet <code>Reservoir</code>, rows from 13 to 66, column 412 to 447</li> </ul> <p><strong>Reservoir levels</strong></p> <p>The file <code>PECD-hydro-weekly-reservoir-min-max-uniform-levels.csv</code> contains the minimum, maximum and the exact reservoir levels at beginning of each week (scaled coefficient from 0 to 1). The number are supposed to be used when climate years cannot be used (e.g. outside the range 1982-2017). The data is extracted from the Excel files with the name starting with <code>PEMM</code> from the following sections:</p> <ul> <li>sheet <code>Reservoir</code>, rows from 14 to 66, column 12</li> <li>sheet <code>Reservoir</code>, rows from 14 to 66, column 13</li> </ul> <p><strong>CHANGELOG</strong></p> <p>[2020/08/14] Added missing inflows for some countries (including Norway)<br> [2020/07/20] The old reservoir levels have been renamed 'uniform' consisting with the PECD source data. Added min, max and exact levels<br> [2020/07/17] Added maximum generation for the reservoir</p>
Methane ebullition fluxes from hydropower reservoirs: dataset
<p>Dataset relevant to the article: Diel pumped-storage operation minimizes methane ebullition fluxes from hydropower reservoirs. DOI: 10.1029/2020WR027221</p>
Potential power scenario for solar, wind and hydropower in Europe
<p>Data for power scenario used to assess climate impact on solar, wind and hydropower over a 35-year historical period.</p><p> </p><p><strong>Structure and content of data repository</strong></p><p>Here, we provide information on the data used in the investigation of the scientific article "Continental complementarity of renewable energy mixes" by Wörman et al., Nature Communications Engineering.</p><p>Hydro-climatic data was obtained from the Copernicus ECMWF database for an area of 13 106 km2 covering most parts of Europe and the Middle East. The hydropower potential was calculated at the locations of hydropower stations included in the GranD data base (Beams et al., 2019). Runoff was calculated based on the E-HEPE model (Hundecha et al., 2016) and this was used to estimate the hydropower potential at station locations (Wörman et al., 2017) and to generalize these values to 362 of totally 1,055 uniformly distributed sub-areas covering Europe (see figure below). The primary data used to derive the hydropower data contained in this repository is available at this link:</p><p>Virtual Energy Storage – Hydropower, DOI: 10.5281/zenodo.3706758</p><p>Daily data of the Surface Solar Radiation Downwards (SSRD) from 01-01-1979 to 31-12-2020 was obtained from Copernicus ECMWF database and converted to radiation incident on a fixed, south-facing panel with an inclination equal to the latitude and, further, covered to PV power potential according to Huld et al (2011, 2015). The power potential was averaged over 24 hours (both night and day) under consideration of changes in the solar elevation and azimuth angles as well as aggregated for 995 of the 1,055 sub-areas. A data report is available in catalogue 4. </p><p>Meteorological data with the relevance to wind power potential was obtained from ERA5, a reanalysis product of the ECMWF's General Circulation Model available in the Copernicus Climate Data Store. For comparison, data was also taken from Merra 2 and JRA 55 and used to derive wind speed time-series from 01/01/1979 till 31/12/2019 at the location of 20,010 onshore wind farms from the "World Wind Farm Database". The primary data used to derive the solar PV power data contained in this repository is available in catalogue 4 of this repository. The primary data used to derive the wind power data contained in this repository is available at this link:</p><p>Virtual Energy Storage - Wind power, DOI: 10.5281/zenodo.7749150</p><p>The data representing power scenarios for solar, wind and hydropower are structured in five folders sharing information on different variables and their physiographic characteristics. A ReadMe file is provided in each folder to describe the format of every file:</p><p><strong>1. Temporal mean power for solar-wind-hydro at 1,055 areas</strong></p><p>This folder provides the mean power for the three renewable sources with the following geographical division (Mean_Hydro, Mean_Solar, Mean_Wind). This catalogue also contains information on area id referring to the geographical data files as well as area values and coordinates (ReadMe_mean power CSV).</p><p><strong>2. Geographical data</strong></p><p>This folder contains the following sub-folders and information:</p><ol><li>Shape files for the 1,055 areas depicted above (shapefile_solar_domain)</li><li>Shape file of Europe and parts of the Middle East including different nations (Europe_Shapefile)</li><li>An Excel file with geodata för the 1,055 areas (areas_points_land)</li></ol><p><strong>3. GranD_Hydropower time-series</strong></p><p>This folder contains the following sub-folders and information:</p><ol><li>A ReadMe file</li><li>Temporal mean values of potential hydropower production estimated at GranD hydropower stations (Temporal mean values)</li><li>Linear scaling of the above time-series to match the reported national annual mean hydropower production</li></ol><p><strong>4. Solar power_Time-series_Excel</strong></p><p>This folder contains the following files:</p><ol><li>A data report describing how Copernicus ERA5 data has been used to estimate solar radiation density and conversion to panel power for different panel types (Readme_Accessing_Solar_Data)</li><li>Excel sheets with power density time series for the incident solar radiation (cSolarTimeSeries_ssrd24.xlsx) and two panel types (cSolarTimeSeries_ssrd24, cSolarTimeSeries_CdTe24). The values represents 24h averages.</li></ol><p><strong>5. Time-series of 1055 regions </strong></p><p>This folder contains the daily time-series used in a full assessment of solar, wind and hydropower system based on the above solar power, wind power and hydropower.</p><p>A readme file is also provided.</p><ol><li>Various information, including electric consumption data</li><li>Data on electric consumption extracted on 25/10/2022 13:35:55 from [ESTAT]</li><li>Matlab file used to derive average monthly consumption pattern based on 6a)</li><li>Energy storage capacity in Euopean Hydropower according to data collected by Prof. em. Killingtveit.</li><li>National hydropower production used to scale hydropower estimated at GranD stations to the national production level</li><li>Simulation results used for Figure 3</li></ol><p><strong>6. Various information including electric consumption</strong></p><p> </p><p><strong>References</strong></p><p>Beames at al., 2019. Global Reservoir and dam (GRanD) Database: technical documentation – version 1.3. February 2019. <a href="http://globaldamwatch.org/">http://globaldamwatch.org</a></p><p>Huld, T. and Ana M.G. Amillo. Estimating PV Module Performance over Large Geographical Regions: The Role of Irradiance, Air Temperature, Wind Speed and Solar Spectrum. In: Energies 8 (2015), pp. 5159{5181. doi: <a href="http://dx.doi.org/10.3390/en8065159">http://dx.doi.org/10.3390/en8065159</a>.</p><p>Huld, T.A.; Friesen, G.; Skoczek, A.; Kenny, R.A.; Sample, T.; Field, M.; Dunlop, E.D. A, power-rating model for crystalline silicon PV modules. Solar Energy Mater. Solar Cells 2011, 95, 3359–3369.</p><p>Hundecha, Y., Arheimer, B., Donnelly, C. and Pechlivanidis, I.: A regional parameter estimation scheme for a pan-European multi-basin model, Journal of Hydrology: Regional Studies, 6(Supplement C), 90–111, doi:<a href="https://doi.org/10.1016/j.ejrh.2016.04.002">https://doi.org/10.1016/j.ejrh.2016.04.002</a>, 2016.</p><p>Wörman, A., Lindström, G., Riml, J., 2017. "The Power of Runoff", J. Hydrology, 548(2017): 784-793, dx.doi.org/10.1016/j.jhydrol.2017.03.041</p>
G-Res data for 3 hydropower reservoirs in Myanmar
Open the record for dataset details and reuse information.
Hydropower Generator (Biogas) - a prototype
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Supplementary Data: Cloud-based multi-dimensional parallel dynamic programming algorithm for a hydropower station system
<p>The files in this record contain data for cloud-based multi-dimensional parallel dynamic programming algorithm for a hydropower station system considered for publication in Water Resources Research.</p> <p>The files consist of:</p> <ul> <li>cascade reservoir system data;</li> <li>Source code and results of the parallel dynamic programming algorithm program on the physical machine;</li> <li>Source code and results of the parallel dynamic programming algorithm program on the cloud virtual machine;</li> </ul>
Figure 1 from: Ek K, Goytia S, Lundmark C, Nysten-Haarala S, Pettersson M, Sandström A, Söderasp J, Stage J (2017) Challenges in Swedish hydropower – politics, economics and rights. Research Ideas and Outcomes 3: e21305. https://doi.org/10.3897/rio.3.e21305
Figure 1 - The challenges of two parallel water management systems.
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