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{"references": ["O Pires, X Munduate, O Ceyhan, M Jacobs, H Snel. (2016) Analysis of high Reynolds numbers effects on a wind turbine airfoil using 2D wind tunnel test data. Journal of Physics: Conference Series 753 (2016) 022047. 2016. http://dx.doi.org/10.1088/1742-6596/753/2/022047", "O Pires, X Munduate, O Ceyhan, M Jacobs, J Madsen and J G Schepers. (2016) Analysis of the high Reynolds number 2D tests on a wind turbine airfoil performed at two different wind tunnels. Journal of Physics: Conference Series 749 (2016) 012014. 2016 http://dx.doi.org/10.1088/1742-6596/749/1/012014", "Ozlem Ceyhan, Oscar Pires, Xabier Munduate, Niels N. Sorensen, Alois Peter Schaffarczyk, Torben Reichstein, Konstantinos Diakakis, Giorgos Papadakis, Elia Daniele, Michael Schwarz, Thorsten Lutz, and Raul Prieto. (2017) Summary of the Blind Test Campaign to predict the High Reynolds number performance of DU00-W-210 airfoil, 35th Wind Energy Symposium, AIAA SciTech Forum, (AIAA 2017-0915) http://dx.doi.org/10.2514/6.2017-0915"]} Within EU FP7 AVATAR project (AdVanced Aerodynamic Tools of lArge Rotors), a high Reynolds number and low Mach number wind tunnel test has been performed with the aim to obtain reliable data that can be used to validate existing aerodynamic models for this operating range. The test has been performed at the DNW High Pressure Wind Tunnel in Göttingen (HDG).

Aerodynamic experiments have been executed in the wind tunnel and on a wind turbine blade to measure the impact of roughness on the airfoil characteristics and the associated effect on rotor performance and to establish the transition location on a rotating blade. The wind tunnel tests have been performed in the low-speed, low-turbulence wind tunnel of TUDelft. The wind turbine tests were carried out at ECN’s Wind Turbine Test Site. Roughness simulation material has been installed on the airfoil leading edge to measure the impact on airfoil performance. Microphones were mounted on the airfoil surface to detect the boundary layer laminar to turbulent transition position both on the wind tunnel model and on the wind turbine blade.

This dataset includes the data used for production of WISE map layers for annual freshwater abstraction, use for hydropower and cooling water as well as data on population per country or river basin district (RBD) used for the normalisation.

This spatio-temporal dataset contains capacity factors timeseries for locations on a grid with 50km edge length in Europe. The data is resolved in one hour timesteps and comprises the years 2000--2016. It has been generated using Renewables.ninja and is based on MERRA-2 reanalysis data. For each of the ~2700 onshore location, it contains one time series for onshore wind turbines and five time series for PV installations with different orientations and tilts. PV time series exist for (1) installations on open fields, (2) installations on all possible rooftops, (3) south-facing and flat rooftops, (4) east- and west-facing rooftops, (5) north-facing rooftops. For each of the ~2800 offshore location there is one timeseries for offshore wind turbines. Two GeoTIFF files contain spatial information of onshore and offshore locations. For each of the three technologies -- onshore wind, offshore wind, and PV -- there is one NetCDF file determining the temporal dimension and containing the data. The GeoTIFF and NetCDF files are linked through unique IDs for all locations. This data serves as input data to euro-calliope, a model of the European electricity system. The following parameters have been used to generate the timeseries: resolution-grid: 50 # [km^2] corresponding to MERRA resolution pv-performance-ratio: 0.9 hub-height: onshore: 105 # m, median hub height of V90/2000 in Europe between 2010 and 2018 offshore: 87 # m, median hub height of SWT-3.6-107 in Europe between 2010 and 2018 turbine: onshore: "vestas v90 2000" # most built between 2010 and 2018 in Europe offshore: "siemens swt 3.6 107" # most built between 2010 and 2018 in Europe {"references": ["Tr\u00f6ndle, T., Pfenninger, S., & Lilliestam, J. (2019). Home-made or imported: On the possibility for renewable electricity autarky on all scales in Europe. Energy Strategy Reviews, 26, 100388. https://doi.org/10.1016/j.esr.2019.100388"]}

This dataset is a subset of the TotalControl windfarm dataset compiled in the context of FarmConners Wind Farm Control Benchmark project for code comparison. This case aims to investigate the quantities of interest in a row of normally operating turbines, for a fully aligned 8 turbine configuration. It should be noted that the configuration is a subset of a wind farm simulation, i.e. there are additional blockage effects. The python files "plot_cross_sections.py" and "plot_performance.py" are to be used for loading and visualizing the velocity field through turbines stored in "cross_sections_timeseries.h5" and the turbine performance in "turb_performance.h5" respectively. The inflow in this case is a Conventionally Neutral Boundary Layer (CNBL) with a capping inversion of 4K strength at a height of 250 m. The precursor data of the atmospheric boundary layer simulations without any turbines is publicly available in the online zenodo repository at https://zenodo.org/communities/totalcontrolflowdatabase/. The complete datasets for the TotalControl windfarm simulations area available at https://zenodo.org/communities/totalcontrolwindfarmdatabase/

In Task 2.1 of hybridGEOTABS project, an optimal load splitting algorithm (OLSA) was developed and validated. The OLSA splits the building thermal loads (calculated in T2.2 of the project) to the baseload and residual loads. The baseload is defined as the maximum share of GEOTABS that allows to minimise the energy use of the entire (primary + secondary) heating and cooling system, while maintaining thermal comfort in the building and by using and taking into account the thermal storage in the TABS. The algorithm is documented in detail in D2.1 of the hybridGEOTABS project. This document reports all the parameter values used in the OLSA.

The EVIDENT Discrete Choice Experiment seeks to explore the impact of energy-related financial literacy, consumer motivation, point-of-sale information and demographic factors on discount rates and willingness to pay for efficient household appliances. Across a series of choice experiments, the impact of factors such as financial information (purchase price, operating cost, salience of financial information), risk reduction (i.e. extended warranty), and financial capacity (i.e. low-cost loans) on implicit discount rates for home appliances is examined. Further, the impact of direct rebound rates on efficient appliance selection is examined. weather Sweden environmental data Swedish climate data Sweden weather data Sweden temperature data Sweden humidity data Swedish meteorological data Sweden city climate data Swedish city weather data Sweden city temperature data Sweden city humidity data Swedish urban climate data Sweden urban weather data Sweden urban temperature data Sweden urban humidity data Dataset of Sweden city temperatures and humidities Dataset of environmental data for 700 Swedish cities Swedish city climate and weather dataset

This paper is to describe an open-source code for optimization of clean energy technologies. The model covers the whole chain of energy systems including mainly 6 areas: renewable energies, clean e ...

Dataset supporting publication: “On Site Monitoring During Nearby Drilling Operations Toward a Geothermal Power System Installation” (publication available in GEOFIT Zenodo) Datasets resultant from structural health monitoring activities (accelerometer data). Among the approaches to the production of “green” energy, geothermal power systems are becoming quite popular in Europe. Their installation in existing buildings requires an extended, external pipes appendix whose laying operation needs a drilling activities nearby structural skeletons often designed to support static loads only, especially when ancient buildings are targeted. This contribution reports and discusses the experimental results achieved within a specific case study within the European project GEOFIT. In particular, standard accelerometric measurements in and nearby a single-story reinforced concrete building are collected and analysed in the absence of drilling (pre-drilling) and during drilling activities (drilling phase) to monitor the structure response to the external source of vibrations related to the excavations phase. The target is to outline automatic guidelines toward installations preventing from any sort of structural damage.