97 skills found · Page 1 of 4
OpenFAST / OpenfastMain repository for the NREL-supported OpenFAST whole-turbine and FAST.Farm wind farm simulation codes.
NatLabRockies / HPCA collection of various resources, examples, and executables for the general NLR HPC user community's benefit. Use the following website for accessing documentation.
nre-learning / Nrelabs CurriculumLearn next-generation skills for network engineers, all in your browser.
NatLabRockies / Hsds ExamplesExamples of using the HSDS Service to Access NREL WIND Toolkit data
NatLabRockies / REopt APIThe model for the REopt API, which is used as the back-end for the REopt Webtool (reopt.nrel.gov/tool), and can be accessed directly via the NREL Developer Network (https://developer.nrel.gov/docs/energy-optimization/reopt)
klausbrunner / SolarpositioningJava sun position code (topocentric coordinates, sunrise/sunset/twilight) based on the NREL SPA and ENEA/Grena algorithms.
sammwyy / NRelayW.I.P Ngrok Alternative: Self-hosted and open-source OOB reverse tunnel (TCP/UDP/SNI/HTTP/MC)
aladdine / Essential Solar Energy And Storage Software ResourcesCurated links to APIs, SDKs, paltforms and tools relevant to solar energy and battery storage
NatLabRockies / WexWEX, which is short for WxWidgets Extensions, is a cross-platform library of graphical user interface tools that extends the popular open-source project WxWidgets. WEX includes many features including the powerful DView program (https://github.com/NREL/wex/wiki/DView), which provides an easy-to-use way to visualize complex time series data.
slopp / MyhybridDemo of a Reticulated Shiny App, using NREL's FASTSim model to compare vehicle MPGs for a user defined trip.
nrcharles / Solpypython library to model solar system power performance similar to PVWatts or NREL's System Advisor Model(SAM)
NatLabRockies / Developer.nlr.govAn issue tracker for NREL's APIs available at https://developer.nrel.gov
NatLabRockies / GEOPHIRES XGEOPHIRES is NREL's free and open-source geothermal techno-economic simulator.
borgestassio / Wind Turbine ControlControllers designed to the 5MW NREL wind turbine using Simulink and Fast V8
deanhiller / Databustime series data in cassandra with visualization(NREL's opensource databus project)
mahdi-usask / Wind Speed Forecasting For Wind Power Generation Plant. Neural Network ML Based Prediction Algo. For largescale wind power penetration Wind speed prediction is a basic requirement of wind energy generation. There are many artificial neural network (ANN), ARMA, ARIMA approaches proposed in the recent literature in order to tackle this problem. This paper will use the artificial neural network (ANN) approach to get a prediction of wind speed using historical wind speed data. The historical data used here were gathered from NREL website ,as hourly basis from 80 meter hub height. The measurement location is NREL Flatirons Campus (M2). The readings displayed are derived from instruments mounted on or near a 82 meter (270 foot) meteorological tower located at the western edge of the Flatirons Campus (formerly NWTC) and about 11 km (7 miles) west of Broomfield, and approximately 8 km (5 miles) south of Boulder, Colorado. The tower is located at 39o 54' 38.34" N and 105o 14' 5.28" W (datum WGS84) with its base at an elevation of 1855 meters (6085 feet) above mean sea level. Data from year 2014 to 2018, in total 5 years of data has been used here as dataframe. Here the neural network has been implemented by Tensorflow’s Keras API. The used model is “sequential”. Four dense layer has been used in the optimized model. LSTM(Long- short-term memory) architecture has been used here as neural network architecture. Activation function being used in the dense layers are dropout function. The optimizer being used here is Adam. Here various range of Dropout function has been examined and chosen the best fit for this model. Also this paper examined various kinds of optimization method and used the best fitted one. The model performances were evaluated using the mean squared error using adam optimizer. Various kinds of data analytic techniques has been used here for better visualization and in depth understanding of the dataset and its variables. Since it is mostly a time series data so in the analytic part how the data is being changed with time has been shown. From the result of the predicted dataset it can be state that, this wind speed prediction model works best for all kinds of winds speed besides overfitted/ abnormal wind speeds which is a very rare case scenario.
NatLabRockies / ComStockNational scale modeling of the U.S. commercial building stock supported by U.S. DOE, LADWP, and others and maintained by NREL
NatLabRockies / Openfast Turbine ModelsA repository of OpenFAST turbine models developed by NREL researchers.
NREL-Sienna / InfrastructureSystems.jlUtility package for Sienna's simulation infrastructure
thomas-crane / NrelayA console based modular client for Realm of the Mad God built with Node.js and TypeScript.
