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2021-code-a-velocity-quasilpv-mpc-algorithm-for-wind-turbine-control

Code for paper "A-Velocity-quasiLPV-MPC-Algorithm-for-Wind-Turbine-Control"

3dwindturbinesimulator

a 3D Simulator that can design a wind farm by PSO technique in a continuous space, as well as can design in Grid base wind farm layout. The simulator will provide 3D environment system and control with simulated values, simulation of wake effect and air flow in the environment and present simulation results into graphical format that can be used in future for analysis

advanced-controls-for-maximizing-wind-turbine-power-coefficient-in-matlab_simulink

basicdtucontroller

This repository is no longer being updated, and has been moved to DTU Wind Energy's GitLab server: https://gitlab.windenergy.dtu.dk/OpenLAC/BasicDTUController

bemused

Blade Element Momentum calculations in Python

bladeblockmesh

Create a wind turbine mesh using blockMesh

dissertation

dotx-wind-turbine-controller

Dotx Wind Turbine Controller (DWTC)

drl-for-microgrid-energy-management

We study the performance of various deep reinforcement learning algorithms for the problem of microgrid’s energy management system. We propose a novel microgrid model that consists of a wind turbine generator, an energy storage system, a population of thermostatically controlled loads, a population of price-responsive loads, and a connection to the main grid. The proposed energy management system is designed to coordinate between the different sources of flexibility by defining the priority resources, the direct demand control signals and the electricity prices. Seven deep reinforcement learning algorithms are implemented and empirically compared in this paper. The numerical results show a significant difference between the different deep reinforcement learning algorithms in their ability to converge to optimal policies. By adding an experience replay and a second semi-deterministic training phase to the well-known Asynchronous advantage actor critic algorithm, we achieved considerably better performance and converged to superior policies in terms of energy efficiency and economic value.

dtu10mw_sowfa

An ALMAdvanced implementation of the DTU 10MW turbine for SOWFA

eacontrol_fast

f2a

F2A is an aero-hydro-servo-elastic tool developed based on AQWA by Yang Yang, a postdoctoral research associate in Liverpool John Moores University for performing fully coupled analysis of floating offshore wind turbines (FOWT). The aero-servo-elastic simulation capabilities are fully implemented within the user_force64.dll which is a built-in DLL of AQWA for external force calculation. For a coupled analysis of a floating offshore wind turbine subjected to wind, wave and current loadings, the aerodynamic loads acting on the rotor, the elastic responses of the blades and tower, and the servo-control are examined through the DLL, considering the influence from the platform motions. The platform position, velocity and acceleration at each degree of freedom are passed into the DLL to update the kinematics of the upper structures. Before being passed into DLL, these terms are transformed from the inertial coordinate system to the local coordinate system of the platform.

fasttool

NREL FASTv8, with MATLAB GUI and Simulink integration

fastv8driverprogram

Driver Program for FAST v8

fatigue_cvae

Code for "Conditional Variational Autoencoders for Probabilistic Wind Turbine Blade Fatigue Estimation using SCADA data"

iea-15-240-rwt

15MW reference wind turbine repository developed in conjunction with IEA Wind

iecwind

iot-and-cloud-based-remote-monitoring-of-wind-turbine

The project aims to collect, monitor and analyze the data obtained from various sensors and Visualization of data using Node-red platform

livefft

Real-time spectrum analyser in Python

ml-web-service

A Flask Web Service that uses Machine Learning to make predictions based of a Power Production of a Wind Turbine Data Set.

moorpy

nrel-5mw-controller

Python implementation of the torque and pitch controller for the NREL 5MW wind turbine

nrel-iecwind

NREL IECWind

openfast

Main repository for the NREL-supported OpenFAST whole-turbine simulation code. Further documentation is available at

pce-surrogates-for-power-and-loads-under-wind-farm-control

The code is part of the development to create fast and reliable surrogate models for yaw-based wind farm control. The surrogates, based on polynomial chaos expansion, are built using high fidelity flow simulations combined with aeroelastic simulations of the turbine performance and loads. The code is still in development and will be updated on a continuous basis

predicting-the-energy-output-of-wind-turbine

A web app built using Django to recommend the Power Grid to suggest the best time to utilize the energy from wind farm that uses Stacked LSTM model to predict power output from 1hr to 72hrs.

py-bem

Python implementation of Blade Element Momentum wind turbine aerodynamics

python-turbine-blade-designer

Python project to design wind turbine blade geometry, based on the blade element method. This is a re-written and enhanced version of the old MATLAB project (nicola-sorace/turbine_blade_designer).

pyturbsim

pyTurbSim is a turbulence simulation tool for HydroKinetic (tidal, river and ocean-current) turbine device design tools (e.g. NWTC's FAST). It is also an effective development platform for new TurbSim spectral models.

pywake

Mirror of https://gitlab.windenergy.dtu.dk/TOPFARM/PyWake